WorldWideScience

Sample records for online error detection

  1. Hybrid online sensor error detection and functional redundancy for systems with time-varying parameters.

    Science.gov (United States)

    Feng, Jianyuan; Turksoy, Kamuran; Samadi, Sediqeh; Hajizadeh, Iman; Littlejohn, Elizabeth; Cinar, Ali

    2017-12-01

    Supervision and control systems rely on signals from sensors to receive information to monitor the operation of a system and adjust manipulated variables to achieve the control objective. However, sensor performance is often limited by their working conditions and sensors may also be subjected to interference by other devices. Many different types of sensor errors such as outliers, missing values, drifts and corruption with noise may occur during process operation. A hybrid online sensor error detection and functional redundancy system is developed to detect errors in online signals, and replace erroneous or missing values detected with model-based estimates. The proposed hybrid system relies on two techniques, an outlier-robust Kalman filter (ORKF) and a locally-weighted partial least squares (LW-PLS) regression model, which leverage the advantages of automatic measurement error elimination with ORKF and data-driven prediction with LW-PLS. The system includes a nominal angle analysis (NAA) method to distinguish between signal faults and large changes in sensor values caused by real dynamic changes in process operation. The performance of the system is illustrated with clinical data continuous glucose monitoring (CGM) sensors from people with type 1 diabetes. More than 50,000 CGM sensor errors were added to original CGM signals from 25 clinical experiments, then the performance of error detection and functional redundancy algorithms were analyzed. The results indicate that the proposed system can successfully detect most of the erroneous signals and substitute them with reasonable estimated values computed by functional redundancy system.

  2. [Research on modeling method to analyze Lonicerae Japonicae Flos extraction process with online MEMS-NIR based on two types of error detection theory].

    Science.gov (United States)

    Du, Chen-Zhao; Wu, Zhi-Sheng; Zhao, Na; Zhou, Zheng; Shi, Xin-Yuan; Qiao, Yan-Jiang

    2016-10-01

    To establish a rapid quantitative analysis method for online monitoring of chlorogenic acid in aqueous solution of Lonicera Japonica Flos extraction by using micro-electromechanical near infrared spectroscopy (MEMS-NIR). High performance liquid chromatography(HPLC) was used as reference method.Kennard-Stone (K-S) algorithm was used to divide sample sets, and partial least square(PLS) regression was adopted to establish the multivariate analysis model between the HPLC analysis contents and NIR spectra. The synergy interval partial least squares (SiPLS) was used to selected modeling waveband to establish PLS models. RPD was used to evaluate the prediction performance of the models. MDLs was calculated based on two types of error detection theory, on-line analytical modeling approach of Lonicera Japonica Flos extraction process was expressed scientifically by MDL. The result shows that the model established by multiplicative scatter correction(MSC) was the best, with the root mean square with cross validation(RMSECV), root mean square error of correction(RMSEC) and root mean square error of prediction(RMSEP) of chlorogenic acid as 1.707, 1.489, 2.362, respectively, the determination coefficient of the calibration model was 0.998 5, and the determination coefficient of the prediction was 0.988 1.The value of RPD is 9.468.The MDL (0.042 15 g•L⁻¹) selected by SiPLS is less than the original,which demonstrated that SiPLS was beneficial to improve the prediction performance of the model. In this study, a more accurate expression of the prediction performance of the model from the two types of error detection theory, to further illustrate MEMS-NIR spectroscopy can be used for on-line monitoring of Lonicera Japonica Flos extraction process. Copyright© by the Chinese Pharmaceutical Association.

  3. Online Community Transition Detection

    DEFF Research Database (Denmark)

    Tan, Biying; Zhu, Feida; Qu, Qiang

    2014-01-01

    communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution......Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave...... of community transition of individual users, adaptive to the noisy behavior. Experiments on real data sets demonstrate the efficiency and effectiveness of our proposed method....

  4. Error handling for the CDF online silicon vertex tracker

    CERN Document Server

    Bari, M; Cerri, A; Dell'Orso, Mauro; Donati, S; Galeotti, S; Giannetti, P; Morsani, F; Punzi, G; Ristori, L; Spinella, F; Zanetti, A M

    2001-01-01

    The online silicon vertex tracker (SVT) is composed of 104 VME 9U digital boards (of eight different types). Since the data output from the SVT (few MB/s) are a small fraction of the input data (200 MB/s), it is extremely difficult to track possible internal errors by using only the output stream. For this reason, several diagnostic tools have been implemented: local error registers, error bits propagated through the data streams, and the Spy Buffer system. Data flowing through each input and output stream of every board are continuously copied to memory banks named spy buffers, which act as built-in logic state analyzers hooked continuously to internal data streams. The contents of all buffers can be frozen at any time (e.g., on error detection) to take a snapshot of all data flowing through each SVT board. The spy buffers are coordinated at system level by the Spy Control Board. The architecture, design, and implementation of this system are described. (4 refs).

  5. Interpreting the change detection error matrix

    NARCIS (Netherlands)

    Oort, van P.A.J.

    2007-01-01

    Two different matrices are commonly reported in assessment of change detection accuracy: (1) single date error matrices and (2) binary change/no change error matrices. The third, less common form of reporting, is the transition error matrix. This paper discuses the relation between these matrices.

  6. Comparing classifiers for pronunciation error detection

    NARCIS (Netherlands)

    Strik, H.; Truong, K.; Wet, F. de; Cucchiarini, C.

    2007-01-01

    Providing feedback on pronunciation errors in computer assisted language learning systems requires that pronunciation errors be detected automatically. In the present study we compare four types of classifiers that can be used for this purpose: two acoustic-phonetic classifiers (one of which employs

  7. Online deforestation detection

    OpenAIRE

    Diaz, Emiliano

    2017-01-01

    Deforestation detection using satellite images can make an important contribution to forest management. Current approaches can be broadly divided into those that compare two images taken at similar periods of the year and those that monitor changes by using multiple images taken during the growing season. The CMFDA algorithm described in Zhu et al. (2012) is an algorithm that builds on the latter category by implementing a year-long, continuous, time-series based approach to monitoring images...

  8. Errors, error detection, error correction and hippocampal-region damage: data and theories.

    Science.gov (United States)

    MacKay, Donald G; Johnson, Laura W

    2013-11-01

    This review and perspective article outlines 15 observational constraints on theories of errors, error detection, and error correction, and their relation to hippocampal-region (HR) damage. The core observations come from 10 studies with H.M., an amnesic with cerebellar and HR damage but virtually no neocortical damage. Three studies examined the detection of errors planted in visual scenes (e.g., a bird flying in a fish bowl in a school classroom) and sentences (e.g., I helped themselves to the birthday cake). In all three experiments, H.M. detected reliably fewer errors than carefully matched memory-normal controls. Other studies examined the detection and correction of self-produced errors, with controls for comprehension of the instructions, impaired visual acuity, temporal factors, motoric slowing, forgetting, excessive memory load, lack of motivation, and deficits in visual scanning or attention. In these studies, H.M. corrected reliably fewer errors than memory-normal and cerebellar controls, and his uncorrected errors in speech, object naming, and reading aloud exhibited two consistent features: omission and anomaly. For example, in sentence production tasks, H.M. omitted one or more words in uncorrected encoding errors that rendered his sentences anomalous (incoherent, incomplete, or ungrammatical) reliably more often than controls. Besides explaining these core findings, the theoretical principles discussed here explain H.M.'s retrograde amnesia for once familiar episodic and semantic information; his anterograde amnesia for novel information; his deficits in visual cognition, sentence comprehension, sentence production, sentence reading, and object naming; and effects of aging on his ability to read isolated low frequency words aloud. These theoretical principles also explain a wide range of other data on error detection and correction and generate new predictions for future test. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Crowdsourcing for error detection in cortical surface delineations.

    Science.gov (United States)

    Ganz, Melanie; Kondermann, Daniel; Andrulis, Jonas; Knudsen, Gitte Moos; Maier-Hein, Lena

    2017-01-01

    With the recent trend toward big data analysis, neuroimaging datasets have grown substantially in the past years. While larger datasets potentially offer important insights for medical research, one major bottleneck is the requirement for resources of medical experts needed to validate automatic processing results. To address this issue, the goal of this paper was to assess whether anonymous nonexperts from an online community can perform quality control of MR-based cortical surface delineations derived by an automatic algorithm. So-called knowledge workers from an online crowdsourcing platform were asked to annotate errors in automatic cortical surface delineations on 100 central, coronal slices of MR images. On average, annotations for 100 images were obtained in less than an hour. When using expert annotations as reference, the crowd on average achieves a sensitivity of 82 % and a precision of 42 %. Merging multiple annotations per image significantly improves the sensitivity of the crowd (up to 95 %), but leads to a decrease in precision (as low as 22 %). Our experiments show that the detection of errors in automatic cortical surface delineations generated by anonymous untrained workers is feasible. Future work will focus on increasing the sensitivity of our method further, such that the error detection tasks can be handled exclusively by the crowd and expert resources can be focused on error correction.

  10. System tuning and measurement error detection testing

    International Nuclear Information System (INIS)

    Krejci, Petr; Machek, Jindrich

    2008-09-01

    The project includes the use of the PEANO (Process Evaluation and Analysis by Neural Operators) system to verify the monitoring of the status of dependent measurements with a view to early measurement fault detection and estimation of selected signal levels. At the present stage, the system's capabilities of detecting measurement errors was assessed and the quality of the estimates was evaluated for various system configurations and the formation of empiric models, and rules were sought for system training at chosen process data recording parameters and operating modes. The aim was to find a suitable system configuration and to document the quality of the tuned system on artificial failures

  11. Error detecting capabilities of the shortened Hamming codes adopted for error detection in IEEE Standard 802.3

    Science.gov (United States)

    Fujiwara, Toru; Kasami, Tadao; Lin, Shu

    1989-09-01

    The error-detecting capabilities of the shortened Hamming codes adopted for error detection in IEEE Standard 802.3 are investigated. These codes are also used for error detection in the data link layer of the Ethernet, a local area network. The weight distributions for various code lengths are calculated to obtain the probability of undetectable error and that of detectable error for a binary symmetric channel with bit-error rate between 0.00001 and 1/2.

  12. Detecting Soft Errors in Stencil based Computations

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, V. [Univ. of Utah, Salt Lake City, UT (United States); Gopalkrishnan, G. [Univ. of Utah, Salt Lake City, UT (United States); Bronevetsky, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-05-06

    Given the growing emphasis on system resilience, it is important to develop software-level error detectors that help trap hardware-level faults with reasonable accuracy while minimizing false alarms as well as the performance overhead introduced. We present a technique that approaches this idea by taking stencil computations as our target, and synthesizing detectors based on machine learning. In particular, we employ linear regression to generate computationally inexpensive models which form the basis for error detection. Our technique has been incorporated into a new open-source library called SORREL. In addition to reporting encouraging experimental results, we demonstrate techniques that help reduce the size of training data. We also discuss the efficacy of various detectors synthesized, as well as our future plans.

  13. Robust online face tracking-by-detection

    NARCIS (Netherlands)

    Comaschi, F.; Stuijk, S.; Basten, T.; Corporaal, H.

    2016-01-01

    The problem of online face tracking from unconstrained videos is still unresolved. Challenges range from coping with severe online appearance variations to coping with occlusion. We propose RFTD (Robust Face Tracking-by-Detection), a system which combines tracking and detection into a single

  14. Detecting and correcting partial errors: Evidence for efficient control without conscious access.

    Science.gov (United States)

    Rochet, N; Spieser, L; Casini, L; Hasbroucq, T; Burle, B

    2014-09-01

    Appropriate reactions to erroneous actions are essential to keeping behavior adaptive. Erring, however, is not an all-or-none process: electromyographic (EMG) recordings of the responding muscles have revealed that covert incorrect response activations (termed "partial errors") occur on a proportion of overtly correct trials. The occurrence of such "partial errors" shows that incorrect response activations could be corrected online, before turning into overt errors. In the present study, we showed that, unlike overt errors, such "partial errors" are poorly consciously detected by participants, who could report only one third of their partial errors. Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected). These two parameters provided independent information. The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection. The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed.

  15. Ac-dc converter firing error detection

    International Nuclear Information System (INIS)

    Gould, O.L.

    1996-01-01

    Each of the twelve Booster Main Magnet Power Supply modules consist of two three-phase, full-wave rectifier bridges in series to provide a 560 VDC maximum output. The harmonic contents of the twelve-pulse ac-dc converter output are multiples of the 60 Hz ac power input, with a predominant 720 Hz signal greater than 14 dB in magnitude above the closest harmonic components at maximum output. The 720 Hz harmonic is typically greater than 20 dB below the 500 VDC output signal under normal operation. Extracting specific harmonics from the rectifier output signal of a 6, 12, or 24 pulse ac-dc converter allows the detection of SCR firing angle errors or complete misfires. A bandpass filter provides the input signal to a frequency-to-voltage converter. Comparing the output of the frequency-to-voltage converter to a reference voltage level provides an indication of the magnitude of the harmonics in the ac-dc converter output signal

  16. Error Detection and Error Classification: Failure Awareness in Data Transfer Scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Louisiana State University; Balman, Mehmet; Kosar, Tevfik

    2010-10-27

    Data transfer in distributed environment is prone to frequent failures resulting from back-end system level problems, like connectivity failure which is technically untraceable by users. Error messages are not logged efficiently, and sometimes are not relevant/useful from users point-of-view. Our study explores the possibility of an efficient error detection and reporting system for such environments. Prior knowledge about the environment and awareness of the actual reason behind a failure would enable higher level planners to make better and accurate decisions. It is necessary to have well defined error detection and error reporting methods to increase the usability and serviceability of existing data transfer protocols and data management systems. We investigate the applicability of early error detection and error classification techniques and propose an error reporting framework and a failure-aware data transfer life cycle to improve arrangement of data transfer operations and to enhance decision making of data transfer schedulers.

  17. Error detection, handling and recovery at the High Level Trigger of the ATLAS experiment at the LHC

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00223972; The ATLAS collaboration

    2016-01-01

    The complexity of the ATLAS High Level Trigger (HLT) requires a robust system for error detection and handling during online data-taking; it also requires an offline system for the recovery of events where no trigger decision could be made online. The error detection and handling ensure smooth operation of the trigger system and provide debugging information necessary for offline analysis and diagnosis. In this presentation, we give an overview of the error detection, handling and recovery of problematic events at the HLT of ATLAS.

  18. Detected-jump-error-correcting quantum codes, quantum error designs, and quantum computation

    International Nuclear Information System (INIS)

    Alber, G.; Mussinger, M.; Beth, Th.; Charnes, Ch.; Delgado, A.; Grassl, M.

    2003-01-01

    The recently introduced detected-jump-correcting quantum codes are capable of stabilizing qubit systems against spontaneous decay processes arising from couplings to statistically independent reservoirs. These embedded quantum codes exploit classical information about which qubit has emitted spontaneously and correspond to an active error-correcting code embedded in a passive error-correcting code. The construction of a family of one-detected-jump-error-correcting quantum codes is shown and the optimal redundancy, encoding, and recovery as well as general properties of detected-jump-error-correcting quantum codes are discussed. By the use of design theory, multiple-jump-error-correcting quantum codes can be constructed. The performance of one-jump-error-correcting quantum codes under nonideal conditions is studied numerically by simulating a quantum memory and Grover's algorithm

  19. Computer-Assisted Detection of 90% of EFL Student Errors

    Science.gov (United States)

    Harvey-Scholes, Calum

    2018-01-01

    Software can facilitate English as a Foreign Language (EFL) students' self-correction of their free-form writing by detecting errors; this article examines the proportion of errors which software can detect. A corpus of 13,644 words of written English was created, comprising 90 compositions written by Spanish-speaking students at levels A2-B2…

  20. Plagiarism Detection by Online Solutions.

    Science.gov (United States)

    Masic, Izet; Begic, Edin; Dobraca, Amra

    2017-01-01

    The problem of plagiarism represents one of the burning issues of the modern scientific world. Detection of plagiarism is a problem that the Editorial Board encounters in their daily work. Software solutions represent a good solution for the detection of plagiarism. The problem of plagiarism will become most discussed topic of the modern scientific world, especially due to the development of standard measures, which rank the work of one author. Investment in education, education of young research personnel about the importance of scientific research, with paying particular attention on ethical behavior, becomes an imperative of academic staff. Editors have to invest additional effort in the development of the base of reviewers team as well as in their proper guidance, because after all, despite the software solutions, they are the best weapon to fight plagiarism. Peer review process should be a key of successful operation of each journal.

  1. Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.

    Science.gov (United States)

    Kreilinger, Alex; Hiebel, Hannah; Müller-Putz, Gernot R

    2016-03-01

    This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection. In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users. We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game. Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs. This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.

  2. Error detection and prevention in Embedded Systems Software

    DEFF Research Database (Denmark)

    Kamel, Hani Fouad

    1996-01-01

    Despite many efforts to structure the development and design processes of embedded systems, errors are discovered at the final stages of production and sometimes after the delivery of the products. The cost of such errors can be prohibitive.Different design techniques to detect such errors...... systems, a formal model for such systems is introduced. The main characteristics of embedded systems design and the interaction of these properties are described. A taxonomy for the structure of the software developed for such systems based on the amount of processes and processors involved is presented.......The second part includes methods and techniques to detect software design errors.The third part deals with error prevention. It starts with a presentation of different models of the development processes used in industry and taught at universities. This leads us to deduce the major causes of errors...

  3. DETECTING AND REPORTING THE FRAUDS AND ERRORS BY THE AUDITOR

    OpenAIRE

    Ovidiu Constantin Bunget; Alin Constantin Dumitrescu

    2009-01-01

    Responsibility for preventing and detecting fraud rest with management entities.Although the auditor is not and cannot be held responsible for preventing fraud and errors, in yourwork, he can have a positive role in preventing fraud and errors by deterring their occurrence. Theauditor should plan and perform the audit with an attitude of professional skepticism, recognizingthat condition or events may be found that indicate that fraud or error may exist.Based on the audit risk assessment, aud...

  4. A study of the laser power online detecting

    Science.gov (United States)

    Zhang, Qiue; Zhang, Rong; Li, Yongzheng

    2008-12-01

    This article introduced a fundamental of new intelligent instruments. It can be used in laser power online detecting. Based in this theory, we have made a new intelligent mini-power meter. The device adopt SPCE061A MPU to control and process the all detected data, Its CPU core is used 16-bits MPU, it is a perfect unit in industry field. It can process complicated digital signals. Its detecting parts adopt high-speed responding and high-sensitive photoelectric dynatron 3DU13 to detecting the beam's output. It respond spectrum is from 0.4 to 1.1µm, can detect any other laser source's online detecting. Which locate in this spectrum range, optical design is made up of 45 degrees high reflect device and dark body scattering structure. The detector receive a little scatter light, use on-chip ADC to sampling the detector's output. By subsection, insert value linearity, proportion calculate to beam's output powers. And then real-time to displaying by LCD. It can communicate to PC by RS232. By communicate to upper instrument and others, the users can use detected data to achieve laser power's closed-loop control, to control laser source's real time output correctly and calibrating by itself. This mini-power meter need use standard power meter to calibrate in installing, after this process, the device can detect laser power's output from 1 to 200 watts correctly. It error is less than 5 percent.

  5. Comparing different approaches for automatic pronunciation error detection

    NARCIS (Netherlands)

    Strik, Helmer; Truong, Khiet Phuong; de Wet, Febe; Cucchiarini, Catia

    2009-01-01

    One of the biggest challenges in designing computer assisted language learning (CALL) applications that provide automatic feedback on pronunciation errors consists in reliably detecting the pronunciation errors at such a detailed level that the information provided can be useful to learners. In our

  6. Automated Error Detection in Physiotherapy Training.

    Science.gov (United States)

    Jovanović, Marko; Seiffarth, Johannes; Kutafina, Ekaterina; Jonas, Stephan M

    2018-01-01

    Manual skills teaching, such as physiotherapy education, requires immediate teacher feedback for the students during the learning process, which to date can only be performed by expert trainers. A machine-learning system trained only on correct performances to classify and score performed movements, to identify sources of errors in the movement and give feedback to the learner. We acquire IMU and sEMG sensor data from a commercial-grade wearable device and construct an HMM-based model for gesture classification, scoring and feedback giving. We evaluate the model on publicly available and self-generated data of an exemplary movement pattern executions. The model achieves an overall accuracy of 90.71% on the public dataset and 98.9% on our dataset. An AUC of 0.99 for the ROC of the scoring method could be achieved to discriminate between correct and untrained incorrect executions. The proposed system demonstrated its suitability for scoring and feedback in manual skills training.

  7. Error-Detecting Identification Codes for Algebra Students.

    Science.gov (United States)

    Sutherland, David C.

    1990-01-01

    Discusses common error-detecting identification codes using linear algebra terminology to provide an interesting application of algebra. Presents examples from the International Standard Book Number, the Universal Product Code, bank identification numbers, and the ZIP code bar code. (YP)

  8. Adaptive skin detection based on online training

    Science.gov (United States)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  9. Setup error in radiotherapy: on-line correction using electronic kilovoltage and megavoltage radiographs

    International Nuclear Information System (INIS)

    Pisani, Laura; Lockman, David; Jaffray, David; Yan Di; Martinez, Alvaro; Wong, John

    2000-01-01

    Purpose: We hypothesize that the difference in image quality between the traditional kilovoltage (kV) prescription radiographs and megavoltage (MV) treatment radiographs is a major factor hindering our ability to accurately measure, thus correct, setup error in radiation therapy. The objective of this work is to study the accuracy of on-line correction of setup errors achievable using either kV- or MV-localization (i.e., open-field) radiographs. Methods and Materials: Using a gantry mounted kV and MV dual-beam imaging system, the accuracy of on-line measurement and correction of setup error using electronic kV- and MV-localization images was examined based on anthropomorphic phantom and patient imaging studies. For the phantom study, the user's ability to accurately detect known translational shifts was analyzed. The clinical study included 14 patients with disease in the head and neck, thoracic, and pelvic regions. For each patient, 4 orthogonal kV radiographs acquired during treatment simulation from the right lateral, anterior-to-posterior, left lateral, and posterior-to-anterior directions were employed as reference prescription images. Two-dimensional (2D) anatomic templates were defined on each of the 4 reference images. On each treatment day, after positioning the patient for treatment, 4 orthogonal electronic localization images were acquired with both kV and 6-MV photon beams. On alternate weeks, setup errors were determined from either the kV- or MV-localization images but not both. Setup error was determined by aligning each 2D template with the anatomic information on the corresponding localization image, ignoring rotational and nonrigid variations. For each set of 4 orthogonal images, the results from template alignments were averaged. Based on the results from the phantom study and a parallel study of the inter- and intraobserver template alignment variability, a threshold for minimum correction was set at 2 mm in any direction. Setup correction was

  10. Online Synthesis for Error Recovery in Digital Microfluidic Biochips with Operation Variability

    DEFF Research Database (Denmark)

    Alistar, Mirela; Pop, Paul; Madsen, Jan

    2012-01-01

    . The droplet volumes can vary erroneously due to parametric faults, thus impacting negatively the correctness of the application. Researchers have proposed approaches that synthesize offline predetermined recovery subroutines, which are activated online when errors occur. In this paper, we propose an online...

  11. Medication error detection in two major teaching hospitals: What are the types of errors?

    Directory of Open Access Journals (Sweden)

    Fatemeh Saghafi

    2014-01-01

    Full Text Available Background: Increasing number of reports on medication errors and relevant subsequent damages, especially in medical centers has become a growing concern for patient safety in recent decades. Patient safety and in particular, medication safety is a major concern and challenge for health care professionals around the world. Our prospective study was designed to detect prescribing, transcribing, dispensing, and administering medication errors in two major university hospitals. Materials and Methods: After choosing 20 similar hospital wards in two large teaching hospitals in the city of Isfahan, Iran, the sequence was randomly selected. Diagrams for drug distribution were drawn by the help of pharmacy directors. Direct observation technique was chosen as the method for detecting the errors. A total of 50 doses were studied in each ward to detect prescribing, transcribing and administering errors in each ward. The dispensing error was studied on 1000 doses dispensed in each hospital pharmacy. Results: A total of 8162 number of doses of medications were studied during the four stages, of which 8000 were complete data to be analyzed. 73% of prescribing orders were incomplete and did not have all six parameters (name, dosage form, dose and measuring unit, administration route, and intervals of administration. We found 15% transcribing errors. One-third of administration of medications on average was erroneous in both hospitals. Dispensing errors ranged between 1.4% and 2.2%. Conclusion: Although prescribing and administrating compromise most of the medication errors, improvements are needed in all four stages with regard to medication errors. Clear guidelines must be written and executed in both hospitals to reduce the incidence of medication errors.

  12. Arduino-based noise robust online heart-rate detection.

    Science.gov (United States)

    Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

    2017-04-01

    This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

  13. Patient identification errors: the detective in the laboratory.

    Science.gov (United States)

    Salinas, Maria; López-Garrigós, Maite; Lillo, Rosa; Gutiérrez, Mercedes; Lugo, Javier; Leiva-Salinas, Carlos

    2013-11-01

    The eradication of errors regarding patients' identification is one of the main goals for safety improvement. As clinical laboratory intervenes in 70% of clinical decisions, laboratory safety is crucial in patient safety. We studied the number of Laboratory Information System (LIS) demographic data errors registered in our laboratory during one year. The laboratory attends a variety of inpatients and outpatients. The demographic data of outpatients is registered in the LIS, when they present to the laboratory front desk. The requests from the primary care centers (PCC) are made electronically by the general practitioner. A manual step is always done at the PCC to conciliate the patient identification number in the electronic request with the one in the LIS. Manual registration is done through hospital information system demographic data capture when patient's medical record number is registered in LIS. Laboratory report is always sent out electronically to the patient's electronic medical record. Daily, every demographic data in LIS is manually compared to the request form to detect potential errors. Fewer errors were committed when electronic order was used. There was great error variability between PCC when using the electronic order. LIS demographic data manual registration errors depended on patient origin and test requesting method. Even when using the electronic approach, errors were detected. There was a great variability between PCC even when using this electronic modality; this suggests that the number of errors is still dependent on the personnel in charge of the technology. © 2013.

  14. An advanced SEU tolerant latch based on error detection

    Science.gov (United States)

    Xu, Hui; Zhu, Jianwei; Lu, Xiaoping; Li, Jingzhao

    2018-05-01

    This paper proposes a latch that can mitigate SEUs via an error detection circuit. The error detection circuit is hardened by a C-element and a stacked PMOS. In the hold state, a particle strikes the latch or the error detection circuit may cause a fault logic state of the circuit. The error detection circuit can detect the upset node in the latch and the fault output will be corrected. The upset node in the error detection circuit can be corrected by the C-element. The power dissipation and propagation delay of the proposed latch are analyzed by HSPICE simulations. The proposed latch consumes about 77.5% less energy and 33.1% less propagation delay than the triple modular redundancy (TMR) latch. Simulation results demonstrate that the proposed latch can mitigate SEU effectively. Project supported by the National Natural Science Foundation of China (Nos. 61404001, 61306046), the Anhui Province University Natural Science Research Major Project (No. KJ2014ZD12), the Huainan Science and Technology Program (No. 2013A4011), and the National Natural Science Foundation of China (No. 61371025).

  15. IMRT QA: Selecting gamma criteria based on error detection sensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Steers, Jennifer M. [Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California 90048 and Physics and Biology in Medicine IDP, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California 90095 (United States); Fraass, Benedick A., E-mail: benedick.fraass@cshs.org [Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California 90048 (United States)

    2016-04-15

    Purpose: The gamma comparison is widely used to evaluate the agreement between measurements and treatment planning system calculations in patient-specific intensity modulated radiation therapy (IMRT) quality assurance (QA). However, recent publications have raised concerns about the lack of sensitivity when employing commonly used gamma criteria. Understanding the actual sensitivity of a wide range of different gamma criteria may allow the definition of more meaningful gamma criteria and tolerance limits in IMRT QA. We present a method that allows the quantitative determination of gamma criteria sensitivity to induced errors which can be applied to any unique combination of device, delivery technique, and software utilized in a specific clinic. Methods: A total of 21 DMLC IMRT QA measurements (ArcCHECK®, Sun Nuclear) were compared to QA plan calculations with induced errors. Three scenarios were studied: MU errors, multi-leaf collimator (MLC) errors, and the sensitivity of the gamma comparison to changes in penumbra width. Gamma comparisons were performed between measurements and error-induced calculations using a wide range of gamma criteria, resulting in a total of over 20 000 gamma comparisons. Gamma passing rates for each error class and case were graphed against error magnitude to create error curves in order to represent the range of missed errors in routine IMRT QA using 36 different gamma criteria. Results: This study demonstrates that systematic errors and case-specific errors can be detected by the error curve analysis. Depending on the location of the error curve peak (e.g., not centered about zero), 3%/3 mm threshold = 10% at 90% pixels passing may miss errors as large as 15% MU errors and ±1 cm random MLC errors for some cases. As the dose threshold parameter was increased for a given %Diff/distance-to-agreement (DTA) setting, error sensitivity was increased by up to a factor of two for select cases. This increased sensitivity with increasing dose

  16. Detecting Predatory Behaviour in Online Game Chats

    DEFF Research Database (Denmark)

    Gudnadottir, Elin Rut; Jensen, Alaina K.; Cheong, Yun-Gyung

    This paper describes a machine learning approach to detect sexually predatory behaviour in the massively multiplayer online game for children, MovieStarPlanet. The goal of this work is to take a chat log as an input and outputs its label as either the predatory category or the non......-predatory category. From the raw in-game chat logs provided by MovieStarPlanet, we first prepared three sub datasets via extensive preprocessing. Then, two machine learning algorithms, naive Bayes and Decision Tree, were employed to model the predatory behaviour using different feature sets. Our evaluation has...

  17. Structural damage detection robust against time synchronization errors

    International Nuclear Information System (INIS)

    Yan, Guirong; Dyke, Shirley J

    2010-01-01

    Structural damage detection based on wireless sensor networks can be affected significantly by time synchronization errors among sensors. Precise time synchronization of sensor nodes has been viewed as crucial for addressing this issue. However, precise time synchronization over a long period of time is often impractical in large wireless sensor networks due to two inherent challenges. First, time synchronization needs to be performed periodically, requiring frequent wireless communication among sensors at significant energy cost. Second, significant time synchronization errors may result from node failures which are likely to occur during long-term deployment over civil infrastructures. In this paper, a damage detection approach is proposed that is robust against time synchronization errors in wireless sensor networks. The paper first examines the ways in which time synchronization errors distort identified mode shapes, and then proposes a strategy for reducing distortion in the identified mode shapes. Modified values for these identified mode shapes are then used in conjunction with flexibility-based damage detection methods to localize damage. This alternative approach relaxes the need for frequent sensor synchronization and can tolerate significant time synchronization errors caused by node failures. The proposed approach is successfully demonstrated through numerical simulations and experimental tests in a lab

  18. Context-Aware Online Commercial Intention Detection

    Science.gov (United States)

    Hu, Derek Hao; Shen, Dou; Sun, Jian-Tao; Yang, Qiang; Chen, Zheng

    With more and more commercial activities moving onto the Internet, people tend to purchase what they need through Internet or conduct some online research before the actual transactions happen. For many Web users, their online commercial activities start from submitting a search query to search engines. Just like the common Web search queries, the queries with commercial intention are usually very short. Recognizing the queries with commercial intention against the common queries will help search engines provide proper search results and advertisements, help Web users obtain the right information they desire and help the advertisers benefit from the potential transactions. However, the intentions behind a query vary a lot for users with different background and interest. The intentions can even be different for the same user, when the query is issued in different contexts. In this paper, we present a new algorithm framework based on skip-chain conditional random field (SCCRF) for automatically classifying Web queries according to context-based online commercial intention. We analyze our algorithm performance both theoretically and empirically. Extensive experiments on several real search engine log datasets show that our algorithm can improve more than 10% on F1 score than previous algorithms on commercial intention detection.

  19. Detection of Patients at High Risk of Medication Errors

    DEFF Research Database (Denmark)

    Sædder, Eva Aggerholm; Lisby, Marianne; Nielsen, Lars Peter

    2016-01-01

    Medication errors (MEs) are preventable and can result in patient harm and increased expenses in the healthcare system in terms of hospitalization, prolonged hospitalizations and even death. We aimed to develop a screening tool to detect acutely admitted patients at low or high risk of MEs...

  20. Bayesian network models for error detection in radiotherapy plans

    International Nuclear Information System (INIS)

    Kalet, Alan M; Ford, Eric C; Phillips, Mark H; Gennari, John H

    2015-01-01

    The purpose of this study is to design and develop a probabilistic network for detecting errors in radiotherapy plans for use at the time of initial plan verification. Our group has initiated a multi-pronged approach to reduce these errors. We report on our development of Bayesian models of radiotherapy plans. Bayesian networks consist of joint probability distributions that define the probability of one event, given some set of other known information. Using the networks, we find the probability of obtaining certain radiotherapy parameters, given a set of initial clinical information. A low probability in a propagated network then corresponds to potential errors to be flagged for investigation. To build our networks we first interviewed medical physicists and other domain experts to identify the relevant radiotherapy concepts and their associated interdependencies and to construct a network topology. Next, to populate the network’s conditional probability tables, we used the Hugin Expert software to learn parameter distributions from a subset of de-identified data derived from a radiation oncology based clinical information database system. These data represent 4990 unique prescription cases over a 5 year period. Under test case scenarios with approximately 1.5% introduced error rates, network performance produced areas under the ROC curve of 0.88, 0.98, and 0.89 for the lung, brain and female breast cancer error detection networks, respectively. Comparison of the brain network to human experts performance (AUC of 0.90 ± 0.01) shows the Bayes network model performs better than domain experts under the same test conditions. Our results demonstrate the feasibility and effectiveness of comprehensive probabilistic models as part of decision support systems for improved detection of errors in initial radiotherapy plan verification procedures. (paper)

  1. ERROR DETECTION BY ANTICIPATION FOR VISION-BASED CONTROL

    Directory of Open Access Journals (Sweden)

    A ZAATRI

    2001-06-01

    Full Text Available A vision-based control system has been developed.  It enables a human operator to remotely direct a robot, equipped with a camera, towards targets in 3D space by simply pointing on their images with a pointing device. This paper presents an anticipatory system, which has been designed for improving the safety and the effectiveness of the vision-based commands. It simulates these commands in a virtual environment. It attempts to detect hard contacts that may occur between the robot and its environment, which can be caused by machine errors or operator errors as well.

  2. Comparison of computer workstation with film for detecting setup errors

    International Nuclear Information System (INIS)

    Fritsch, D.S.; Boxwala, A.A.; Raghavan, S.; Coffee, C.; Major, S.A.; Muller, K.E.; Chaney, E.L.

    1997-01-01

    Purpose/Objective: Workstations designed for portal image interpretation by radiation oncologists provide image displays and image processing and analysis tools that differ significantly compared with the standard clinical practice of inspecting portal films on a light box. An implied but unproved assumption associated with the clinical implementation of workstation technology is that patient care is improved, or at least not adversely affected. The purpose of this investigation was to conduct observer studies to test the hypothesis that radiation oncologists can detect setup errors using a workstation at least as accurately as when following standard clinical practice. Materials and Methods: A workstation, PortFolio, was designed for radiation oncologists to display and inspect digital portal images for setup errors. PortFolio includes tools to enhance images; align cross-hairs, field edges, and anatomic structures on reference and acquired images; measure distances and angles; and view registered images superimposed on one another. In a well designed and carefully controlled observer study, nine radiation oncologists, including attendings and residents, used PortFolio to detect setup errors in realistic digitally reconstructed portal (DRPR) images computed from the NLM visible human data using a previously described approach † . Compared with actual portal images where absolute truth is ill defined or unknown, the DRPRs contained known translation or rotation errors in the placement of the fields over target regions in the pelvis and head. Twenty DRPRs with randomly induced errors were computed for each site. The induced errors were constrained to a plane at the isocenter of the target volume and perpendicular to the central axis of the treatment beam. Images used in the study were also printed on film. Observers interpreted the film-based images using standard clinical practice. The images were reviewed in eight sessions. During each session five images were

  3. A methodology of error detection: Improving speech recognition in radiology

    OpenAIRE

    Voll, Kimberly Dawn

    2006-01-01

    Automated speech recognition (ASR) in radiology report dictation demands highly accurate and robust recognition software. Despite vendor claims, current implementations are suboptimal, leading to poor accuracy, and time and money wasted on proofreading. Thus, other methods must be considered for increasing the reliability and performance of ASR before it is a viable alternative to human transcription. One such method is post-ASR error detection, used to recover from the inaccuracy of speech r...

  4. Recursive prediction error methods for online estimation in nonlinear state-space models

    Directory of Open Access Journals (Sweden)

    Dag Ljungquist

    1994-04-01

    Full Text Available Several recursive algorithms for online, combined state and parameter estimation in nonlinear state-space models are discussed in this paper. Well-known algorithms such as the extended Kalman filter and alternative formulations of the recursive prediction error method are included, as well as a new method based on a line-search strategy. A comparison of the algorithms illustrates that they are very similar although the differences can be important for the online tracking capabilities and robustness. Simulation experiments on a simple nonlinear process show that the performance under certain conditions can be improved by including a line-search strategy.

  5. Prospective detection of large prediction errors: a hypothesis testing approach

    International Nuclear Information System (INIS)

    Ruan, Dan

    2010-01-01

    Real-time motion management is important in radiotherapy. In addition to effective monitoring schemes, prediction is required to compensate for system latency, so that treatment can be synchronized with tumor motion. However, it is difficult to predict tumor motion at all times, and it is critical to determine when large prediction errors may occur. Such information can be used to pause the treatment beam or adjust monitoring/prediction schemes. In this study, we propose a hypothesis testing approach for detecting instants corresponding to potentially large prediction errors in real time. We treat the future tumor location as a random variable, and obtain its empirical probability distribution with the kernel density estimation-based method. Under the null hypothesis, the model probability is assumed to be a concentrated Gaussian centered at the prediction output. Under the alternative hypothesis, the model distribution is assumed to be non-informative uniform, which reflects the situation that the future position cannot be inferred reliably. We derive the likelihood ratio test (LRT) for this hypothesis testing problem and show that with the method of moments for estimating the null hypothesis Gaussian parameters, the LRT reduces to a simple test on the empirical variance of the predictive random variable. This conforms to the intuition to expect a (potentially) large prediction error when the estimate is associated with high uncertainty, and to expect an accurate prediction when the uncertainty level is low. We tested the proposed method on patient-derived respiratory traces. The 'ground-truth' prediction error was evaluated by comparing the prediction values with retrospective observations, and the large prediction regions were subsequently delineated by thresholding the prediction errors. The receiver operating characteristic curve was used to describe the performance of the proposed hypothesis testing method. Clinical implication was represented by miss

  6. Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity

    Directory of Open Access Journals (Sweden)

    Martin eSpüler

    2015-03-01

    Full Text Available When a person recognizes an error during a task, an error-related potential (ErrP can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback.With this study, we wanted to answer three different questions: (i Can ErrPs be measured in electroencephalography (EEG recordings during a task with continuous cursor control? (ii Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action. We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible.Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG.

  7. Error-related potentials during continuous feedback: using EEG to detect errors of different type and severity

    Science.gov (United States)

    Spüler, Martin; Niethammer, Christian

    2015-01-01

    When a person recognizes an error during a task, an error-related potential (ErrP) can be measured as response. It has been shown that ErrPs can be automatically detected in tasks with time-discrete feedback, which is widely applied in the field of Brain-Computer Interfaces (BCIs) for error correction or adaptation. However, there are only a few studies that concentrate on ErrPs during continuous feedback. With this study, we wanted to answer three different questions: (i) Can ErrPs be measured in electroencephalography (EEG) recordings during a task with continuous cursor control? (ii) Can ErrPs be classified using machine learning methods and is it possible to discriminate errors of different origins? (iii) Can we use EEG to detect the severity of an error? To answer these questions, we recorded EEG data from 10 subjects during a video game task and investigated two different types of error (execution error, due to inaccurate feedback; outcome error, due to not achieving the goal of an action). We analyzed the recorded data to show that during the same task, different kinds of error produce different ErrP waveforms and have a different spectral response. This allows us to detect and discriminate errors of different origin in an event-locked manner. By utilizing the error-related spectral response, we show that also a continuous, asynchronous detection of errors is possible. Although the detection of error severity based on EEG was one goal of this study, we did not find any significant influence of the severity on the EEG. PMID:25859204

  8. Runtime Detection of C-Style Errors in UPC Code

    Energy Technology Data Exchange (ETDEWEB)

    Pirkelbauer, P; Liao, C; Panas, T; Quinlan, D

    2011-09-29

    Unified Parallel C (UPC) extends the C programming language (ISO C 99) with explicit parallel programming support for the partitioned global address space (PGAS), which provides a global memory space with localized partitions to each thread. Like its ancestor C, UPC is a low-level language that emphasizes code efficiency over safety. The absence of dynamic (and static) safety checks allows programmer oversights and software flaws that can be hard to spot. In this paper, we present an extension of a dynamic analysis tool, ROSE-Code Instrumentation and Runtime Monitor (ROSECIRM), for UPC to help programmers find C-style errors involving the global address space. Built on top of the ROSE source-to-source compiler infrastructure, the tool instruments source files with code that monitors operations and keeps track of changes to the system state. The resulting code is linked to a runtime monitor that observes the program execution and finds software defects. We describe the extensions to ROSE-CIRM that were necessary to support UPC. We discuss complications that arise from parallel code and our solutions. We test ROSE-CIRM against a runtime error detection test suite, and present performance results obtained from running error-free codes. ROSE-CIRM is released as part of the ROSE compiler under a BSD-style open source license.

  9. Decoding of DBEC-TBED Reed-Solomon codes. [Double-Byte-Error-Correcting, Triple-Byte-Error-Detecting

    Science.gov (United States)

    Deng, Robert H.; Costello, Daniel J., Jr.

    1987-01-01

    A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256 K bit DRAM's are organized in 32 K x 8 bit-bytes. Byte-oriented codes such as Reed-Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. The paper presents a special decoding technique for double-byte-error-correcting, triple-byte-error-detecting RS codes which is capable of high-speed operation. This technique is designed to find the error locations and the error values directly from the syndrome without having to use the iterative algorithm to find the error locator polynomial.

  10. Vision based error detection for 3D printing processes

    Directory of Open Access Journals (Sweden)

    Baumann Felix

    2016-01-01

    Full Text Available 3D printers became more popular in the last decade, partly because of the expiration of key patents and the supply of affordable machines. The origin is located in rapid prototyping. With Additive Manufacturing (AM it is possible to create physical objects from 3D model data by layer wise addition of material. Besides professional use for prototyping and low volume manufacturing they are becoming widespread amongst end users starting with the so called Maker Movement. The most prevalent type of consumer grade 3D printers is Fused Deposition Modelling (FDM, also Fused Filament Fabrication FFF. This work focuses on FDM machinery because of their widespread occurrence and large number of open problems like precision and failure. These 3D printers can fail to print objects at a statistical rate depending on the manufacturer and model of the printer. Failures can occur due to misalignment of the print-bed, the print-head, slippage of the motors, warping of the printed material, lack of adhesion or other reasons. The goal of this research is to provide an environment in which these failures can be detected automatically. Direct supervision is inhibited by the recommended placement of FDM printers in separate rooms away from the user due to ventilation issues. The inability to oversee the printing process leads to late or omitted detection of failures. Rejects effect material waste and wasted time thus lowering the utilization of printing resources. Our approach consists of a camera based error detection mechanism that provides a web based interface for remote supervision and early failure detection. Early failure detection can lead to reduced time spent on broken prints, less material wasted and in some cases salvaged objects.

  11. Enhancing Syndromic Surveillance With Online Respondent-Driven Detection

    NARCIS (Netherlands)

    Stein, Mart L; van Steenbergen, Jim E; Buskens, Vincent; van der Heijden, Peter G M; Koppeschaar, Carl E; Bengtsson, Linus; Thorson, Anna; Kretzschmar, MEE

    OBJECTIVES: We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants. METHODS: In 2014, volunteers from 2

  12. Enhancing syndromic surveillance with online respondent-driven detection

    NARCIS (Netherlands)

    Stein, Mart L.; Van Steenbergen, Jim E.; Buskens, Vincent; Van Der Heijden, Peter G M; Koppeschaar, Carl E.; Bengtsson, Linus; Thorson, Anna; Kretzschmar, Mirjam E E

    2015-01-01

    Objectives. We investigated the feasibility of combining an online chain recruitment method (respondent-driven detection) and participatory surveillance panels to collect previously undetected information on infectious diseases via social networks of participants. Methods. In 2014, volunteers from 2

  13. Adaptive control of nonlinear system using online error minimum neural networks.

    Science.gov (United States)

    Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

    2016-11-01

    In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Online Detection of Abnormal Events in Video Streams

    Directory of Open Access Journals (Sweden)

    Tian Wang

    2013-01-01

    an image descriptor and online nonlinear classification method. We introduce the covariance matrix of the optical flow and image intensity as a descriptor encoding moving information. The nonlinear online support vector machine (SVM firstly learns a limited set of the training frames to provide a basic reference model then updates the model and detects abnormal events in the current frame. We finally apply the method to detect abnormal events on a benchmark video surveillance dataset to demonstrate the effectiveness of the proposed technique.

  15. An online detection system for aggregate sizes and shapes based on digital image processing

    Science.gov (United States)

    Yang, Jianhong; Chen, Sijia

    2017-02-01

    Traditional aggregate size measuring methods are time-consuming, taxing, and do not deliver online measurements. A new online detection system for determining aggregate size and shape based on a digital camera with a charge-coupled device, and subsequent digital image processing, have been developed to overcome these problems. The system captures images of aggregates while falling and flat lying. Using these data, the particle size and shape distribution can be obtained in real time. Here, we calibrate this method using standard globules. Our experiments show that the maximum particle size distribution error was only 3 wt%, while the maximum particle shape distribution error was only 2 wt% for data derived from falling aggregates, having good dispersion. In contrast, the data for flat-lying aggregates had a maximum particle size distribution error of 12 wt%, and a maximum particle shape distribution error of 10 wt%; their accuracy was clearly lower than for falling aggregates. However, they performed well for single-graded aggregates, and did not require a dispersion device. Our system is low-cost and easy to install. It can successfully achieve online detection of aggregate size and shape with good reliability, and it has great potential for aggregate quality assurance.

  16. Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.

    Science.gov (United States)

    Spüler, Martin; Rosenstiel, Wolfgang; Bogdan, Martin

    2012-01-01

    The goal of a Brain-Computer Interface (BCI) is to control a computer by pure brain activity. Recently, BCIs based on code-modulated visual evoked potentials (c-VEPs) have shown great potential to establish high-performance communication. In this paper we present a c-VEP BCI that uses online adaptation of the classifier to reduce calibration time and increase performance. We compare two different approaches for online adaptation of the system: an unsupervised method and a method that uses the detection of error-related potentials. Both approaches were tested in an online study, in which an average accuracy of 96% was achieved with adaptation based on error-related potentials. This accuracy corresponds to an average information transfer rate of 144 bit/min, which is the highest bitrate reported so far for a non-invasive BCI. In a free-spelling mode, the subjects were able to write with an average of 21.3 error-free letters per minute, which shows the feasibility of the BCI system in a normal-use scenario. In addition we show that a calibration of the BCI system solely based on the detection of error-related potentials is possible, without knowing the true class labels.

  17. A Sequential Analysis of Responses in Online Debates to Postings of Students Exhibiting High Versus Low Grammar and Spelling Errors

    Science.gov (United States)

    Jeong, Allan; Li, Haiying; Pan, Andy Jiaren

    2017-01-01

    Given that grammatical and spelling errors have been found to influence perceived competence and credibility in written communication, this study examined how a student's grammar and spelling errors affect how other students respond to the student's postings in four online debates hosted in asynchronous threaded discussions. Message-response…

  18. Competitive action video game players display rightward error bias during on-line video game play.

    Science.gov (United States)

    Roebuck, Andrew J; Dubnyk, Aurora J B; Cochran, David; Mandryk, Regan L; Howland, John G; Harms, Victoria

    2017-09-12

    Research in asymmetrical visuospatial attention has identified a leftward bias in the general population across a variety of measures including visual attention and line-bisection tasks. In addition, increases in rightward collisions, or bumping, during visuospatial navigation tasks have been demonstrated in real world and virtual environments. However, little research has investigated these biases beyond the laboratory. The present study uses a semi-naturalistic approach and the online video game streaming service Twitch to examine navigational errors and assaults as skilled action video game players (n = 60) compete in Counter Strike: Global Offensive. This study showed a significant rightward bias in both fatal assaults and navigational errors. Analysis using the in-game ranking system as a measure of skill failed to show a relationship between bias and skill. These results suggest that a leftward visuospatial bias may exist in skilled players during online video game play. However, the present study was unable to account for some factors such as environmental symmetry and player handedness. In conclusion, video game streaming is a promising method for behavioural research in the future, however further study is required before one can determine whether these results are an artefact of the method applied, or representative of a genuine rightward bias.

  19. Medication errors detected in non-traditional databases

    DEFF Research Database (Denmark)

    Perregaard, Helene; Aronson, Jeffrey K; Dalhoff, Kim

    2015-01-01

    AIMS: We have looked for medication errors involving the use of low-dose methotrexate, by extracting information from Danish sources other than traditional pharmacovigilance databases. We used the data to establish the relative frequencies of different types of errors. METHODS: We searched four...... errors, whereas knowledge-based errors more often resulted in near misses. CONCLUSIONS: The medication errors in this survey were most often action-based (50%) and knowledge-based (34%), suggesting that greater attention should be paid to education and surveillance of medical personnel who prescribe...

  20. Detecting Friendship Within Dynamic Online Interaction Networks

    OpenAIRE

    Merritt, Sears; Jacobs, Abigail Z.; Mason, Winter; Clauset, Aaron

    2013-01-01

    In many complex social systems, the timing and frequency of interactions between individuals are observable but friendship ties are hidden. Recovering these hidden ties, particularly for casual users who are relatively less active, would enable a wide variety of friendship-aware applications in domains where labeled data are often unavailable, including online advertising and national security. Here, we investigate the accuracy of multiple statistical features, based either purely on temporal...

  1. An On-Line Method for Thermal Diffusivity Detection of Thin Films Using Infrared Video

    Directory of Open Access Journals (Sweden)

    Dong Huilong

    2016-03-01

    Full Text Available A novel method for thermal diffusivity evolution of thin-film materials with pulsed Gaussian beam and infrared video is reported. Compared with common pulse methods performed in specialized labs, the proposed method implements a rapid on-line measurement without producing the off-centre detection error. Through mathematical deduction of the original heat conduction model, it is discovered that the area s, which is encircled by the maximum temperature curve rTMAX(θ, increases linearly over elapsed time. The thermal diffusivity is acquired from the growth rate of the area s. In this study, the off-centre detection error is avoided by performing the distance regularized level set evolution formulation. The area s was extracted from the binary images of temperature variation rate, without inducing errors from determination of the heat source centre. Thermal diffusivities of three materials, 304 stainless steel, titanium, and zirconium have been measured with the established on-line detection system, and the measurement errors are: −2.26%, −1.07%, and 1.61% respectively.

  2. Neutron detection using soft errors in dynamic random access memories

    International Nuclear Information System (INIS)

    Darambara, D.G.; Spyrou, N.M.

    1992-01-01

    The fact that energetic alpha particles have been observed to be capable of inducing single-event upsets in integrated circuit memories has become a topic of considerable interest in the past few years. One recognized difficulty with dynamic random access memory devices (dRAMs) is that the alpha-particle 'contamination' present within the dRAM encapsulating material interact sufficiently as to corrupt stored data. The authors essentially utilized the fact that these corruptions may be induced in dRAMs by the interaction of charged particles with the chip of the dRAM itself as a basis of a hardware system for neutron detection with a view to applications in neutron imaging and elemental analysis. The design incorporates a bank of dRAMs on which the particles are incident. Initially, these particles were alpha particles from an appropriate alpha-emitting source employed to assess system parameters. The sensitivity of the device to logic state upsets by ionizing radiation is a function of design and technology parameters, inducing storage node area, node capacitance, operating voltage, minority carrier lifetime, electric fields pattern in the bulk silicon, and specific device geometry. The soft error rate of the device in a given package depends on the flux of alphas, the energy spectrum, the distribution of incident angles, the target area, the total stored charge, the collection efficiency, the cell geometry, the supply voltage, the cycle and refreshing time, and the noise margin

  3. Non-Linguistic Vocal Event Detection Using Online Random

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

    2014-01-01

    areas such as object detection, face recognition, and audio event detection. This paper proposes to use online random forest technique for detecting laughter and filler and for analyzing the importance of various features for non-linguistic vocal event classification through permutation. The results...... show that according to the Area Under Curve measure the online random forest achieved 88.1% compared to 82.9% obtained by the baseline support vector machines for laughter classification and 86.8% to 83.6% for filler classification....

  4. The timing of spontaneous detection and repair of naming errors in aphasia.

    Science.gov (United States)

    Schuchard, Julia; Middleton, Erica L; Schwartz, Myrna F

    2017-08-01

    This study examined the timing of spontaneous self-monitoring in the naming responses of people with aphasia. Twelve people with aphasia completed a 615-item naming test twice, in separate sessions. Naming attempts were scored for accuracy and error type, and verbalizations indicating detection were coded as negation (e.g., "no, not that") or repair attempts (i.e., a changed naming attempt). Focusing on phonological and semantic errors, we measured the timing of the errors and of the utterances that provided evidence of detection. The effects of error type and detection response type on error-to-detection latencies were analyzed using mixed-effects regression modeling. We first asked whether phonological errors and semantic errors differed in the timing of the detection process or repair planning. Results suggested that the two error types primarily differed with respect to repair planning. Specifically, repair attempts for phonological errors were initiated more quickly than repair attempts for semantic errors. We next asked whether this difference between the error types could be attributed to the tendency for phonological errors to have a high degree of phonological similarity with the subsequent repair attempts, thereby speeding the programming of the repairs. Results showed that greater phonological similarity between the error and the repair was associated with faster repair times for both error types, providing evidence of error-to-repair priming in spontaneous self-monitoring. When controlling for phonological overlap, significant effects of error type and repair accuracy on repair times were also found. These effects indicated that correct repairs of phonological errors were initiated particularly quickly, whereas repairs of semantic errors were initiated relatively slowly, regardless of their accuracy. We discuss the implications of these findings for theoretical accounts of self-monitoring and the role of speech error repair in learning. Copyright

  5. A Novel Multiple-Bits Collision Attack Based on Double Detection with Error-Tolerant Mechanism

    Directory of Open Access Journals (Sweden)

    Ye Yuan

    2018-01-01

    Full Text Available Side-channel collision attacks are more powerful than traditional side-channel attack without knowing the leakage model or establishing the model. Most attack strategies proposed previously need quantities of power traces with high computational complexity and are sensitive to mistakes, which restricts the attack efficiency seriously. In this paper, we propose a multiple-bits side-channel collision attack based on double distance voting detection (DDVD and also an improved version, involving the error-tolerant mechanism, which can find all 120 relations among 16 key bytes when applied to AES (Advanced Encryption Standard algorithm. In addition, we compare our collision detection method called DDVD with the Euclidean distance and the correlation-enhanced collision method under different intensity of noise, which indicates that our detection technique performs better in the circumstances of noise. Furthermore, 4-bit model of our collision detection method is proven to be optimal in theory and in practice. Meanwhile the corresponding practical attack experiments are also performed on a hardware implementation of AES-128 on FPGA board successfully. Results show that our strategy needs less computation time but more traces than LDPC method and the online time for our strategy is about 90% less than CECA and 96% less than BCA with 90% success rate.

  6. Detection of illicit online sales of fentanyls via Twitter.

    Science.gov (United States)

    Mackey, Tim K; Kalyanam, Janani

    2017-01-01

    A counterfeit fentanyl crisis is currently underway in the United States.  Counterfeit versions of commonly abused prescription drugs laced with fentanyl are being manufactured, distributed, and sold globally, leading to an increase in overdose and death in countries like the United States and Canada.  Despite concerns from the U.S. Drug Enforcement Agency regarding covert and overt sale of fentanyls online, no study has examined the role of the Internet and social media on fentanyl illegal marketing and direct-to-consumer access.  In response, this study collected and analyzed five months of Twitter data (from June-November 2015) filtered for the keyword "fentanyl" using Amazon Web Services.  We then analyzed 28,711 fentanyl-related tweets using text filtering and a machine learning approach called a Biterm Topic Model (BTM) to detect underlying latent patterns or "topics" present in the corpus of tweets.  Using this approach we detected a subset of 771 tweets marketing the sale of fentanyls online and then filtered this down to nine unique tweets containing hyperlinks to external websites.  Six hyperlinks were associated with online fentanyl classified ads, 2 with illicit online pharmacies, and 1 could not be classified due to traffic redirection.  Importantly, the one illicit online pharmacy detected was still accessible and offered the sale of fentanyls and other controlled substances direct-to-consumers with no prescription required at the time of publication of this study.   Overall, we detected a relatively small sample of Tweets promoting illegal online sale of fentanyls.  However, the detection of even a few online sellers represents a public health danger and a direct violation of law that demands further study.

  7. Glaucoma detection with damato multifixation campimetry online

    DEFF Research Database (Denmark)

    Olsen, Ane Sophie; Alberti, M.; Serup, L.

    2016-01-01

    to define abnormality, and these were evaluated using the Glaucoma Staging System as gold standard. Receiver operating characteristic (ROC) curves and area under the ROC (AUC) were calculated. Results AUCs from 15 algorithms ranged from 0.79 to 0.90. The most promising algorithm combined results from two...... successive DMCO STANDARD tests. The sensitivity was highly dependent on the severity of glaucoma. Hence, for eyes with mild, moderate, advanced, and severe glaucoma, the DMCO test demonstrated a sensitivity of 11.8, 71.4, 100, and 100%, respectively. The specificity was as high as 98.1%. Median duration per...... eye to complete the DMCO STANDARD test was 86 s for the control group and 125 s in participants with glaucoma. Conclusions DMCO shows promise as a free-of-charge online tool to identify glaucomatous visual field defects in a preselected population. Ongoing studies are evaluating the use of DMCO...

  8. On-line intermittent connector anomaly detection

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper investigates a non-traditional use of differential current sensor and current sensor to detect intermittent disconnection problems in connectors. An...

  9. On-line bacteriological detection in water

    OpenAIRE

    Lopez Roldan, Ramon; Tusell, Pol; Courtois, Sophie; Cortina Pallás, José Luís

    2013-01-01

    Microorganism contamination is a permanent concern in a wide range of fields, including the water-treatment, food and pharmaceutical industries, in which fast detection is critical to prevent microbial outbreaks. In water monitoring, current procedures for water-quality analysis are based on periodic sampling and detection by culture methods, which are slow, requiring 24–48 h for completion, so that, when first results reach the decision-takers and trigger an alarm, significant time has a...

  10. Detecting self-produced speech errors before and after articulation: An ERP investigation

    Directory of Open Access Journals (Sweden)

    Kevin Michael Trewartha

    2013-11-01

    Full Text Available It has been argued that speech production errors are monitored by the same neural system involved in monitoring other types of action errors. Behavioral evidence has shown that speech errors can be detected and corrected prior to articulation, yet the neural basis for such pre-articulatory speech error monitoring is poorly understood. The current study investigated speech error monitoring using a phoneme-substitution task known to elicit speech errors. Stimulus-locked event-related potential (ERP analyses comparing correct and incorrect utterances were used to assess pre-articulatory error monitoring and response-locked ERP analyses were used to assess post-articulatory monitoring. Our novel finding in the stimulus-locked analysis revealed that words that ultimately led to a speech error were associated with a larger P2 component at midline sites (FCz, Cz, and CPz. This early positivity may reflect the detection of an error in speech formulation, or a predictive mechanism to signal the potential for an upcoming speech error. The data also revealed that general conflict monitoring mechanisms are involved during this task as both correct and incorrect responses elicited an anterior N2 component typically associated with conflict monitoring. The response-locked analyses corroborated previous observations that self-produced speech errors led to a fronto-central ERN. These results demonstrate that speech errors can be detected prior to articulation, and that speech error monitoring relies on a central error monitoring mechanism.

  11. Methods of Run-Time Error Detection in Distributed Process Control Software

    DEFF Research Database (Denmark)

    Drejer, N.

    of generic run-time error types, design of methods of observing application software behaviorduring execution and design of methods of evaluating run time constraints. In the definition of error types it is attempted to cover all relevant aspects of the application softwaree behavior. Methods of observation......In this thesis, methods of run-time error detection in application software for distributed process control is designed. The error detection is based upon a monitoring approach in which application software is monitored by system software during the entire execution. The thesis includes definition...... and constraint evaluation is designed for the modt interesting error types. These include: a) semantical errors in data communicated between application tasks; b) errors in the execution of application tasks; and c) errors in the timing of distributed events emitted by the application software. The design...

  12. Methods of Run-Time Error Detection in Distributed Process Control Software

    DEFF Research Database (Denmark)

    Drejer, N.

    In this thesis, methods of run-time error detection in application software for distributed process control is designed. The error detection is based upon a monitoring approach in which application software is monitored by system software during the entire execution. The thesis includes definition...... and constraint evaluation is designed for the modt interesting error types. These include: a) semantical errors in data communicated between application tasks; b) errors in the execution of application tasks; and c) errors in the timing of distributed events emitted by the application software. The design...... of error detection methods includes a high level software specification. this has the purpose of illustrating that the designed can be used in practice....

  13. Detecting errors in micro and trace analysis by using statistics

    DEFF Research Database (Denmark)

    Heydorn, K.

    1993-01-01

    By assigning a standard deviation to each step in an analytical method it is possible to predict the standard deviation of each analytical result obtained by this method. If the actual variability of replicate analytical results agrees with the expected, the analytical method is said...... to be in statistical control. Significant deviations between analytical results from different laboratories reveal the presence of systematic errors, and agreement between different laboratories indicate the absence of systematic errors. This statistical approach, referred to as the analysis of precision, was applied...

  14. Real-time detection and elimination of nonorthogonality error in interference fringe processing

    International Nuclear Information System (INIS)

    Hu Haijiang; Zhang Fengdeng

    2011-01-01

    In the measurement system of interference fringe, the nonorthogonality error is a main error source that influences the precision and accuracy of the measurement system. The detection and elimination of the error has been an important target. A novel method that only uses the cross-zero detection and the counting is proposed to detect and eliminate the nonorthogonality error in real time. This method can be simply realized by means of the digital logic device, because it does not invoke trigonometric functions and inverse trigonometric functions. And it can be widely used in the bidirectional subdivision systems of a Moire fringe and other optical instruments.

  15. Error detection in spoken human-machine interaction

    NARCIS (Netherlands)

    Krahmer, E.J.; Swerts, M.G.J.; Theune, M.; Weegels, M.F.

    2001-01-01

    Given the state of the art of current language and speech technology, errors are unavoidable in present-day spoken dialogue systems. Therefore, one of the main concerns in dialogue design is how to decide whether or not the system has understood the user correctly. In human-human communication,

  16. Error detection in spoken human-machine interaction

    NARCIS (Netherlands)

    Krahmer, E.; Swerts, M.; Theune, Mariet; Weegels, M.

    Given the state of the art of current language and speech technology, errors are unavoidable in present-day spoken dialogue systems. Therefore, one of the main concerns in dialogue design is how to decide whether or not the system has understood the user correctly. In human-human communication,

  17. Music Abilities and Experiences as Predictors of Error-Detection Skill.

    Science.gov (United States)

    Brand, Manny; Burnsed, Vernon

    1981-01-01

    This study examined the predictive validity of previous music abilities and experiences of skill in music error detection among undergraduate instrumental music education majors. Results indicated no statistically significant relationships which suggest that the ability to detect music errors may exist independently of other music abilities.…

  18. Methods of Profile Cloning Detection in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Zabielski Michał

    2016-01-01

    Full Text Available With the arrival of online social networks, the importance of privacy on the Internet has increased dramatically. Thus, it is important to develop mechanisms that will prevent our hidden personal data from unauthorized access and use. In this paper an attempt was made to present a concept of profile cloning detection in Online Social Networks (OSN using Graph and Networks Theory. By analysing structural similarity of network and value of attributes of user personal profile, we will be able to search for attackers which steal our identity.

  19. Robust online tracking via adaptive samples selection with saliency detection

    Science.gov (United States)

    Yan, Jia; Chen, Xi; Zhu, QiuPing

    2013-12-01

    Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

  20. Errors detected in pediatric oral liquid medication doses prepared in an automated workflow management system.

    Science.gov (United States)

    Bledsoe, Sarah; Van Buskirk, Alex; Falconer, R James; Hollon, Andrew; Hoebing, Wendy; Jokic, Sladan

    2018-02-01

    The effectiveness of barcode-assisted medication preparation (BCMP) technology on detecting oral liquid dose preparation errors. From June 1, 2013, through May 31, 2014, a total of 178,344 oral doses were processed at Children's Mercy, a 301-bed pediatric hospital, through an automated workflow management system. Doses containing errors detected by the system's barcode scanning system or classified as rejected by the pharmacist were further reviewed. Errors intercepted by the barcode-scanning system were classified as (1) expired product, (2) incorrect drug, (3) incorrect concentration, and (4) technological error. Pharmacist-rejected doses were categorized into 6 categories based on the root cause of the preparation error: (1) expired product, (2) incorrect concentration, (3) incorrect drug, (4) incorrect volume, (5) preparation error, and (6) other. Of the 178,344 doses examined, 3,812 (2.1%) errors were detected by either the barcode-assisted scanning system (1.8%, n = 3,291) or a pharmacist (0.3%, n = 521). The 3,291 errors prevented by the barcode-assisted system were classified most commonly as technological error and incorrect drug, followed by incorrect concentration and expired product. Errors detected by pharmacists were also analyzed. These 521 errors were most often classified as incorrect volume, preparation error, expired product, other, incorrect drug, and incorrect concentration. BCMP technology detected errors in 1.8% of pediatric oral liquid medication doses prepared in an automated workflow management system, with errors being most commonly attributed to technological problems or incorrect drugs. Pharmacists rejected an additional 0.3% of studied doses. Copyright © 2018 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

  1. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

    Directory of Open Access Journals (Sweden)

    Hesham Mostafa

    2017-09-01

    Full Text Available Artificial neural networks (ANNs trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

  2. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

    Science.gov (United States)

    Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

    2017-01-01

    Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

  3. Sequential Change-Point Detection via Online Convex Optimization

    Directory of Open Access Journals (Sweden)

    Yang Cao

    2018-02-01

    Full Text Available Sequential change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. When the post-change parameters are unknown, we consider a set of detection procedures based on sequential likelihood ratios with non-anticipating estimators constructed using online convex optimization algorithms such as online mirror descent, which provides a more versatile approach to tackling complex situations where recursive maximum likelihood estimators cannot be found. When the underlying distributions belong to a exponential family and the estimators satisfy the logarithm regret property, we show that this approach is nearly second-order asymptotically optimal. This means that the upper bound for the false alarm rate of the algorithm (measured by the average-run-length meets the lower bound asymptotically up to a log-log factor when the threshold tends to infinity. Our proof is achieved by making a connection between sequential change-point and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.

  4. Neutron detection using soft errors in dynamic Random Access Memories

    International Nuclear Information System (INIS)

    Darambara, D.G.; Spyrou, N.M.

    1994-01-01

    The purpose of this paper is to present results from experiments that have been performed to show the memory cycle time dependence of the soft errors produced by the interaction of alpha particles with dynamic random access memory devices, with a view to using these as position sensitive detectors. Furthermore, a preliminary feasibility study being carried out indicates the use of dynamic RAMs as neutron detectors by the utilization of (n, α) capture reactions in a Li converter placed on the top of the active area of the memory chip. ((orig.))

  5. Incorporating profile information in community detection for online social networks

    Science.gov (United States)

    Fan, W.; Yeung, K. H.

    2014-07-01

    Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.

  6. Prevention of prescription errors by computerized, on-line, individual patient related surveillance of drug order entry.

    Science.gov (United States)

    Oliven, A; Zalman, D; Shilankov, Y; Yeshurun, D; Odeh, M

    2002-01-01

    Computerized prescription of drugs is expected to reduce the number of many preventable drug ordering errors. In the present study we evaluated the usefullness of a computerized drug order entry (CDOE) system in reducing prescription errors. A department of internal medicine using a comprehensive CDOE, which included also patient-related drug-laboratory, drug-disease and drug-allergy on-line surveillance was compared to a similar department in which drug orders were handwritten. CDOE reduced prescription errors to 25-35%. The causes of errors remained similar, and most errors, on both departments, were associated with abnormal renal function and electrolyte balance. Residual errors remaining on the CDOE-using department were due to handwriting on the typed order, failure to feed patients' diseases, and system failures. The use of CDOE was associated with a significant reduction in mean hospital stay and in the number of changes performed in the prescription. The findings of this study both quantity the impact of comprehensive CDOE on prescription errors and delineate the causes for remaining errors.

  7. Investigating the error sources of the online state of charge estimation methods for lithium-ion batteries in electric vehicles

    Science.gov (United States)

    Zheng, Yuejiu; Ouyang, Minggao; Han, Xuebing; Lu, Languang; Li, Jianqiu

    2018-02-01

    Sate of charge (SOC) estimation is generally acknowledged as one of the most important functions in battery management system for lithium-ion batteries in new energy vehicles. Though every effort is made for various online SOC estimation methods to reliably increase the estimation accuracy as much as possible within the limited on-chip resources, little literature discusses the error sources for those SOC estimation methods. This paper firstly reviews the commonly studied SOC estimation methods from a conventional classification. A novel perspective focusing on the error analysis of the SOC estimation methods is proposed. SOC estimation methods are analyzed from the views of the measured values, models, algorithms and state parameters. Subsequently, the error flow charts are proposed to analyze the error sources from the signal measurement to the models and algorithms for the widely used online SOC estimation methods in new energy vehicles. Finally, with the consideration of the working conditions, choosing more reliable and applicable SOC estimation methods is discussed, and the future development of the promising online SOC estimation methods is suggested.

  8. Assessment of residual error for online cone-beam CT-guided treatment of prostate cancer patients

    International Nuclear Information System (INIS)

    Letourneau, Daniel; Martinez, Alvaro A.; Lockman, David; Yan Di; Vargas, Carlos; Ivaldi, Giovanni; Wong, John

    2005-01-01

    Purpose: Kilovoltage cone-beam CT (CBCT) implemented on board a medical accelerator is available for image-guidance applications in our clinic. The objective of this work was to assess the magnitude and stability of the residual setup error associated with CBCT online-guided prostate cancer patient setup. Residual error pertains to the uncertainty in image registration, the limited mechanical accuracy, and the intrafraction motion during imaging and treatment. Methods and Materials: The residual error for CBCT online-guided correction was first determined in a phantom study. After online correction, the phantom residual error was determined by comparing megavoltage portal images acquired every 90 deg. to the corresponding digitally reconstructed radiographs. In the clinical study, 8 prostate cancer patients were implanted with three radiopaque markers made of high-winding coils. After positioning the patient using the skin marks, a CBCT scan was acquired and the setup error determined by fusing the coils on the CBCT and planning CT scans. The patient setup was then corrected by moving the couch accordingly. A second CBCT scan was acquired immediately after the correction to evaluate the residual target setup error. Intrafraction motion was evaluated by tracking the coils and the bony landmarks on kilovoltage radiographs acquired every 30 s between the two CBCT scans. Corrections based on soft-tissue registration were evaluated offline by aligning the prostate contours defined on both planning CT and CBCT images. Results: For ideal rigid phantoms, CBCT image-guided treatment can usually achieve setup accuracy of 1 mm or better. For the patients, after CBCT correction, the target setup error was reduced in almost all cases and was generally within ±1.5 mm. The image guidance process took 23-35 min, dictated by the computer speed and network configuration. The contribution of the intrafraction motion to the residual setup error was small, with a standard deviation of

  9. Double symbol error rates for differential detection of narrow-band FM

    Science.gov (United States)

    Simon, M. K.

    1985-01-01

    This paper evaluates the double symbol error rate (average probability of two consecutive symbol errors) in differentially detected narrow-band FM. Numerical results are presented for the special case of MSK with a Gaussian IF receive filter. It is shown that, not unlike similar results previously obtained for the single error probability of such systems, large inaccuracies in predicted performance can occur when intersymbol interference is ignored.

  10. The role of financial auditor in detecting and reporting fraud and error

    OpenAIRE

    Bunget, Ovidiu-Constantin

    2009-01-01

    Responsibility for preventing and detecting fraud rest with management entities. Although the auditor is not and cannot be held responsible for preventing fraud and errors, in your work, he can have a positive role in preventing fraud and errors by deterring their occurrence. The auditor should plan and perform the audit with an attitude of professional skepticism, recognizing that condition or events may be found that indicate that fraud or error may exist. Based on the audit risk asse...

  11. Neural Bases of Unconscious Error Detection in a Chinese Anagram Solution Task: Evidence from ERP Study.

    Directory of Open Access Journals (Sweden)

    Hua-Zhan Yin

    Full Text Available In everyday life, error monitoring and processing are important for improving ongoing performance in response to a changing environment. However, detecting an error is not always a conscious process. The temporal activation patterns of brain areas related to cognitive control in the absence of conscious awareness of an error remain unknown. In the present study, event-related potentials (ERPs in the brain were used to explore the neural bases of unconscious error detection when subjects solved a Chinese anagram task. Our ERP data showed that the unconscious error detection (UED response elicited a more negative ERP component (N2 than did no error (NE and detect error (DE responses in the 300-400-ms time window, and the DE elicited a greater late positive component (LPC than did the UED and NE in the 900-1200-ms time window after the onset of the anagram stimuli. Taken together with the results of dipole source analysis, the N2 (anterior cingulate cortex might reflect unconscious/automatic conflict monitoring, and the LPC (superior/medial frontal gyrus might reflect conscious error recognition.

  12. Detecting genotyping errors and describing black bear movement in northern Idaho

    Science.gov (United States)

    Michael K. Schwartz; Samuel A. Cushman; Kevin S. McKelvey; Jim Hayden; Cory Engkjer

    2006-01-01

    Non-invasive genetic sampling has become a favored tool to enumerate wildlife. Genetic errors, caused by poor quality samples, can lead to substantial biases in numerical estimates of individuals. We demonstrate how the computer program DROPOUT can detect amplification errors (false alleles and allelic dropout) in a black bear (Ursus americanus) dataset collected in...

  13. Filter design for failure detection and isolation in the presence of modeling errors and disturbances

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Stoustrup, Jakob

    1996-01-01

    The design problem of filters for robust failure detection and isolation, (FDI) is addressed in this paper. The failure detection problem will be considered with respect to both modeling errors and disturbances. Both an approach based on failure detection observers as well as an approach based...

  14. A dedicated on-line detecting system for auto air dryers

    Science.gov (United States)

    Shi, Chao-yu; Luo, Zai

    2013-10-01

    According to the correlative automobile industry standard and the requirements of manufacturer, this dedicated on-line detecting system is designed against the shortage of low degree automatic efficiency and detection precision of auto air dryer in the domestic. Fast automatic detection is achieved by combining the technology of computer control, mechatronics and pneumatics. This system can detect the speciality performance of pressure regulating valve and sealability of auto air dryer, in which online analytical processing of test data is available, at the same time, saving and inquiring data is achieved. Through some experimental analysis, it is indicated that efficient and accurate detection of the performance of auto air dryer is realized, and the test errors are less than 3%. Moreover, we carry out the type A evaluation of uncertainty in test data based on Bayesian theory, and the results show that the test uncertainties of all performance parameters are less than 0.5kPa, which can meet the requirements of operating industrial site absolutely.

  15. Attentional capture by irrelevant transients leads to perceptual errors in a competitive change detection task

    Directory of Open Access Journals (Sweden)

    Daniel eSchneider

    2012-05-01

    Full Text Available Theories on visual change detection imply that attention is a necessary but not sufficient prerequisite for aware perception. Misguidance of attention due to salient irrelevant distractors can therefore lead to severe deficits in change detection. The present study investigates the mechanisms behind such perceptual errors and their relation to error processing on higher cognitive levels. Participants had to detect a luminance change that occasionally occurred simultaneously with an irrelevant orientation change in the opposite hemi-field (conflict condition. By analyzing event-related potentials in the EEG separately in those error prone conflict trials for correct and erroneous change detection, we demonstrate that only correct change detection was associated with the allocation of attention to the relevant luminance change. Erroneous change detection was associated with an initial capture of attention towards the irrelevant orientation change in the N1 time window and a lack of subsequent target selection processes (N2pc. Errors were additionally accompanied by an increase of the fronto-central N2 and a kind of error negativity (Ne or ERN, which, however, peaked prior to the response. These results suggest that a strong perceptual conflict by salient distractors can disrupt the further processing of relevant information and thus affect its aware perception. Yet, it does not impair higher cognitive processes for conflict and error detection, indicating that these processes are independent from awareness.

  16. OUTLIER DETECTION IN PARTIAL ERRORS-IN-VARIABLES MODEL

    Directory of Open Access Journals (Sweden)

    JUN ZHAO

    Full Text Available The weighed total least square (WTLS estimate is very sensitive to the outliers in the partial EIV model. A new procedure for detecting outliers based on the data-snooping is presented in this paper. Firstly, a two-step iterated method of computing the WTLS estimates for the partial EIV model based on the standard LS theory is proposed. Secondly, the corresponding w-test statistics are constructed to detect outliers while the observations and coefficient matrix are contaminated with outliers, and a specific algorithm for detecting outliers is suggested. When the variance factor is unknown, it may be estimated by the least median squares (LMS method. At last, the simulated data and real data about two-dimensional affine transformation are analyzed. The numerical results show that the new test procedure is able to judge that the outliers locate in x component, y component or both components in coordinates while the observations and coefficient matrix are contaminated with outliers

  17. Improvement of the Error-detection Mechanism in Adults with Dyslexia Following Reading Acceleration Training.

    Science.gov (United States)

    Horowitz-Kraus, Tzipi

    2016-05-01

    The error-detection mechanism aids in preventing error repetition during a given task. Electroencephalography demonstrates that error detection involves two event-related potential components: error-related and correct-response negativities (ERN and CRN, respectively). Dyslexia is characterized by slow, inaccurate reading. In particular, individuals with dyslexia have a less active error-detection mechanism during reading than typical readers. In the current study, we examined whether a reading training programme could improve the ability to recognize words automatically (lexical representations) in adults with dyslexia, thereby resulting in more efficient error detection during reading. Behavioural and electrophysiological measures were obtained using a lexical decision task before and after participants trained with the reading acceleration programme. ERN amplitudes were smaller in individuals with dyslexia than in typical readers before training but increased following training, as did behavioural reading scores. Differences between the pre-training and post-training ERN and CRN components were larger in individuals with dyslexia than in typical readers. Also, the error-detection mechanism as represented by the ERN/CRN complex might serve as a biomarker for dyslexia and be used to evaluate the effectiveness of reading intervention programmes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  18. Assessing the Library Homepages of COPLAC Institutions for Section 508 Accessibility Errors: Who's Accessible, Who's Not, and How the Online WebXACT Assessment Tool Can Help

    Science.gov (United States)

    Huprich, Julia; Green, Ravonne

    2007-01-01

    The Council on Public Liberal Arts Colleges (COPLAC) libraries websites were assessed for Section 508 errors using the online WebXACT tool. Only three of the twenty-one institutions (14%) had zero accessibility errors. Eighty-six percent of the COPLAC institutions had an average of 1.24 errors. Section 508 compliance is required for institutions…

  19. A Multipoint Method for Detecting Genotyping Errors and Mutations in Sibling-Pair Linkage Data

    OpenAIRE

    Douglas, Julie A.; Boehnke, Michael; Lange, Kenneth

    2000-01-01

    The identification of genes contributing to complex diseases and quantitative traits requires genetic data of high fidelity, because undetected errors and mutations can profoundly affect linkage information. The recent emphasis on the use of the sibling-pair design eliminates or decreases the likelihood of detection of genotyping errors and marker mutations through apparent Mendelian incompatibilities or close double recombinants. In this article, we describe a hidden Markov method for detect...

  20. Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors

    DEFF Research Database (Denmark)

    Nguyen, Chuyen T.; Hayashi, Kazunori; Kaneko, Megumi

    2013-01-01

    Abstract Estimation schemes of Radio Frequency IDentification (RFID) tag set cardinality are studied in this paper using Maximum Likelihood (ML) approach. We consider the estimation problem under the model of multiple independent reader sessions with detection errors due to unreliable radio...... is evaluated under dierent system parameters and compared with that of the conventional method via computer simulations assuming flat Rayleigh fading environments and framed-slotted ALOHA based protocol. Keywords RFID tag cardinality estimation maximum likelihood detection error...

  1. Design Margin Elimination Through Robust Timing Error Detection at Ultra-Low Voltage

    OpenAIRE

    Reyserhove, Hans; Dehaene, Wim

    2017-01-01

    This paper discusses a timing error masking-aware ARM Cortex M0 microcontroller system. Through in-path timing error detection, operation at the point-of-first-failure is possi- ble without corrupting the pipeline state, effectively eliminat- ing traditional timing margins. Error events are flagged and gathered to allow dynamic voltage scaling. The error-aware microcontroller was implemented in a 40nm CMOS process and realizes ultra-low voltage operation down to 0.29V at 5MHz consuming 12.90p...

  2. A heuristic approach to edge detection in on-line portal imaging

    International Nuclear Information System (INIS)

    McGee, Kiaran P.; Schultheiss, Timothy E.; Martin, Eric E.

    1995-01-01

    Purpose: Portal field edge detection is an essential component of several postprocessing techniques used in on-line portal imaging, including field shape verification, selective contrast enhancement, and treatment setup error detection. Currently edge detection of successive fractions in a multifraction portal image series involves the repetitive application of the same algorithm. As the number of changes in the field is small compared to the total number of fractions, standard edge detection algorithms essentially recalculate the same field shape numerous times. A heuristic approach to portal edge detection has been developed that takes advantage of the relatively few changes in the portal field shape throughout a fractionation series. Methods and Materials: The routine applies a standard edge detection routine to calculate an initial field edge and saves the edge information. Subsequent fractions are processed by applying an edge detection operator over a small region about each point of the previously defined contour, to determine any shifts in the field shape in the new image. Failure of this edge check indicates that a significant change in the field edge has occurred, and the original edge detection routine is applied to the image. Otherwise the modified edge contour is used to define the new edge. Results: Two hundred and eighty-one portal images collected from an electronic portal imaging device were processed by the edge detection routine. The algorithm accurately calculated each portal field edge, as well as reducing processing time in subsequent fractions of an individual portal field by a factor of up to 14. Conclusions: The heuristic edge detection routine is an accurate and fast method for calculating portal field edges and determining field edge setup errors

  3. Using Analysis Increments (AI) to Estimate and Correct Systematic Errors in the Global Forecast System (GFS) Online

    Science.gov (United States)

    Bhargava, K.; Kalnay, E.; Carton, J.; Yang, F.

    2017-12-01

    Systematic forecast errors, arising from model deficiencies, form a significant portion of the total forecast error in weather prediction models like the Global Forecast System (GFS). While much effort has been expended to improve models, substantial model error remains. The aim here is to (i) estimate the model deficiencies in the GFS that lead to systematic forecast errors, (ii) implement an online correction (i.e., within the model) scheme to correct GFS following the methodology of Danforth et al. [2007] and Danforth and Kalnay [2008, GRL]. Analysis Increments represent the corrections that new observations make on, in this case, the 6-hr forecast in the analysis cycle. Model bias corrections are estimated from the time average of the analysis increments divided by 6-hr, assuming that initial model errors grow linearly and first ignoring the impact of observation bias. During 2012-2016, seasonal means of the 6-hr model bias are generally robust despite changes in model resolution and data assimilation systems, and their broad continental scales explain their insensitivity to model resolution. The daily bias dominates the sub-monthly analysis increments and consists primarily of diurnal and semidiurnal components, also requiring a low dimensional correction. Analysis increments in 2015 and 2016 are reduced over oceans, which is attributed to improvements in the specification of the SSTs. These results encourage application of online correction, as suggested by Danforth and Kalnay, for mean, seasonal and diurnal and semidiurnal model biases in GFS to reduce both systematic and random errors. As the error growth in the short-term is still linear, estimated model bias corrections can be added as a forcing term in the model tendency equation to correct online. Preliminary experiments with GFS, correcting temperature and specific humidity online show reduction in model bias in 6-hr forecast. This approach can then be used to guide and optimize the design of sub

  4. Detection method of nonlinearity errors by statistical signal analysis in heterodyne Michelson interferometer.

    Science.gov (United States)

    Hu, Juju; Hu, Haijiang; Ji, Yinghua

    2010-03-15

    Periodic nonlinearity that ranges from tens of nanometers to a few nanometers in heterodyne interferometer limits its use in high accuracy measurement. A novel method is studied to detect the nonlinearity errors based on the electrical subdivision and the analysis method of statistical signal in heterodyne Michelson interferometer. Under the movement of micropositioning platform with the uniform velocity, the method can detect the nonlinearity errors by using the regression analysis and Jackknife estimation. Based on the analysis of the simulations, the method can estimate the influence of nonlinearity errors and other noises for the dimensions measurement in heterodyne Michelson interferometer.

  5. Students versus Plagiarism: How is Online Plagiarism Detection Service Perceived?

    Directory of Open Access Journals (Sweden)

    Muhammad Affan Ramadhana

    2016-08-01

    Full Text Available The development of information and communication technology plays a considerable role for students in writing their theses. The positive side, it will help the students to find countless number of academic sources ranging from journal articles to complete theses written by other scholars. On the other hand, it will also create a chance for the students to commit plagiarism easier. Unoriginal writing and plagiarism in this digital era can be detected in the digital way by using plagiarism detection software. This paper elaborates how students understand the concept of plagiarism, how they avoid plagiarism, and how they perceive online plagiarism detection service. The data was taken from interviews to MA students during their period of thesis writing. This paper concludes several important outlines to be learning guidelines for the students in improving their academic writing.

  6. Thresholds for human detection of patient setup errors in digitally reconstructed portal images of prostate fields

    International Nuclear Information System (INIS)

    Phillips, Brooke L.; Jiroutek, Michael R.; Tracton, Gregg; Elfervig, Michelle; Muller, Keith E.; Chaney, Edward L.

    2002-01-01

    Purpose: Computer-assisted methods to analyze electronic portal images for the presence of treatment setup errors should be studied in controlled experiments before use in the clinical setting. Validation experiments using images that contain known errors usually report the smallest errors that can be detected by the image analysis algorithm. This paper offers human error-detection thresholds as one benchmark for evaluating the smallest errors detected by algorithms. Unfortunately, reliable data are lacking describing human performance. The most rigorous benchmarks for human performance are obtained under conditions that favor error detection. To establish such benchmarks, controlled observer studies were carried out to determine the thresholds of detectability for in-plane and out-of-plane translation and rotation setup errors introduced into digitally reconstructed portal radiographs (DRPRs) of prostate fields. Methods and Materials: Seventeen observers comprising radiation oncologists, radiation oncology residents, physicists, and therapy students participated in a two-alternative forced choice experiment involving 378 DRPRs computed using the National Library of Medicine Visible Human data sets. An observer viewed three images at a time displayed on adjacent computer monitors. Each image triplet included a reference digitally reconstructed radiograph displayed on the central monitor and two DRPRs displayed on the flanking monitors. One DRPR was error free. The other DRPR contained a known in-plane or out-of-plane error in the placement of the treatment field over a target region in the pelvis. The range for each type of error was determined from pilot observer studies based on a Probit model for error detection. The smallest errors approached the limit of human visual capability. The observer was told what kind of error was introduced, and was asked to choose the DRPR that contained the error. Observer decisions were recorded and analyzed using repeated

  7. Detection and correction of prescription errors by an emergency department pharmacy service.

    Science.gov (United States)

    Stasiak, Philip; Afilalo, Marc; Castelino, Tanya; Xue, Xiaoqing; Colacone, Antoinette; Soucy, Nathalie; Dankoff, Jerrald

    2014-05-01

    Emergency departments (EDs) are recognized as a high-risk setting for prescription errors. Pharmacist involvement may be important in reviewing prescriptions to identify and correct errors. The objectives of this study were to describe the frequency and type of prescription errors detected by pharmacists in EDs, determine the proportion of errors that could be corrected, and identify factors associated with prescription errors. This prospective observational study was conducted in a tertiary care teaching ED on 25 consecutive weekdays. Pharmacists reviewed all documented prescriptions and flagged and corrected errors for patients in the ED. We collected information on patient demographics, details on prescription errors, and the pharmacists' recommendations. A total of 3,136 ED prescriptions were reviewed. The proportion of prescriptions in which a pharmacist identified an error was 3.2% (99 of 3,136; 95% confidence interval [CI] 2.5-3.8). The types of identified errors were wrong dose (28 of 99, 28.3%), incomplete prescription (27 of 99, 27.3%), wrong frequency (15 of 99, 15.2%), wrong drug (11 of 99, 11.1%), wrong route (1 of 99, 1.0%), and other (17 of 99, 17.2%). The pharmacy service intervened and corrected 78 (78 of 99, 78.8%) errors. Factors associated with prescription errors were patient age over 65 (odds ratio [OR] 2.34; 95% CI 1.32-4.13), prescriptions with more than one medication (OR 5.03; 95% CI 2.54-9.96), and those written by emergency medicine residents compared to attending emergency physicians (OR 2.21, 95% CI 1.18-4.14). Pharmacists in a tertiary ED are able to correct the majority of prescriptions in which they find errors. Errors are more likely to be identified in prescriptions written for older patients, those containing multiple medication orders, and those prescribed by emergency residents.

  8. Online visual feedback during error-free channel trials leads to active unlearning of movement dynamics: evidence for adaptation to trajectory prediction errors.

    Directory of Open Access Journals (Sweden)

    Angel Lago-Rodriguez

    2016-09-01

    Full Text Available Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group, when compared with participants who had no EC feedback regarding movement trajectory (Arc group. Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group. Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory.

  9. Multi-bits error detection and fast recovery in RISC cores

    International Nuclear Information System (INIS)

    Wang Jing; Yang Xing; Zhang Weigong; Shen Jiao; Qiu Keni; Zhao Yuanfu

    2015-01-01

    The particles-induced soft errors are a major threat to the reliability of microprocessors. Even worse, multi-bits upsets (MBUs) are ever-increased due to the rapidly shrinking feature size of the IC on a chip. Several architecture-level mechanisms have been proposed to protect microprocessors from soft errors, such as dual and triple modular redundancies (DMR and TMR). However, most of them are inefficient to combat the growing multi-bits errors or cannot well balance the critical paths delay, area and power penalty. This paper proposes a novel architecture, self-recovery dual-pipeline (SRDP), to effectively provide soft error detection and recovery with low cost for general RISC structures. We focus on the following three aspects. First, an advanced DMR pipeline is devised to detect soft error, especially MBU. Second, SEU/MBU errors can be located by enhancing self-checking logic into pipelines stage registers. Third, a recovery scheme is proposed with a recovery cost of 1 or 5 clock cycles. Our evaluation of a prototype implementation exhibits that the SRDP can successfully detect particle-induced soft errors up to 100% and recovery is nearly 95%, the other 5% will inter a specific trap. (paper)

  10. Multi-bits error detection and fast recovery in RISC cores

    Science.gov (United States)

    Jing, Wang; Xing, Yang; Yuanfu, Zhao; Weigong, Zhang; Jiao, Shen; Keni, Qiu

    2015-11-01

    The particles-induced soft errors are a major threat to the reliability of microprocessors. Even worse, multi-bits upsets (MBUs) are ever-increased due to the rapidly shrinking feature size of the IC on a chip. Several architecture-level mechanisms have been proposed to protect microprocessors from soft errors, such as dual and triple modular redundancies (DMR and TMR). However, most of them are inefficient to combat the growing multi-bits errors or cannot well balance the critical paths delay, area and power penalty. This paper proposes a novel architecture, self-recovery dual-pipeline (SRDP), to effectively provide soft error detection and recovery with low cost for general RISC structures. We focus on the following three aspects. First, an advanced DMR pipeline is devised to detect soft error, especially MBU. Second, SEU/MBU errors can be located by enhancing self-checking logic into pipelines stage registers. Third, a recovery scheme is proposed with a recovery cost of 1 or 5 clock cycles. Our evaluation of a prototype implementation exhibits that the SRDP can successfully detect particle-induced soft errors up to 100% and recovery is nearly 95%, the other 5% will inter a specific trap.

  11. Minimum Symbol Error Rate Detection in Single-Input Multiple-Output Channels with Markov Noise

    DEFF Research Database (Denmark)

    Christensen, Lars P.B.

    2005-01-01

    Minimum symbol error rate detection in Single-Input Multiple- Output(SIMO) channels with Markov noise is presented. The special case of zero-mean Gauss-Markov noise is examined closer as it only requires knowledge of the second-order moments. In this special case, it is shown that optimal detection...

  12. CUSUM-Logistic Regression analysis for the rapid detection of errors in clinical laboratory test results.

    Science.gov (United States)

    Sampson, Maureen L; Gounden, Verena; van Deventer, Hendrik E; Remaley, Alan T

    2016-02-01

    The main drawback of the periodic analysis of quality control (QC) material is that test performance is not monitored in time periods between QC analyses, potentially leading to the reporting of faulty test results. The objective of this study was to develop a patient based QC procedure for the more timely detection of test errors. Results from a Chem-14 panel measured on the Beckman LX20 analyzer were used to develop the model. Each test result was predicted from the other 13 members of the panel by multiple regression, which resulted in correlation coefficients between the predicted and measured result of >0.7 for 8 of the 14 tests. A logistic regression model, which utilized the measured test result, the predicted test result, the day of the week and time of day, was then developed for predicting test errors. The output of the logistic regression was tallied by a daily CUSUM approach and used to predict test errors, with a fixed specificity of 90%. The mean average run length (ARL) before error detection by CUSUM-Logistic Regression (CSLR) was 20 with a mean sensitivity of 97%, which was considerably shorter than the mean ARL of 53 (sensitivity 87.5%) for a simple prediction model that only used the measured result for error detection. A CUSUM-Logistic Regression analysis of patient laboratory data can be an effective approach for the rapid and sensitive detection of clinical laboratory errors. Published by Elsevier Inc.

  13. Detection of layup errors in prepreg laminates using shear ultrasonic waves

    Science.gov (United States)

    Hsu, David K.; Fischer, Brent A.

    1996-11-01

    The highly anisotropic elastic properties of the plies in a composite laminate manufactured from unidirectional prepregs interact strongly with the polarization direction of shear ultrasonic waves propagating through its thickness. The received signals in a 'crossed polarizer' transmission configuration are particularly sensitive to ply orientation and layup sequence in a laminate. Such measurements can therefore serve as an NDE tool for detecting layup errors. For example, it was shown experimentally recently that the sensitivity for detecting the presence of misoriented plies is better than one ply out of a 48-ply laminate of graphite epoxy. A physical model based on the decomposition and recombination of the shear polarization vector has been constructed and used in the interpretation and prediction of test results. Since errors should be detected early in the manufacturing process, this work also addresses the inspection of 'green' composite laminates using electromagnetic acoustic transducers (EMAT). Preliminary results for ply error detection obtained with EMAT probes are described.

  14. Evaluating suggestibility to additive and contradictory misinformation following explicit error detection in younger and older adults.

    Science.gov (United States)

    Huff, Mark J; Umanath, Sharda

    2018-06-01

    In 2 experiments, we assessed age-related suggestibility to additive and contradictory misinformation (i.e., remembering of false details from an external source). After reading a fictional story, participants answered questions containing misleading details that were either additive (misleading details that supplemented an original event) or contradictory (errors that changed original details). On a final test, suggestibility was greater for additive than contradictory misinformation, and older adults endorsed fewer false contradictory details than younger adults. To mitigate suggestibility in Experiment 2, participants were warned about potential errors, instructed to detect errors, or instructed to detect errors after exposure to examples of additive and contradictory details. Again, suggestibility to additive misinformation was greater than contradictory, and older adults endorsed less contradictory misinformation. Only after detection instructions with misinformation examples were younger adults able to reduce contradictory misinformation effects and reduced these effects to the level of older adults. Additive misinformation however, was immune to all warning and detection instructions. Thus, older adults were less susceptible to contradictory misinformation errors, and younger adults could match this misinformation rate when warning/detection instructions were strong. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning

    Science.gov (United States)

    Wagstaff, Kiri L.; Bornstein, Benjamin; Granat, Robert; Tang, Benyang; Turmon, Michael

    2009-01-01

    Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.

  16. Development of safety analysis and constraint detection techniques for process interaction errors

    International Nuclear Information System (INIS)

    Fan, Chin-Feng; Tsai, Shang-Lin; Tseng, Wan-Hui

    2011-01-01

    Among the new failure modes introduced by computer into safety systems, the process interaction error is the most unpredictable and complicated failure mode, which may cause disastrous consequences. This paper presents safety analysis and constraint detection techniques for process interaction errors among hardware, software, and human processes. Among interaction errors, the most dreadful ones are those that involve run-time misinterpretation from a logic process. We call them the 'semantic interaction errors'. Such abnormal interaction is not adequately emphasized in current research. In our static analysis, we provide a fault tree template focusing on semantic interaction errors by checking conflicting pre-conditions and post-conditions among interacting processes. Thus, far-fetched, but highly risky, interaction scenarios involve interpretation errors can be identified. For run-time monitoring, a range of constraint types is proposed for checking abnormal signs at run time. We extend current constraints to a broader relational level and a global level, considering process/device dependencies and physical conservation rules in order to detect process interaction errors. The proposed techniques can reduce abnormal interactions; they can also be used to assist in safety-case construction.

  17. Development of safety analysis and constraint detection techniques for process interaction errors

    Energy Technology Data Exchange (ETDEWEB)

    Fan, Chin-Feng, E-mail: csfanc@saturn.yzu.edu.tw [Computer Science and Engineering Dept., Yuan-Ze University, Taiwan (China); Tsai, Shang-Lin; Tseng, Wan-Hui [Computer Science and Engineering Dept., Yuan-Ze University, Taiwan (China)

    2011-02-15

    Among the new failure modes introduced by computer into safety systems, the process interaction error is the most unpredictable and complicated failure mode, which may cause disastrous consequences. This paper presents safety analysis and constraint detection techniques for process interaction errors among hardware, software, and human processes. Among interaction errors, the most dreadful ones are those that involve run-time misinterpretation from a logic process. We call them the 'semantic interaction errors'. Such abnormal interaction is not adequately emphasized in current research. In our static analysis, we provide a fault tree template focusing on semantic interaction errors by checking conflicting pre-conditions and post-conditions among interacting processes. Thus, far-fetched, but highly risky, interaction scenarios involve interpretation errors can be identified. For run-time monitoring, a range of constraint types is proposed for checking abnormal signs at run time. We extend current constraints to a broader relational level and a global level, considering process/device dependencies and physical conservation rules in order to detect process interaction errors. The proposed techniques can reduce abnormal interactions; they can also be used to assist in safety-case construction.

  18. Detecting medication errors in the New Zealand pharmacovigilance database: a retrospective analysis.

    Science.gov (United States)

    Kunac, Desireé L; Tatley, Michael V

    2011-01-01

    Despite the traditional focus being adverse drug reactions (ADRs), pharmacovigilance centres have recently been identified as a potentially rich and important source of medication error data. To identify medication errors in the New Zealand Pharmacovigilance database (Centre for Adverse Reactions Monitoring [CARM]), and to describe the frequency and characteristics of these events. A retrospective analysis of the CARM pharmacovigilance database operated by the New Zealand Pharmacovigilance Centre was undertaken for the year 1 January-31 December 2007. All reports, excluding those relating to vaccines, clinical trials and pharmaceutical company reports, underwent a preventability assessment using predetermined criteria. Those events deemed preventable were subsequently classified to identify the degree of patient harm, type of error, stage of medication use process where the error occurred and origin of the error. A total of 1412 reports met the inclusion criteria and were reviewed, of which 4.3% (61/1412) were deemed preventable. Not all errors resulted in patient harm: 29.5% (18/61) were 'no harm' errors but 65.5% (40/61) of errors were deemed to have been associated with some degree of patient harm (preventable adverse drug events [ADEs]). For 5.0% (3/61) of events, the degree of patient harm was unable to be determined as the patient outcome was unknown. The majority of preventable ADEs (62.5% [25/40]) occurred in adults aged 65 years and older. The medication classes most involved in preventable ADEs were antibacterials for systemic use and anti-inflammatory agents, with gastrointestinal and respiratory system disorders the most common adverse events reported. For both preventable ADEs and 'no harm' events, most errors were incorrect dose and drug therapy monitoring problems consisting of failures in detection of significant drug interactions, past allergies or lack of necessary clinical monitoring. Preventable events were mostly related to the prescribing and

  19. Applications of pattern recognition techniques to online fault detection

    International Nuclear Information System (INIS)

    Singer, R.M.; Gross, K.C.; King, R.W.

    1993-01-01

    A common problem to operators of complex industrial systems is the early detection of incipient degradation of sensors and components in order to avoid unplanned outages, to orderly plan for anticipated maintenance activities and to assure continued safe operation. In such systems, there usually are a large number of sensors (upwards of several thousand is not uncommon) serving many functions, ranging from input to control systems, monitoring of safety parameters and component performance limits, system environmental conditions, etc. Although sensors deemed to measure important process conditions are generally alarmed, the alarm set points usually are just high-low limits and the operator's response to such alarms is based on written procedures and his or her experience and training. In many systems this approach has been successful, but in situations where the cost of a forced outage is high an improved method is needed. In such cases it is desirable, if not necessary, to detect disturbances in either sensors or the process prior to any actual failure that could either shut down the process or challenge any safety system that is present. Recent advances in various artificial intelligence techniques have provided the opportunity to perform such functions of early detection and diagnosis. In this paper, the experience gained through the application of several pattern-recognition techniques to the on-line monitoring and incipient disturbance detection of several coolant pumps and numerous sensors at the Experimental Breeder Reactor-II (EBR-II) which is located at the Idaho National Engineering Laboratory is presented

  20. An Approach to Human Error Hazard Detection of Unexpected Situations in NPPs

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sangjun; Oh, Yeonju; Shin, Youmin; Lee, Yong-Hee [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    Fukushima accident is a typical complex event including the extreme situations induced by the succeeding earthquake, tsunami, explosion, and human errors. And it is judged with incomplete cause of system build-up same manner, procedure as a deficiency of response manual, education and training, team capability and the discharge of operator from human engineering point of view. Especially, the guidelines of current operating NPPs are not enough including countermeasures to the human errors at the extreme situations. Therefore, this paper describes a trial to detect the hazards of human errors at extreme situation, and to define the countermeasures that can properly response to the human error hazards when an individual, team, organization, and working entities that encounter the extreme situation in NPPs. In this paper we try to propose an approach to analyzing and extracting human error hazards for suggesting additional countermeasures to the human errors in unexpected situations. They might be utilized to develop contingency guidelines, especially for reducing the human error accident in NPPs. But the trial application in this study is currently limited since it is not easy to find accidents cases in detail enough to enumerate the proposed steps. Therefore, we will try to analyze as more cases as possible, and consider other environmental factors and human error conditions.

  1. A Case for Soft Error Detection and Correction in Computational Chemistry.

    Science.gov (United States)

    van Dam, Hubertus J J; Vishnu, Abhinav; de Jong, Wibe A

    2013-09-10

    High performance computing platforms are expected to deliver 10(18) floating operations per second by the year 2022 through the deployment of millions of cores. Even if every core is highly reliable the sheer number of them will mean that the mean time between failures will become so short that most application runs will suffer at least one fault. In particular soft errors caused by intermittent incorrect behavior of the hardware are a concern as they lead to silent data corruption. In this paper we investigate the impact of soft errors on optimization algorithms using Hartree-Fock as a particular example. Optimization algorithms iteratively reduce the error in the initial guess to reach the intended solution. Therefore they may intuitively appear to be resilient to soft errors. Our results show that this is true for soft errors of small magnitudes but not for large errors. We suggest error detection and correction mechanisms for different classes of data structures. The results obtained with these mechanisms indicate that we can correct more than 95% of the soft errors at moderate increases in the computational cost.

  2. An Approach to Human Error Hazard Detection of Unexpected Situations in NPPs

    International Nuclear Information System (INIS)

    Park, Sangjun; Oh, Yeonju; Shin, Youmin; Lee, Yong-Hee

    2015-01-01

    Fukushima accident is a typical complex event including the extreme situations induced by the succeeding earthquake, tsunami, explosion, and human errors. And it is judged with incomplete cause of system build-up same manner, procedure as a deficiency of response manual, education and training, team capability and the discharge of operator from human engineering point of view. Especially, the guidelines of current operating NPPs are not enough including countermeasures to the human errors at the extreme situations. Therefore, this paper describes a trial to detect the hazards of human errors at extreme situation, and to define the countermeasures that can properly response to the human error hazards when an individual, team, organization, and working entities that encounter the extreme situation in NPPs. In this paper we try to propose an approach to analyzing and extracting human error hazards for suggesting additional countermeasures to the human errors in unexpected situations. They might be utilized to develop contingency guidelines, especially for reducing the human error accident in NPPs. But the trial application in this study is currently limited since it is not easy to find accidents cases in detail enough to enumerate the proposed steps. Therefore, we will try to analyze as more cases as possible, and consider other environmental factors and human error conditions

  3. Latency and mode of error detection as reflected in Swedish licensee event reports

    Energy Technology Data Exchange (ETDEWEB)

    Svenson, Ola; Salo, Ilkka [Stockholm Univ., (Sweden). Dept. of Psychology

    2002-03-01

    Licensee event reports (LERs) from an industry provide important information feedback about safety to the industry itself, the regulators and to the public. LERs from four nuclear power reactors were analyzed to find out about detection times, mode of detection and qualitative differences in reports from different reactors. The reliability of the coding was satisfactory and measured as the covariance between the ratings from two independent judges. The results showed differences in detection time across the reactors. On the average about ten percent of the errors remained undetected for 100 weeks or more, but the great majority of errors were detected soon after their first appearance in the plant. On the average 40 percent of the errors were detected in regular tests and 40 per cent through alarms. Operators found about 10 per cent of the errors through noticing something abnormal in the plant. The remaining errors were detected in various other ways. There were qualitative differences between the LERs from the different reactors reflecting the different conditions in the plants. The number of reports differed by a magnitude 1:2 between the different plants. However, a greater number of LERs can indicate both higher safety standards (e.g., a greater willingness to report all possible events to be able to learn from them) and lower safety standards (e.g., reporting as few events as possible to make a good impression). It was pointed out that LERs are indispensable in order to maintain safety of an industry and that the differences between plants found in the analyses of this study indicate how error reports can be used to initiate further investigations for improved safety.

  4. Latency and mode of error detection as reflected in Swedish licensee event reports

    International Nuclear Information System (INIS)

    Svenson, Ola; Salo, Ilkka

    2002-03-01

    Licensee event reports (LERs) from an industry provide important information feedback about safety to the industry itself, the regulators and to the public. LERs from four nuclear power reactors were analyzed to find out about detection times, mode of detection and qualitative differences in reports from different reactors. The reliability of the coding was satisfactory and measured as the covariance between the ratings from two independent judges. The results showed differences in detection time across the reactors. On the average about ten percent of the errors remained undetected for 100 weeks or more, but the great majority of errors were detected soon after their first appearance in the plant. On the average 40 percent of the errors were detected in regular tests and 40 per cent through alarms. Operators found about 10 per cent of the errors through noticing something abnormal in the plant. The remaining errors were detected in various other ways. There were qualitative differences between the LERs from the different reactors reflecting the different conditions in the plants. The number of reports differed by a magnitude 1:2 between the different plants. However, a greater number of LERs can indicate both higher safety standards (e.g., a greater willingness to report all possible events to be able to learn from them) and lower safety standards (e.g., reporting as few events as possible to make a good impression). It was pointed out that LERs are indispensable in order to maintain safety of an industry and that the differences between plants found in the analyses of this study indicate how error reports can be used to initiate further investigations for improved safety

  5. Efficient detection of dangling pointer error for C/C++ programs

    Science.gov (United States)

    Zhang, Wenzhe

    2017-08-01

    Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method.

  6. SU-F-T-310: Does a Head-Mounted Ionization Chamber Detect IMRT Errors?

    International Nuclear Information System (INIS)

    Wegener, S; Herzog, B; Sauer, O

    2016-01-01

    Purpose: The conventional plan verification strategy is delivering a plan to a QA-phantom before the first treatment. Monitoring each fraction of the patient treatment in real-time would improve patient safety. We evaluated how well a new detector, the IQM (iRT Systems, Germany), is capable of detecting errors we induced into IMRT plans of three different treatment regions. Results were compared to an established phantom. Methods: Clinical plans of a brain, prostate and head-and-neck patient were modified in the Pinnacle planning system, such that they resulted in either several percent lower prescribed doses to the target volume or several percent higher doses to relevant organs at risk. Unaltered plans were measured on three days, modified plans once, each with the IQM at an Elekta Synergy with an Agility MLC. All plans were also measured with the ArcCHECK with the cavity plug and a PTW semiflex 31010 ionization chamber inserted. Measurements were evaluated with SNC patient software. Results: Repeated IQM measurements of the original plans were reproducible, such that a 1% deviation from the mean as warning and 3% as action level as suggested by the manufacturer seemed reasonable. The IQM detected most of the simulated errors including wrong energy, a faulty leaf, wrong trial exported and a 2 mm shift of one leaf bank. Detection limits were reached for two plans - a 2 mm field position error and a leaf bank offset combined with an MU change. ArcCHECK evaluation according to our current standards also left undetected errors. Ionization chamber evaluation alone would leave most errors undetected. Conclusion: The IQM detected most errors and performed as well as currently established phantoms with the advantage that it can be used throughout the whole treatment. Drawback is that it does not indicate the source of the error.

  7. SU-F-T-310: Does a Head-Mounted Ionization Chamber Detect IMRT Errors?

    Energy Technology Data Exchange (ETDEWEB)

    Wegener, S; Herzog, B; Sauer, O [University of Wuerzburg, Wuerzburg (Germany)

    2016-06-15

    Purpose: The conventional plan verification strategy is delivering a plan to a QA-phantom before the first treatment. Monitoring each fraction of the patient treatment in real-time would improve patient safety. We evaluated how well a new detector, the IQM (iRT Systems, Germany), is capable of detecting errors we induced into IMRT plans of three different treatment regions. Results were compared to an established phantom. Methods: Clinical plans of a brain, prostate and head-and-neck patient were modified in the Pinnacle planning system, such that they resulted in either several percent lower prescribed doses to the target volume or several percent higher doses to relevant organs at risk. Unaltered plans were measured on three days, modified plans once, each with the IQM at an Elekta Synergy with an Agility MLC. All plans were also measured with the ArcCHECK with the cavity plug and a PTW semiflex 31010 ionization chamber inserted. Measurements were evaluated with SNC patient software. Results: Repeated IQM measurements of the original plans were reproducible, such that a 1% deviation from the mean as warning and 3% as action level as suggested by the manufacturer seemed reasonable. The IQM detected most of the simulated errors including wrong energy, a faulty leaf, wrong trial exported and a 2 mm shift of one leaf bank. Detection limits were reached for two plans - a 2 mm field position error and a leaf bank offset combined with an MU change. ArcCHECK evaluation according to our current standards also left undetected errors. Ionization chamber evaluation alone would leave most errors undetected. Conclusion: The IQM detected most errors and performed as well as currently established phantoms with the advantage that it can be used throughout the whole treatment. Drawback is that it does not indicate the source of the error.

  8. Maximum error-bounded Piecewise Linear Representation for online stream approximation

    KAUST Repository

    Xie, Qing; Pang, Chaoyi; Zhou, Xiaofang; Zhang, Xiangliang; Deng, Ke

    2014-01-01

    Given a time series data stream, the generation of error-bounded Piecewise Linear Representation (error-bounded PLR) is to construct a number of consecutive line segments to approximate the stream, such that the approximation error does not exceed a prescribed error bound. In this work, we consider the error bound in L∞ norm as approximation criterion, which constrains the approximation error on each corresponding data point, and aim on designing algorithms to generate the minimal number of segments. In the literature, the optimal approximation algorithms are effectively designed based on transformed space other than time-value space, while desirable optimal solutions based on original time domain (i.e., time-value space) are still lacked. In this article, we proposed two linear-time algorithms to construct error-bounded PLR for data stream based on time domain, which are named OptimalPLR and GreedyPLR, respectively. The OptimalPLR is an optimal algorithm that generates minimal number of line segments for the stream approximation, and the GreedyPLR is an alternative solution for the requirements of high efficiency and resource-constrained environment. In order to evaluate the superiority of OptimalPLR, we theoretically analyzed and compared OptimalPLR with the state-of-art optimal solution in transformed space, which also achieves linear complexity. We successfully proved the theoretical equivalence between time-value space and such transformed space, and also discovered the superiority of OptimalPLR on processing efficiency in practice. The extensive results of empirical evaluation support and demonstrate the effectiveness and efficiency of our proposed algorithms.

  9. Maximum error-bounded Piecewise Linear Representation for online stream approximation

    KAUST Repository

    Xie, Qing

    2014-04-04

    Given a time series data stream, the generation of error-bounded Piecewise Linear Representation (error-bounded PLR) is to construct a number of consecutive line segments to approximate the stream, such that the approximation error does not exceed a prescribed error bound. In this work, we consider the error bound in L∞ norm as approximation criterion, which constrains the approximation error on each corresponding data point, and aim on designing algorithms to generate the minimal number of segments. In the literature, the optimal approximation algorithms are effectively designed based on transformed space other than time-value space, while desirable optimal solutions based on original time domain (i.e., time-value space) are still lacked. In this article, we proposed two linear-time algorithms to construct error-bounded PLR for data stream based on time domain, which are named OptimalPLR and GreedyPLR, respectively. The OptimalPLR is an optimal algorithm that generates minimal number of line segments for the stream approximation, and the GreedyPLR is an alternative solution for the requirements of high efficiency and resource-constrained environment. In order to evaluate the superiority of OptimalPLR, we theoretically analyzed and compared OptimalPLR with the state-of-art optimal solution in transformed space, which also achieves linear complexity. We successfully proved the theoretical equivalence between time-value space and such transformed space, and also discovered the superiority of OptimalPLR on processing efficiency in practice. The extensive results of empirical evaluation support and demonstrate the effectiveness and efficiency of our proposed algorithms.

  10. Spreadsheet Error Detection: an Empirical Examination in the Context of Greece

    Directory of Open Access Journals (Sweden)

    Dimitrios Maditinos

    2012-06-01

    Full Text Available The personal computers era made advanced programming tasks available to end users. Spreadsheet models are one of the most widely used applications that can produce valuable results with minimal training and effort. However, errors contained in most spreadsheets may be catastrophic and difficult to detect. This study attempts to investigate the influence of experience and spreadsheet presentation on the error finding performance by end users. To reach the target of the study, 216 business and finance students participated in a task of finding errors in a simple free cash flow model. The findings of the study reveal that presentation of the spreadsheet is of major importance as far as the error finding performance is concerned, while experience does not seem to affect students on their performance. Further research proposals and limitations of the study are, moreover, discussed.

  11. System of error detection in the manufacture of garments using artificial vision

    Science.gov (United States)

    Moreno, J. J.; Aguila, A.; Partida, E.; Martinez, C. L.; Morales, O.; Tejeida, R.

    2017-12-01

    A computer vision system is implemented to detect errors in the cutting stage within the manufacturing process of garments in the textile industry. It provides solution to errors within the process that cannot be easily detected by any employee, in addition to significantly increase the speed of quality review. In the textile industry as in many others, quality control is required in manufactured products and this has been carried out manually by means of visual inspection by employees over the years. For this reason, the objective of this project is to design a quality control system using computer vision to identify errors in the cutting stage within the garment manufacturing process to increase the productivity of textile processes by reducing costs.

  12. Comparison of computer workstation with light box for detecting setup errors from portal images

    International Nuclear Information System (INIS)

    Boxwala, Aziz A.; Chaney, Edward L.; Fritsch, Daniel S.; Raghavan, Suraj; Coffey, Christopher S.; Major, Stacey A.; Muller, Keith E.

    1999-01-01

    Purpose: Observer studies were conducted to test the hypothesis that radiation oncologists using a computer workstation for portal image analysis can detect setup errors at least as accurately as when following standard clinical practice of inspecting portal films on a light box. Methods and Materials: In a controlled observer study, nine radiation oncologists used a computer workstation, called PortFolio, to detect setup errors in 40 realistic digitally reconstructed portal radiograph (DRPR) images. PortFolio is a prototype workstation for radiation oncologists to display and inspect digital portal images for setup errors. PortFolio includes tools for image enhancement; alignment of crosshairs, field edges, and anatomic structures on reference and acquired images; measurement of distances and angles; and viewing registered images superimposed on one another. The test DRPRs contained known in-plane translation or rotation errors in the placement of the fields over target regions in the pelvis and head. Test images used in the study were also printed on film for observers to view on a light box and interpret using standard clinical practice. The mean accuracy for error detection for each approach was measured and the results were compared using repeated measures analysis of variance (ANOVA) with the Geisser-Greenhouse test statistic. Results: The results indicate that radiation oncologists participating in this study could detect and quantify in-plane rotation and translation errors more accurately with PortFolio compared to standard clinical practice. Conclusions: Based on the results of this limited study, it is reasonable to conclude that workstations similar to PortFolio can be used efficaciously in clinical practice

  13. Error detection in GPS observations by means of Multi-process models

    DEFF Research Database (Denmark)

    Thomsen, Henrik F.

    2001-01-01

    The main purpose of this article is to present the idea of using Multi-process models as a method of detecting errors in GPS observations. The theory behind Multi-process models, and double differenced phase observations in GPS is presented shortly. It is shown how to model cycle slips in the Mul...

  14. Automatic detection of frequent pronunciation errors made by L2-learners

    NARCIS (Netherlands)

    Truong, K.P.; Neri, A.; Wet, F. de; Cucchiarini, C.; Strik, H.

    2005-01-01

    In this paper, we present an acoustic-phonetic approach to automatic pronunciation error detection. Classifiers using techniques such as Linear Discriminant Analysis and Decision Trees were developed for three sounds that are frequently pronounced incorrectly by L2-learners of Dutch: /a/, /y/ and

  15. Visual acuity measures do not reliably detect childhood refractive error--an epidemiological study.

    Directory of Open Access Journals (Sweden)

    Lisa O'Donoghue

    Full Text Available PURPOSE: To investigate the utility of uncorrected visual acuity measures in screening for refractive error in white school children aged 6-7-years and 12-13-years. METHODS: The Northern Ireland Childhood Errors of Refraction (NICER study used a stratified random cluster design to recruit children from schools in Northern Ireland. Detailed eye examinations included assessment of logMAR visual acuity and cycloplegic autorefraction. Spherical equivalent refractive data from the right eye were used to classify significant refractive error as myopia of at least 1DS, hyperopia as greater than +3.50DS and astigmatism as greater than 1.50DC, whether it occurred in isolation or in association with myopia or hyperopia. RESULTS: Results are presented from 661 white 12-13-year-old and 392 white 6-7-year-old school-children. Using a cut-off of uncorrected visual acuity poorer than 0.20 logMAR to detect significant refractive error gave a sensitivity of 50% and specificity of 92% in 6-7-year-olds and 73% and 93% respectively in 12-13-year-olds. In 12-13-year-old children a cut-off of poorer than 0.20 logMAR had a sensitivity of 92% and a specificity of 91% in detecting myopia and a sensitivity of 41% and a specificity of 84% in detecting hyperopia. CONCLUSIONS: Vision screening using logMAR acuity can reliably detect myopia, but not hyperopia or astigmatism in school-age children. Providers of vision screening programs should be cognisant that where detection of uncorrected hyperopic and/or astigmatic refractive error is an aspiration, current UK protocols will not effectively deliver.

  16. Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

    Science.gov (United States)

    Thomas, Felicity; Signal, Mathew; Harris, Deborah L; Weston, Philip J; Harding, Jane E; Shaw, Geoffrey M; Chase, J Geoffrey

    2014-05-01

    Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia metrics in newborn infants. Data from 155 babies were used. Two timing and 3 BG meter error models (Abbott Optium Xceed, Roche Accu-Chek Inform II, Nova Statstrip) were created using empirical data. Monte-Carlo methods were employed, and each simulation was run 1000 times. Each set of patient data in each simulation had randomly selected timing and/or measurement error added to BG measurements before CGM data were calibrated. The number of hypoglycemic events, duration of hypoglycemia, and hypoglycemic index were then calculated using the CGM data and compared to baseline values. Timing error alone had little effect on hypoglycemia metrics, but measurement error caused substantial variation. Abbott results underreported the number of hypoglycemic events by up to 8 and Roche overreported by up to 4 where the original number reported was 2. Nova results were closest to baseline. Similar trends were observed in the other hypoglycemia metrics. Errors in blood glucose concentration measurements used for calibration of CGM devices can have a clinically important impact on detection of hypoglycemia. If CGM devices are going to be used for assessing hypoglycemia it is important to understand of the impact of these errors on CGM data. © 2014 Diabetes Technology Society.

  17. Efficient Error Detection in Soft Data Fusion for Cooperative Spectrum Sensing

    KAUST Repository

    Saqib Bhatti, Dost Muhammad

    2018-03-18

    The primary objective of cooperative spectrum sensing (CSS) is to determine whether a particular spectrum is occupied by a licensed user or not, so that unlicensed users called secondary users (SUs) can utilize that spectrum, if it is not occupied. For CSS, all SUs report their sensing information through reporting channel to the central base station called fusion center (FC). During transmission, some of the SUs are subjected to fading and shadowing, due to which the overall performance of CSS is degraded. We have proposed an algorithm which uses error detection technique on sensing measurement of all SUs. Each SU is required to re-transmit the sensing data to the FC, if error is detected on it. Our proposed algorithm combines the sensing measurement of limited number of SUs. Using Proposed algorithm, we have achieved the improved probability of detection (PD) and throughput. The simulation results compare the proposed algorithm with conventional scheme.

  18. Periodic Application of Concurrent Error Detection in Processor Array Architectures. PhD. Thesis -

    Science.gov (United States)

    Chen, Paul Peichuan

    1993-01-01

    Processor arrays can provide an attractive architecture for some applications. Featuring modularity, regular interconnection and high parallelism, such arrays are well-suited for VLSI/WSI implementations, and applications with high computational requirements, such as real-time signal processing. Preserving the integrity of results can be of paramount importance for certain applications. In these cases, fault tolerance should be used to ensure reliable delivery of a system's service. One aspect of fault tolerance is the detection of errors caused by faults. Concurrent error detection (CED) techniques offer the advantage that transient and intermittent faults may be detected with greater probability than with off-line diagnostic tests. Applying time-redundant CED techniques can reduce hardware redundancy costs. However, most time-redundant CED techniques degrade a system's performance.

  19. Data Reconciliation and Gross Error Detection for Troubleshooting of Ammonia Reactor

    Directory of Open Access Journals (Sweden)

    Adhi Tri Partono

    2018-01-01

    Full Text Available Data reconciliation (DR and gross error detection are two common tools used in industry to provide accurate and reliable data, which is useful to analyse plant performance and basis for troubleshooting. DR techniques improve the accuracy of measurements by using redundancies in material and energy balances. This provides reliable information that could help decision making regarding plant operation, which potentially leads to financial benefit. This paper presents the utilization of plant data to perform troubleshooting of ammonia reactor, in particular the profile of catalyst activity. Bad plant data are collected and then analysed using DR to produces reconciled data, which could be used to detect and identify the gross error measurements. The input data for DR and gross error detection were gathered from Aspen HYSYS V8.8 simulations by modelling the single-bed ammonia reactor. The result presents that bad plant data could define actual system condition such as gross error measurements in normal condition or catalyst activity problem. Both conditions are modelled by DR to indicate actual system condition using statistical analysis and to perform troubleshooting. Appropriate troubleshooting could save time and provide financial benefits by avoiding wrong accusation of system problem, specifically in ammonia reactor evaluated in this paper.

  20. Improved assessment of multiple sclerosis lesion segmentation agreement via detection and outline error estimates

    Directory of Open Access Journals (Sweden)

    Wack David S

    2012-07-01

    Full Text Available Abstract Background Presented is the method “Detection and Outline Error Estimates” (DOEE for assessing rater agreement in the delineation of multiple sclerosis (MS lesions. The DOEE method divides operator or rater assessment into two parts: 1 Detection Error (DE -- rater agreement in detecting the same regions to mark, and 2 Outline Error (OE -- agreement of the raters in outlining of the same lesion. Methods DE, OE and Similarity Index (SI values were calculated for two raters tested on a set of 17 fluid-attenuated inversion-recovery (FLAIR images of patients with MS. DE, OE, and SI values were tested for dependence with mean total area (MTA of the raters' Region of Interests (ROIs. Results When correlated with MTA, neither DE (ρ = .056, p=.83 nor the ratio of OE to MTA (ρ = .23, p=.37, referred to as Outline Error Rate (OER, exhibited significant correlation. In contrast, SI is found to be strongly correlated with MTA (ρ = .75, p  Conclusions The DE and OER indices are proposed as a better method than SI for comparing rater agreement of ROIs, which also provide specific information for raters to improve their agreement.

  1. Data Error Detection and Recovery in Embedded Systems: a Literature Review

    Directory of Open Access Journals (Sweden)

    Venu Babu Thati

    2017-06-01

    Full Text Available This paper presents a literature review on data flow error detection and recovery techniques in embedded systems. In recent years, embedded systems are being used more and more in an enormous number of applications from small mobile device to big medical devices. At the same time, it is becoming important for embedded developers to make embedded systems fault-tolerant. To make embedded systems fault-tolerant, error detection and recovery mechanisms are effective techniques to take into consideration. Fault tolerance can be achieved by using both hardware and software techniques. This literature review focuses on software-based techniques since hardware-based techniques need extra hardware and are an extra investment in cost per product. Whereas, software-based techniques needed no or limited hardware. A review on various existing data flow error detection and error recovery techniques is given along with their strengths and weaknesses. Such an information is useful to identify the better techniques among the others.

  2. Predictive error detection in pianists: A combined ERP and motion capture study

    Directory of Open Access Journals (Sweden)

    Clemens eMaidhof

    2013-09-01

    Full Text Available Performing a piece of music involves the interplay of several cognitive and motor processes and requires extensive training to achieve a high skill level. However, even professional musicians commit errors occasionally. Previous event-related potential (ERP studies have investigated the neurophysiological correlates of pitch errors during piano performance, and reported pre-error negativity already occurring approximately 70-100 ms before the error had been committed and audible. It was assumed that this pre-error negativity reflects predictive control processes that compare predicted consequences with actual consequences of one’s own actions. However, in previous investigations, correct and incorrect pitch events were confounded by their different tempi. In addition, no data about the underlying movements were available. In the present study, we exploratively recorded the ERPs and 3D movement data of pianists’ fingers simultaneously while they performed fingering exercises from memory. Results showed a pre-error negativity for incorrect keystrokes when both correct and incorrect keystrokes were performed with comparable tempi. Interestingly, even correct notes immediately preceding erroneous keystrokes elicited a very similar negativity. In addition, we explored the possibility of computing ERPs time-locked to a kinematic landmark in the finger motion trajectories defined by when a finger makes initial contact with the key surface, that is, at the onset of tactile feedback. Results suggest that incorrect notes elicited a small difference after the onset of tactile feedback, whereas correct notes preceding incorrect ones elicited negativity before the onset of tactile feedback. The results tentatively suggest that tactile feedback plays an important role in error-monitoring during piano performance, because the comparison between predicted and actual sensory (tactile feedback may provide the information necessary for the detection of an

  3. The Affect of Varying Arousal Methods Upon Vigilance and Error Detection in an Automated Command and Control Environment

    National Research Council Canada - National Science Library

    Langhals, Brent

    2001-01-01

    .... The study suggests that by continuously applying arousal stimuli, subjects would retain initially high vigilance levels thereby avoiding the vigilance decrement phenomenon and improving error detection...

  4. Invariance of the bit error rate in the ancilla-assisted homodyne detection

    International Nuclear Information System (INIS)

    Yoshida, Yuhsuke; Takeoka, Masahiro; Sasaki, Masahide

    2010-01-01

    We investigate the minimum achievable bit error rate of the discrimination of binary coherent states with the help of arbitrary ancillary states. We adopt homodyne measurement with a common phase of the local oscillator and classical feedforward control. After one ancillary state is measured, its outcome is referred to the preparation of the next ancillary state and the tuning of the next mixing with the signal. It is shown that the minimum bit error rate of the system is invariant under the following operations: feedforward control, deformations, and introduction of any ancillary state. We also discuss the possible generalization of the homodyne detection scheme.

  5. Error Detection, Factorization and Correction for Multi-View Scene Reconstruction from Aerial Imagery

    Energy Technology Data Exchange (ETDEWEB)

    Hess-Flores, Mauricio [Univ. of California, Davis, CA (United States)

    2011-11-10

    Scene reconstruction from video sequences has become a prominent computer vision research area in recent years, due to its large number of applications in fields such as security, robotics and virtual reality. Despite recent progress in this field, there are still a number of issues that manifest as incomplete, incorrect or computationally-expensive reconstructions. The engine behind achieving reconstruction is the matching of features between images, where common conditions such as occlusions, lighting changes and texture-less regions can all affect matching accuracy. Subsequent processes that rely on matching accuracy, such as camera parameter estimation, structure computation and non-linear parameter optimization, are also vulnerable to additional sources of error, such as degeneracies and mathematical instability. Detection and correction of errors, along with robustness in parameter solvers, are a must in order to achieve a very accurate final scene reconstruction. However, error detection is in general difficult due to the lack of ground-truth information about the given scene, such as the absolute position of scene points or GPS/IMU coordinates for the camera(s) viewing the scene. In this dissertation, methods are presented for the detection, factorization and correction of error sources present in all stages of a scene reconstruction pipeline from video, in the absence of ground-truth knowledge. Two main applications are discussed. The first set of algorithms derive total structural error measurements after an initial scene structure computation and factorize errors into those related to the underlying feature matching process and those related to camera parameter estimation. A brute-force local correction of inaccurate feature matches is presented, as well as an improved conditioning scheme for non-linear parameter optimization which applies weights on input parameters in proportion to estimated camera parameter errors. Another application is in

  6. Online track detection in triggerless mode for INO

    Science.gov (United States)

    Jain, A.; Padmini, S.; Joseph, A. N.; Mahesh, P.; Preetha, N.; Behere, A.; Sikder, S. S.; Majumder, G.; Behera, S. P.

    2018-03-01

    The India based Neutrino Observatory (INO) is a proposed particle physics research project to study the atmospheric neutrinos. INO-Iron Calorimeter (ICAL) will consist of 28,800 detectors having 3.6 million electronic channels expected to activate with 100 Hz single rate, producing data at a rate of 3 GBps. Data collected contains a few real hits generated by muon tracks and the remaining noise-induced spurious hits. Estimated reduction factor after filtering out data of interest from generated data is of the order of 103. This makes trigger generation critical for efficient data collection and storage. Trigger is generated by detecting coincidence across multiple channels satisfying trigger criteria, within a small window of 200 ns in the trigger region. As the probability of neutrino interaction is very low, track detection algorithm has to be efficient and fast enough to process 5 × 106 events-candidates/s without introducing significant dead time, so that not even a single neutrino event is missed out. A hardware based trigger system is presently proposed for on-line track detection considering stringent timing requirements. Though the trigger system can be designed with scalability, a lot of hardware devices and interconnections make it a complex and expensive solution with limited flexibility. A software based track detection approach working on the hit information offers an elegant solution with possibility of varying trigger criteria for selecting various potentially interesting physics events. An event selection approach for an alternative triggerless readout scheme has been developed. The algorithm is mathematically simple, robust and parallelizable. It has been validated by detecting simulated muon events for energies of the range of 1 GeV-10 GeV with 100% efficiency at a processing rate of 60 μs/event on a 16 core machine. The algorithm and result of a proof-of-concept for its faster implementation over multiple cores is presented. The paper also

  7. Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

    Science.gov (United States)

    Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

    2014-01-01

    Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

  8. Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

    Science.gov (United States)

    Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

    2010-11-01

    The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

  9. The fundamental attribution error in detecting deception: the boy-who-cried-wolf effect.

    Science.gov (United States)

    O'Sullivan, Maureen

    2003-10-01

    Most people are unable to detect accurately when others are lying. Many explanations for this inability have been suggested but the cognitive heuristics involved in lie detection have received little attention. The present study offers evidence from two experiments, based on two different groups of observers, judging two different kinds of lies, presented in two different testing situations, that the fundamental attribution error significantly undermines the ability to detect honesty and deception accurately. Trait judgments of trustworthiness were highly correlated with state judgments of truthfulness, leading, as predicted, to positive correlations with honest detection accuracy and negative correlations with deception detection accuracy. More accurate lie detectors were significantly more likely than less accurate lie detectors to separate state and trait judgments of honesty. The effect of other biases, such as the halo effect and the truthfulness bias, also are examined. Implications for future research and practice are discussed.

  10. Chaos characteristics and least squares support vector machines based online pipeline small leakages detection

    International Nuclear Information System (INIS)

    Liu, Jinhai; Su, Hanguang; Ma, Yanjuan; Wang, Gang; Wang, Yuan; Zhang, Kun

    2016-01-01

    Small leakages are severe threats to the long distance pipeline transportation. An online small leakage detection method based on chaos characteristics and Least Squares Support Vector Machines (LS-SVMs) is proposed in this paper. For the first time, the relationship between the chaos characteristics of pipeline inner pressures and the small leakages is investigated and applied in the pipeline detection method. Firstly, chaos in the pipeline inner pressure is found. Relevant chaos characteristics are estimated by the nonlinear time series analysis package (TISEAN). Then LS-SVM with a hybrid kernel is built and named as hybrid kernel LS-SVM (HKLS-SVM). It is applied to analyze the chaos characteristics and distinguish the negative pressure waves (NPWs) caused by small leaks. A new leak location method is also expounded. Finally, data of the chaotic Logistic-Map system is used in the simulation. A comparison between HKLS-SVM and other methods, in terms of the identification accuracy and computing efficiency, is made. The simulation result shows that HKLS-SVM gets the best performance and is effective in error analysis of chaotic systems. When real pipeline data is used in the test, the ultimate identification accuracy of HKLS-SVM reaches 97.38% and the position accuracy is 99.28%, indicating that the method proposed in this paper has good performance in detecting and locating small pipeline leaks.

  11. ac driving amplitude dependent systematic error in scanning Kelvin probe microscope measurements: Detection and correction

    International Nuclear Information System (INIS)

    Wu Yan; Shannon, Mark A.

    2006-01-01

    The dependence of the contact potential difference (CPD) reading on the ac driving amplitude in scanning Kelvin probe microscope (SKPM) hinders researchers from quantifying true material properties. We show theoretically and demonstrate experimentally that an ac driving amplitude dependence in the SKPM measurement can come from a systematic error, and it is common for all tip sample systems as long as there is a nonzero tracking error in the feedback control loop of the instrument. We further propose a methodology to detect and to correct the ac driving amplitude dependent systematic error in SKPM measurements. The true contact potential difference can be found by applying a linear regression to the measured CPD versus one over ac driving amplitude data. Two scenarios are studied: (a) when the surface being scanned by SKPM is not semiconducting and there is an ac driving amplitude dependent systematic error; (b) when a semiconductor surface is probed and asymmetric band bending occurs when the systematic error is present. Experiments are conducted using a commercial SKPM and CPD measurement results of two systems: platinum-iridium/gap/gold and platinum-iridium/gap/thermal oxide/silicon are discussed

  12. Tests for detecting overdispersion in models with measurement error in covariates.

    Science.gov (United States)

    Yang, Yingsi; Wong, Man Yu

    2015-11-30

    Measurement error in covariates can affect the accuracy in count data modeling and analysis. In overdispersion identification, the true mean-variance relationship can be obscured under the influence of measurement error in covariates. In this paper, we propose three tests for detecting overdispersion when covariates are measured with error: a modified score test and two score tests based on the proposed approximate likelihood and quasi-likelihood, respectively. The proposed approximate likelihood is derived under the classical measurement error model, and the resulting approximate maximum likelihood estimator is shown to have superior efficiency. Simulation results also show that the score test based on approximate likelihood outperforms the test based on quasi-likelihood and other alternatives in terms of empirical power. By analyzing a real dataset containing the health-related quality-of-life measurements of a particular group of patients, we demonstrate the importance of the proposed methods by showing that the analyses with and without measurement error correction yield significantly different results. Copyright © 2015 John Wiley & Sons, Ltd.

  13. The good, the bad and the outliers: automated detection of errors and outliers from groundwater hydrographs

    Science.gov (United States)

    Peterson, Tim J.; Western, Andrew W.; Cheng, Xiang

    2018-03-01

    Suspicious groundwater-level observations are common and can arise for many reasons ranging from an unforeseen biophysical process to bore failure and data management errors. Unforeseen observations may provide valuable insights that challenge existing expectations and can be deemed outliers, while monitoring and data handling failures can be deemed errors, and, if ignored, may compromise trend analysis and groundwater model calibration. Ideally, outliers and errors should be identified but to date this has been a subjective process that is not reproducible and is inefficient. This paper presents an approach to objectively and efficiently identify multiple types of errors and outliers. The approach requires only the observed groundwater hydrograph, requires no particular consideration of the hydrogeology, the drivers (e.g. pumping) or the monitoring frequency, and is freely available in the HydroSight toolbox. Herein, the algorithms and time-series model are detailed and applied to four observation bores with varying dynamics. The detection of outliers was most reliable when the observation data were acquired quarterly or more frequently. Outlier detection where the groundwater-level variance is nonstationary or the absolute trend increases rapidly was more challenging, with the former likely to result in an under-estimation of the number of outliers and the latter an overestimation in the number of outliers.

  14. One-Class Classification-Based Real-Time Activity Error Detection in Smart Homes.

    Science.gov (United States)

    Das, Barnan; Cook, Diane J; Krishnan, Narayanan C; Schmitter-Edgecombe, Maureen

    2016-08-01

    Caring for individuals with dementia is frequently associated with extreme physical and emotional stress, which often leads to depression. Smart home technology and advances in machine learning techniques can provide innovative solutions to reduce caregiver burden. One key service that caregivers provide is prompting individuals with memory limitations to initiate and complete daily activities. We hypothesize that sensor technologies combined with machine learning techniques can automate the process of providing reminder-based interventions. The first step towards automated interventions is to detect when an individual faces difficulty with activities. We propose machine learning approaches based on one-class classification that learn normal activity patterns. When we apply these classifiers to activity patterns that were not seen before, the classifiers are able to detect activity errors, which represent potential prompt situations. We validate our approaches on smart home sensor data obtained from older adult participants, some of whom faced difficulties performing routine activities and thus committed errors.

  15. Benchmark test cases for evaluation of computer-based methods for detection of setup errors: realistic digitally reconstructed electronic portal images with known setup errors

    International Nuclear Information System (INIS)

    Fritsch, Daniel S.; Raghavan, Suraj; Boxwala, Aziz; Earnhart, Jon; Tracton, Gregg; Cullip, Timothy; Chaney, Edward L.

    1997-01-01

    Purpose: The purpose of this investigation was to develop methods and software for computing realistic digitally reconstructed electronic portal images with known setup errors for use as benchmark test cases for evaluation and intercomparison of computer-based methods for image matching and detecting setup errors in electronic portal images. Methods and Materials: An existing software tool for computing digitally reconstructed radiographs was modified to compute simulated megavoltage images. An interface was added to allow the user to specify which setup parameter(s) will contain computer-induced random and systematic errors in a reference beam created during virtual simulation. Other software features include options for adding random and structured noise, Gaussian blurring to simulate geometric unsharpness, histogram matching with a 'typical' electronic portal image, specifying individual preferences for the appearance of the 'gold standard' image, and specifying the number of images generated. The visible male computed tomography data set from the National Library of Medicine was used as the planning image. Results: Digitally reconstructed electronic portal images with known setup errors have been generated and used to evaluate our methods for automatic image matching and error detection. Any number of different sets of test cases can be generated to investigate setup errors involving selected setup parameters and anatomic volumes. This approach has proved to be invaluable for determination of error detection sensitivity under ideal (rigid body) conditions and for guiding further development of image matching and error detection methods. Example images have been successfully exported for similar use at other sites. Conclusions: Because absolute truth is known, digitally reconstructed electronic portal images with known setup errors are well suited for evaluation of computer-aided image matching and error detection methods. High-quality planning images, such as

  16. From drafting guideline to error detection: Automating style checking for legislative texts

    OpenAIRE

    Höfler Stefan; Sugisaki Kyoko

    2012-01-01

    This paper reports on the development of methods for the automated detection of violations of style guidelines for legislative texts, and their implementation in a prototypical tool. To this aim, the approach of error modelling employed in automated style checkers for technical writing is enhanced to meet the requirements of legislative editing. The paper identifies and discusses the two main sets of challenges that have to be tackled in this process: (i) the provision of domain-specific NLP ...

  17. Impact of Channel Estimation Errors on Multiuser Detection via the Replica Method

    Directory of Open Access Journals (Sweden)

    Li Husheng

    2005-01-01

    Full Text Available For practical wireless DS-CDMA systems, channel estimation is imperfect due to noise and interference. In this paper, the impact of channel estimation errors on multiuser detection (MUD is analyzed under the framework of the replica method. System performance is obtained in the large system limit for optimal MUD, linear MUD, and turbo MUD, and is validated by numerical results for finite systems.

  18. Continuous glucose monitoring in newborn infants: how do errors in calibration measurements affect detected hypoglycemia?

    OpenAIRE

    Thomas, Felicity Louise; Signal, Mathew; Harris, Deborah L.; Weston, Philip J.; Harding, Jane E.; Shaw, Geoffrey M.; Chase, J. Geoffrey

    2014-01-01

    Neonatal hypoglycemia is common and can cause serious brain injury. Continuous glucose monitoring (CGM) could improve hypoglycemia detection, while reducing blood glucose (BG) measurements. Calibration algorithms use BG measurements to convert sensor signals into CGM data. Thus, inaccuracies in calibration BG measurements directly affect CGM values and any metrics calculated from them. The aim was to quantify the effect of timing delays and calibration BG measurement errors on hypoglycemia me...

  19. Faces in places: humans and machines make similar face detection errors.

    Directory of Open Access Journals (Sweden)

    Bernard Marius 't Hart

    Full Text Available The human visual system seems to be particularly efficient at detecting faces. This efficiency sometimes comes at the cost of wrongfully seeing faces in arbitrary patterns, including famous examples such as a rock configuration on Mars or a toast's roast patterns. In machine vision, face detection has made considerable progress and has become a standard feature of many digital cameras. The arguably most wide-spread algorithm for such applications ("Viola-Jones" algorithm achieves high detection rates at high computational efficiency. To what extent do the patterns that the algorithm mistakenly classifies as faces also fool humans? We selected three kinds of stimuli from real-life, first-person perspective movies based on the algorithm's output: correct detections ("real faces", false positives ("illusory faces" and correctly rejected locations ("non faces". Observers were shown pairs of these for 20 ms and had to direct their gaze to the location of the face. We found that illusory faces were mistaken for faces more frequently than non faces. In addition, rotation of the real face yielded more errors, while rotation of the illusory face yielded fewer errors. Using colored stimuli increases overall performance, but does not change the pattern of results. When replacing the eye movement by a manual response, however, the preference for illusory faces over non faces disappeared. Taken together, our data show that humans make similar face-detection errors as the Viola-Jones algorithm, when directing their gaze to briefly presented stimuli. In particular, the relative spatial arrangement of oriented filters seems of relevance. This suggests that efficient face detection in humans is likely to be pre-attentive and based on rather simple features as those encoded in the early visual system.

  20. Detection of treatment setup errors between two CT scans for patients with head and neck cancer

    International Nuclear Information System (INIS)

    Ezzell, Leah C.; Hansen, Eric K.; Quivey, Jeanne M.; Xia Ping

    2007-01-01

    Accuracy of treatment setup for head and neck patients undergoing intensity-modulated radiation therapy is of paramount importance. The conventional method using orthogonal portal images can only detect translational setup errors while the most frequent setup errors for head and neck patients could be rotational errors. With the rapid development of image-guided radiotherapy, three-dimensional images are readily acquired and can be used to detect both translational and rotational setup errors. The purpose of this study is to determine the significance of rotational variations between two planning CT scans acquired for each of eight head and neck patients, who experienced substantial weight loss or tumor shrinkage. To this end, using a rigid body assumption, we developed an in-house computer program that utilizes matrix transformations to align point bony landmarks with an incremental best-fit routine. The program returns the quantified translational and rotational shifts needed to align the scans of each patient. The program was tested using a phantom for a set of known translational and rotational shifts. For comparison, a commercial treatment planning system was used to register the two CT scans and estimate the translational errors for these patients. For the eight patients, we found that the average magnitudes and standard deviations of the rotational shifts about the transverse, anterior-posterior, and longitudinal axes were 1.7±2.3 deg., 0.8±0.7 deg., and 1.8±1.1 deg., respectively. The average magnitudes and standard deviations of the translational shifts were 2.5±2.6 mm, 2.9±2.8 mm, 2.7±1.7 mm while the differences detected between our program and the CT-CT fusion method were 1.8±1.3 mm, 3.3±5.4 mm, and 3.0±3.4 mm in the left-right, anterior-posterior, and superior-inferior directions, respectively. A trend of larger rotational errors resulting in larger translational differences between the two methods was observed. In conclusion, conventional

  1. Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors

    Directory of Open Access Journals (Sweden)

    Claire E. Bulgin

    2018-04-01

    Full Text Available Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR. We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics, cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance. Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.

  2. Detecting Role Errors in the Gene Hierarchy of the NCI Thesaurus

    Directory of Open Access Journals (Sweden)

    Yehoshua Perl

    2008-01-01

    Full Text Available Gene terminologies are playing an increasingly important role in the ever-growing field of genomic research. While errors in large, complex terminologies are inevitable, gene terminologies are even more susceptible to them due to the rapid growth of genomic knowledge and the nature of its discovery. It is therefore very important to establish quality- assurance protocols for such genomic-knowledge repositories. Different kinds of terminologies oftentimes require auditing methodologies adapted to their particular structures. In light of this, an auditing methodology tailored to the characteristics of the NCI Thesaurus’s (NCIT’s Gene hierarchy is presented. The Gene hierarchy is of particular interest to the NCIT’s designers due to the primary role of genomics in current cancer research. This multiphase methodology focuses on detecting role-errors, such as missing roles or roles with incorrect or incomplete target structures, occurring within that hierarchy. The methodology is based on two kinds of abstraction networks, called taxonomies, that highlight the role distribution among concepts within the IS-A (subsumption hierarchy. These abstract views tend to highlight portions of the hierarchy having a higher concentration of errors. The errors found during an application of the methodology

  3. Detecting errors and anomalies in computerized materials control and accountability databases

    International Nuclear Information System (INIS)

    Whiteson, R.; Hench, K.; Yarbro, T.; Baumgart, C.

    1998-01-01

    The Automated MC and A Database Assessment project is aimed at improving anomaly and error detection in materials control and accountability (MC and A) databases and increasing confidence in the data that they contain. Anomalous data resulting in poor categorization of nuclear material inventories greatly reduces the value of the database information to users. Therefore it is essential that MC and A data be assessed periodically for anomalies or errors. Anomaly detection can identify errors in databases and thus provide assurance of the integrity of data. An expert system has been developed at Los Alamos National Laboratory that examines these large databases for anomalous or erroneous data. For several years, MC and A subject matter experts at Los Alamos have been using this automated system to examine the large amounts of accountability data that the Los Alamos Plutonium Facility generates. These data are collected and managed by the Material Accountability and Safeguards System, a near-real-time computerized nuclear material accountability and safeguards system. This year they have expanded the user base, customizing the anomaly detector for the varying requirements of different groups of users. This paper describes the progress in customizing the expert systems to the needs of the users of the data and reports on their results

  4. The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy

    International Nuclear Information System (INIS)

    Gopan, Olga; Zeng, Jing; Novak, Avrey; Nyflot, Matthew; Ford, Eric

    2016-01-01

    Purpose: The pretreatment physics plan review is a standard tool for ensuring treatment quality. Studies have shown that the majority of errors in radiation oncology originate in treatment planning, which underscores the importance of the pretreatment physics plan review. This quality assurance measure is fundamentally important and central to the safety of patients and the quality of care that they receive. However, little is known about its effectiveness. The purpose of this study was to analyze reported incidents to quantify the effectiveness of the pretreatment physics plan review with the goal of improving it. Methods: This study analyzed 522 potentially severe or critical near-miss events within an institutional incident learning system collected over a three-year period. Of these 522 events, 356 originated at a workflow point that was prior to the pretreatment physics plan review. The remaining 166 events originated after the pretreatment physics plan review and were not considered in the study. The applicable 356 events were classified into one of the three categories: (1) events detected by the pretreatment physics plan review, (2) events not detected but “potentially detectable” by the physics review, and (3) events “not detectable” by the physics review. Potentially detectable events were further classified by which specific checks performed during the pretreatment physics plan review detected or could have detected the event. For these events, the associated specific check was also evaluated as to the possibility of automating that check given current data structures. For comparison, a similar analysis was carried out on 81 events from the international SAFRON radiation oncology incident learning system. Results: Of the 356 applicable events from the institutional database, 180/356 (51%) were detected or could have been detected by the pretreatment physics plan review. Of these events, 125 actually passed through the physics review; however

  5. The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Gopan, Olga; Zeng, Jing; Novak, Avrey; Nyflot, Matthew; Ford, Eric, E-mail: eford@uw.edu [Department of Radiation Oncology, University of Washington Medical Center, 1959 NE Pacific Street, Box 356043, Seattle, Washington 98195 (United States)

    2016-09-15

    Purpose: The pretreatment physics plan review is a standard tool for ensuring treatment quality. Studies have shown that the majority of errors in radiation oncology originate in treatment planning, which underscores the importance of the pretreatment physics plan review. This quality assurance measure is fundamentally important and central to the safety of patients and the quality of care that they receive. However, little is known about its effectiveness. The purpose of this study was to analyze reported incidents to quantify the effectiveness of the pretreatment physics plan review with the goal of improving it. Methods: This study analyzed 522 potentially severe or critical near-miss events within an institutional incident learning system collected over a three-year period. Of these 522 events, 356 originated at a workflow point that was prior to the pretreatment physics plan review. The remaining 166 events originated after the pretreatment physics plan review and were not considered in the study. The applicable 356 events were classified into one of the three categories: (1) events detected by the pretreatment physics plan review, (2) events not detected but “potentially detectable” by the physics review, and (3) events “not detectable” by the physics review. Potentially detectable events were further classified by which specific checks performed during the pretreatment physics plan review detected or could have detected the event. For these events, the associated specific check was also evaluated as to the possibility of automating that check given current data structures. For comparison, a similar analysis was carried out on 81 events from the international SAFRON radiation oncology incident learning system. Results: Of the 356 applicable events from the institutional database, 180/356 (51%) were detected or could have been detected by the pretreatment physics plan review. Of these events, 125 actually passed through the physics review; however

  6. SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

    International Nuclear Information System (INIS)

    Kalet, A; Phillips, M; Gennari, J

    2014-01-01

    Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the

  7. SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

    Energy Technology Data Exchange (ETDEWEB)

    Kalet, A; Phillips, M; Gennari, J [UniversityWashington, Seattle, WA (United States)

    2014-06-01

    Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the

  8. A study of redundancy management strategy for tetrad strap-down inertial systems. [error detection codes

    Science.gov (United States)

    Hruby, R. J.; Bjorkman, W. S.; Schmidt, S. F.; Carestia, R. A.

    1979-01-01

    Algorithms were developed that attempt to identify which sensor in a tetrad configuration has experienced a step failure. An algorithm is also described that provides a measure of the confidence with which the correct identification was made. Experimental results are presented from real-time tests conducted on a three-axis motion facility utilizing an ortho-skew tetrad strapdown inertial sensor package. The effects of prediction errors and of quantization on correct failure identification are discussed as well as an algorithm for detecting second failures through prediction.

  9. An Investigation into Soft Error Detection Efficiency at Operating System Level

    OpenAIRE

    Asghari, Seyyed Amir; Kaynak, Okyay; Taheri, Hassan

    2014-01-01

    Electronic equipment operating in harsh environments such as space is subjected to a range of threats. The most important of these is radiation that gives rise to permanent and transient errors on microelectronic components. The occurrence rate of transient errors is significantly more than permanent errors. The transient errors, or soft errors, emerge in two formats: control flow errors (CFEs) and data errors. Valuable research results have already appeared in literature at hardware and soft...

  10. Characterizing a four-qubit planar lattice for arbitrary error detection

    Science.gov (United States)

    Chow, Jerry M.; Srinivasan, Srikanth J.; Magesan, Easwar; Córcoles, A. D.; Abraham, David W.; Gambetta, Jay M.; Steffen, Matthias

    2015-05-01

    Quantum error correction will be a necessary component towards realizing scalable quantum computers with physical qubits. Theoretically, it is possible to perform arbitrarily long computations if the error rate is below a threshold value. The two-dimensional surface code permits relatively high fault-tolerant thresholds at the ~1% level, and only requires a latticed network of qubits with nearest-neighbor interactions. Superconducting qubits have continued to steadily improve in coherence, gate, and readout fidelities, to become a leading candidate for implementation into larger quantum networks. Here we describe characterization experiments and calibration of a system of four superconducting qubits arranged in a planar lattice, amenable to the surface code. Insights into the particular qubit design and comparison between simulated parameters and experimentally determined parameters are given. Single- and two-qubit gate tune-up procedures are described and results for simultaneously benchmarking pairs of two-qubit gates are given. All controls are eventually used for an arbitrary error detection protocol described in separate work [Corcoles et al., Nature Communications, 6, 2015].

  11. Robust Online State of Charge Estimation of Lithium-Ion Battery Pack Based on Error Sensitivity Analysis

    Directory of Open Access Journals (Sweden)

    Ting Zhao

    2015-01-01

    Full Text Available Accurate and reliable state of charge (SOC estimation is a key enabling technique for large format lithium-ion battery pack due to its vital role in battery safety and effective management. This paper tries to make three contributions to existing literatures through robust algorithms. (1 Observer based SOC estimation error model is established, where the crucial parameters on SOC estimation accuracy are determined by quantitative analysis, being a basis for parameters update. (2 The estimation method for a battery pack in which the inconsistency of cells is taken into consideration is proposed, ensuring all batteries’ SOC ranging from 0 to 1, effectively avoiding the battery overcharged/overdischarged. Online estimation of the parameters is also presented in this paper. (3 The SOC estimation accuracy of the battery pack is verified using the hardware-in-loop simulation platform. The experimental results at various dynamic test conditions, temperatures, and initial SOC difference between two cells demonstrate the efficacy of the proposed method.

  12. Pressurized water reactor monitoring. Study of detection, diagnostic and estimation methods (least error squares and filtering)

    International Nuclear Information System (INIS)

    Gillet, M.

    1986-07-01

    This thesis presents a study for the surveillance of the ''primary coolant circuit inventory monitoring'' of a pressurized water reactor. A reference model is developed in view of an automatic system ensuring detection and diagnostic in real time. The methods used for the present application are statistical tests and a method related to pattern recognition. The estimation of failures detected, difficult owing to the non-linearity of the problem, is treated by the least error squares method of the predictor or corrector type, and by filtering. It is in this frame that a new optimized method with superlinear convergence is developed, and that a segmented linearization of the model is introduced, in view of a multiple filtering [fr

  13. Conflict monitoring in speech processing : An fMRI study of error detection in speech production and perception

    NARCIS (Netherlands)

    Gauvin, Hanna; De Baene, W.; Brass, Marcel; Hartsuiker, Robert

    2016-01-01

    To minimize the number of errors in speech, and thereby facilitate communication, speech is monitored before articulation. It is, however, unclear at which level during speech production monitoring takes place, and what mechanisms are used to detect and correct errors. The present study investigated

  14. Online Least Squares One-Class Support Vector Machines-Based Abnormal Visual Event Detection

    Directory of Open Access Journals (Sweden)

    Tian Wang

    2013-12-01

    Full Text Available The abnormal event detection problem is an important subject in real-time video surveillance. In this paper, we propose a novel online one-class classification algorithm, online least squares one-class support vector machine (online LS-OC-SVM, combined with its sparsified version (sparse online LS-OC-SVM. LS-OC-SVM extracts a hyperplane as an optimal description of training objects in a regularized least squares sense. The online LS-OC-SVM learns a training set with a limited number of samples to provide a basic normal model, then updates the model through remaining data. In the sparse online scheme, the model complexity is controlled by the coherence criterion. The online LS-OC-SVM is adopted to handle the abnormal event detection problem. Each frame of the video is characterized by the covariance matrix descriptor encoding the moving information, then is classified into a normal or an abnormal frame. Experiments are conducted, on a two-dimensional synthetic distribution dataset and a benchmark video surveillance dataset, to demonstrate the promising results of the proposed online LS-OC-SVM method.

  15. Fraud detections for online businesses: a perspective from blockchain technology

    OpenAIRE

    Cai, Yuanfeng; Zhu, Dan

    2016-01-01

    Background: The reputation system has been designed as an effective mechanism to reduce risks associated with online shopping for customers. However, it is vulnerable to rating fraud. Some raters may inject unfairly high or low ratings to the system so as to promote their own products or demote their competitors. Method: This study explores the rating fraud by differentiating the subjective fraud from objective fraud. Then it discusses the effectiveness of blockchain technology in objective f...

  16. Estimation of the limit of detection with a bootstrap-derived standard error by a partly non-parametric approach. Application to HPLC drug assays

    DEFF Research Database (Denmark)

    Linnet, Kristian

    2005-01-01

    Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors......Bootstrap, HPLC, limit of blank, limit of detection, non-parametric statistics, type I and II errors...

  17. Capillary electrophoresis microchip coupled with on-line chemiluminescence detection

    International Nuclear Information System (INIS)

    Su Rongguo; Lin Jinming; Qu Feng; Chen Zhifeng; Gao Yunhua; Yamada, Masaaki

    2004-01-01

    In the present work, chemiluminescence detection was integrated with capillary electrophoresis microchip. The microchip was designed on the principle of flow-injection chemiluminescence system and capillary electrophoresis. It has three main channels, five reservoirs and a detection cell. As model samples, dopamine and catechol were separated and detected using a permanganate chemiluminescent system on the prepared microchip. The samples were electrokinetically injected into the double-T cross section, separated in the separation channel, and then oxidized by chemiluminescent reagent delivered by a home-made micropump to produce light in the detection cell. The electroosmotic flow could be smoothly coupled with the micropump flow. The detection limits for dopamine and catechol were 20.0 and 10.0 μM, respectively. Successful separation and detection of dopamine and catechol demonstrated the distinct advantages of integration of chemiluminescent detection on a microchip for rapid and sensitive analysis

  18. MO-FG-202-07: Real-Time EPID-Based Detection Metric For VMAT Delivery Errors

    International Nuclear Information System (INIS)

    Passarge, M; Fix, M K; Manser, P; Stampanoni, M F M; Siebers, J V

    2016-01-01

    Purpose: To create and test an accurate EPID-frame-based VMAT QA metric to detect gross dose errors in real-time and to provide information about the source of error. Methods: A Swiss cheese model was created for an EPID-based real-time QA process. The system compares a treatmentplan- based reference set of EPID images with images acquired over each 2° gantry angle interval. The metric utilizes a sequence of independent consecutively executed error detection Methods: a masking technique that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment to quantify rotation, scaling and translation; standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each test were determined. For algorithm testing, twelve different types of errors were selected to modify the original plan. Corresponding predictions for each test case were generated, which included measurement-based noise. Each test case was run multiple times (with different noise per run) to assess the ability to detect introduced errors. Results: Averaged over five test runs, 99.1% of all plan variations that resulted in patient dose errors were detected within 2° and 100% within 4° (∼1% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 91.5% were detected by the system within 2°. Based on the type of method that detected the error, determination of error sources was achieved. Conclusion: An EPID-based during-treatment error detection system for VMAT deliveries was successfully designed and tested. The system utilizes a sequence of methods to identify and prevent gross treatment delivery errors. The system was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of errors in real-time and indicate the error

  19. MO-FG-202-07: Real-Time EPID-Based Detection Metric For VMAT Delivery Errors

    Energy Technology Data Exchange (ETDEWEB)

    Passarge, M; Fix, M K; Manser, P [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern (Switzerland); Stampanoni, M F M [Institute for Biomedical Engineering, ETH Zurich, and PSI, Villigen (Switzerland); Siebers, J V [Department of Radiation Oncology, University of Virginia, Charlottesville, VA (United States)

    2016-06-15

    Purpose: To create and test an accurate EPID-frame-based VMAT QA metric to detect gross dose errors in real-time and to provide information about the source of error. Methods: A Swiss cheese model was created for an EPID-based real-time QA process. The system compares a treatmentplan- based reference set of EPID images with images acquired over each 2° gantry angle interval. The metric utilizes a sequence of independent consecutively executed error detection Methods: a masking technique that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment to quantify rotation, scaling and translation; standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each test were determined. For algorithm testing, twelve different types of errors were selected to modify the original plan. Corresponding predictions for each test case were generated, which included measurement-based noise. Each test case was run multiple times (with different noise per run) to assess the ability to detect introduced errors. Results: Averaged over five test runs, 99.1% of all plan variations that resulted in patient dose errors were detected within 2° and 100% within 4° (∼1% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 91.5% were detected by the system within 2°. Based on the type of method that detected the error, determination of error sources was achieved. Conclusion: An EPID-based during-treatment error detection system for VMAT deliveries was successfully designed and tested. The system utilizes a sequence of methods to identify and prevent gross treatment delivery errors. The system was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of errors in real-time and indicate the error

  20. Adaptive error detection for HDR/PDR brachytherapy: Guidance for decision making during real-time in vivo point dosimetry

    DEFF Research Database (Denmark)

    Kertzscher Schwencke, Gustavo Adolfo Vladimir; Andersen, Claus E.; Tanderup, Kari

    2014-01-01

    Purpose:This study presents an adaptive error detection algorithm (AEDA) for real-timein vivo point dosimetry during high dose rate (HDR) or pulsed dose rate (PDR) brachytherapy (BT) where the error identification, in contrast to existing approaches, does not depend on an a priori reconstruction ......, and the AEDA’s capacity to distinguish between true and false error scenarios. The study further shows that the AEDA can offer guidance in decision making in the event of potential errors detected with real-time in vivo point dosimetry....... of the dosimeter position reconstruction. Given its nearly exclusive dependence on stable dosimeter positioning, the AEDA allows for a substantially simplified and time efficient real-time in vivo BT dosimetry implementation. Methods:In the event of a measured potential treatment error, the AEDA proposes the most...

  1. Quantile index for gradual and abrupt change detection from CFB boiler sensor data in online settings

    NARCIS (Netherlands)

    Maslov, A.; Pechenizkiy, M.; Kärkkäinen, T.; Tähtinen, M.

    2012-01-01

    In this paper we consider the problem of online detection of gradual and abrupt changes in sensor data having high levels of noise and outliers. We propose a simple heuristic method based on the Quantile Index (QI) and study how robust this method is for detecting both gradual and abrupt changes

  2. On the use of on-line detection for maintenance of gradually deteriorating systems

    International Nuclear Information System (INIS)

    Fouladirad, Mitra; Grall, Antoine; Dieulle, Laurence

    2008-01-01

    This paper deals with condition-based maintenance and non-stationary degradation process due to sudden changes. This is an attempt to propose an adaptive maintenance policy based on the on-line change detection procedure which can help to detect switches from a nominal mode to an accelerated mode in a non-informative context about the change mode time

  3. On the use of on-line detection for maintenance of gradually deteriorating systems

    Energy Technology Data Exchange (ETDEWEB)

    Fouladirad, Mitra [Institut Charles Delaunay, Universite de Technologie de Troyes, FRE CNRS 2848, LM2S 12 rue Marie Curie, 10010 Troyes (France); Grall, Antoine [Institut Charles Delaunay, Universite de Technologie de Troyes, FRE CNRS 2848, LM2S 12 rue Marie Curie, 10010 Troyes (France)], E-mail: antoine.grall@utt.fr; Dieulle, Laurence [Institut Charles Delaunay, Universite de Technologie de Troyes, FRE CNRS 2848, LM2S 12 rue Marie Curie, 10010 Troyes (France)

    2008-12-15

    This paper deals with condition-based maintenance and non-stationary degradation process due to sudden changes. This is an attempt to propose an adaptive maintenance policy based on the on-line change detection procedure which can help to detect switches from a nominal mode to an accelerated mode in a non-informative context about the change mode time.

  4. The war of tools: how can NMR spectroscopists detect errors in their structures?

    Energy Technology Data Exchange (ETDEWEB)

    Saccenti, Edoardo; Rosato, Antonio [University of Florence, Magnetic Resonance Center (Italy)], E-mail: rosato@cerm.unifi.it

    2008-04-15

    Protein structure determination by NMR methods has started in the mid-eighties and has been growing steadily since then. Ca. 14% of the protein structures deposited in the PDB have been solved by NMR. The evaluation of the quality of NMR structures however is still lacking a well-established practice. In this work, we examined various tools for the assessment of structural quality to ascertain the extent to which these tools could be applied to detect flaws in NMR structures. In particular, we investigated the variation in the scores assigned by these programs as a function of the deviation of the structures induced by errors in assignments or in the upper distance limits used. These perturbations did not distort radically the protein fold, but resulted in backbone RMS deviations up to 3 A, which is in line with errors highlighted in the available literature. We found that it is quite difficult to discriminate the structures perturbed because of misassignments from the original ones, also because the spread in score over the conformers of the original bundle is relatively large. {phi}-{psi} distributions and normality scores related to the backbone conformation and to the distribution of side-chain dihedral angles are the most sensitive indicators of flaws.

  5. The use of concept maps to detect and correct concept errors (mistakes

    Directory of Open Access Journals (Sweden)

    Ladislada del Puy Molina Azcárate

    2013-02-01

    Full Text Available This work proposes to detect and correct concept errors (EECC to obtain Meaningful Learning (AS. The Conductive Model does not respond to the demand of meaningful learning that implies gathering thought, feeling and action to lead students up to both compromise and responsibility. In order to respond to the society competition about knowledge and information it is necessary to change the way of teaching and learning (from conductive model to constructive model. In this context it is important not only to learn meaningfully but also to create knowledge so as to developed dissertive, creative and critical thought, and the EECC are and obstacle to cope with this. This study tries to get ride of EECC in order to get meaningful learning. For this, it is essential to elaborate a Teaching Module (MI. This teaching Module implies the treatment of concept errors by a teacher able to change the dynamic of the group in the classroom. This M.I. was used among sixth grade primary school and first grade secondary school in some state assisted schools in the North of Argentina (Tucumán and Jujuy. After evaluation, the results showed great and positive changes among the experimental groups taking into account the attitude and the academic results. Meaningful Learning was shown through pupilʼs creativity, expressions and also their ability of putting this into practice into everyday life.

  6. A Comparison of Error Bounds for a Nonlinear Tracking System with Detection Probability Pd < 1

    Science.gov (United States)

    Tong, Huisi; Zhang, Hao; Meng, Huadong; Wang, Xiqin

    2012-01-01

    Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds. PMID:23242274

  7. Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation

    Science.gov (United States)

    Sakellariou, J. S.; Fassois, S. D.

    2006-11-01

    A stochastic output error (OE) vibration-based methodology for damage detection and assessment (localization and quantification) in structures under earthquake excitation is introduced. The methodology is intended for assessing the state of a structure following potential damage occurrence by exploiting vibration signal measurements produced by low-level earthquake excitations. It is based upon (a) stochastic OE model identification, (b) statistical hypothesis testing procedures for damage detection, and (c) a geometric method (GM) for damage assessment. The methodology's advantages include the effective use of the non-stationary and limited duration earthquake excitation, the handling of stochastic uncertainties, the tackling of the damage localization and quantification subproblems, the use of "small" size, simple and partial (in both the spatial and frequency bandwidth senses) identified OE-type models, and the use of a minimal number of measured vibration signals. Its feasibility and effectiveness are assessed via Monte Carlo experiments employing a simple simulation model of a 6 storey building. It is demonstrated that damage levels of 5% and 20% reduction in a storey's stiffness characteristics may be properly detected and assessed using noise-corrupted vibration signals.

  8. Health-related hot topic detection in online communities using text clustering.

    Directory of Open Access Journals (Sweden)

    Yingjie Lu

    Full Text Available Recently, health-related social media services, especially online health communities, have rapidly emerged. Patients with various health conditions participate in online health communities to share their experiences and exchange healthcare knowledge. Exploring hot topics in online health communities helps us better understand patients' needs and interest in health-related knowledge. However, the statistical topic analysis employed in previous studies is becoming impractical for processing the rapidly increasing amount of online data. Automatic topic detection based on document clustering is an alternative approach for extracting health-related hot topics in online communities. In addition to the keyword-based features used in traditional text clustering, we integrate medical domain-specific features to represent the messages posted in online health communities. Three disease discussion boards, including boards devoted to lung cancer, breast cancer and diabetes, from an online health community are used to test the effectiveness of topic detection. Experiment results demonstrate that health-related hot topics primarily include symptoms, examinations, drugs, procedures and complications. Further analysis reveals that there also exist some significant differences among the hot topics discussed on different types of disease discussion boards.

  9. A Hybrid System for On-line Blink Detection

    NARCIS (Netherlands)

    Sun, Yijia; Zafeiriou, Stefanos; Pantic, Maja; Jensen, Matthew; Meservy, Thomas; Burgoon, Judee; Nunamaker, Jay

    2013-01-01

    Eye blinking behaviour has been shown to be one of the most informative non-verbal behavioural cues for indicating deceptive behaviour. Traditional blink detection methods tend to use a tracker to extract static eye region images and classify those images as open and closed eyes in order to detect

  10. Online Anomaly Energy Consumption Detection Using Lambda Architecture

    DEFF Research Database (Denmark)

    Liu, Xiufeng; Iftikhar, Nadeem; Nielsen, Per Sieverts

    2016-01-01

    problem, which does data mining on a large amount of parallel data streams from smart meters. In this paper, we propose a supervised learning and statistical-based anomaly detection method, and implement a Lambda system using the in-memory distributed computing framework, Spark and its extension Spark...... of the lambda detection system....

  11. TU-G-BRD-08: In-Vivo EPID Dosimetry: Quantifying the Detectability of Four Classes of Errors

    Energy Technology Data Exchange (ETDEWEB)

    Ford, E; Phillips, M; Bojechko, C [University of Washington, Seattle, WA (United States)

    2015-06-15

    Purpose: EPID dosimetry is an emerging method for treatment verification and QA. Given that the in-vivo EPID technique is in clinical use at some centers, we investigate the sensitivity and specificity for detecting different classes of errors. We assess the impact of these errors using dose volume histogram endpoints. Though data exist for EPID dosimetry performed pre-treatment, this is the first study quantifying its effectiveness when used during patient treatment (in-vivo). Methods: We analyzed 17 patients; EPID images of the exit dose were acquired and used to reconstruct the planar dose at isocenter. This dose was compared to the TPS dose using a 3%/3mm gamma criteria. To simulate errors, modifications were made to treatment plans using four possible classes of error: 1) patient misalignment, 2) changes in patient body habitus, 3) machine output changes and 4) MLC misalignments. Each error was applied with varying magnitudes. To assess the detectability of the error, the area under a ROC curve (AUC) was analyzed. The AUC was compared to changes in D99 of the PTV introduced by the simulated error. Results: For systematic changes in the MLC leaves, changes in the machine output and patient habitus, the AUC varied from 0.78–0.97 scaling with the magnitude of the error. The optimal gamma threshold as determined by the ROC curve varied between 84–92%. There was little diagnostic power in detecting random MLC leaf errors and patient shifts (AUC 0.52–0.74). Some errors with weak detectability had large changes in D99. Conclusion: These data demonstrate the ability of EPID-based in-vivo dosimetry in detecting variations in patient habitus and errors related to machine parameters such as systematic MLC misalignments and machine output changes. There was no correlation found between the detectability of the error using the gamma pass rate, ROC analysis and the impact on the dose volume histogram. Funded by grant R18HS022244 from AHRQ.

  12. Ultrasensitive microchip based on smart microgel for real-time online detection of trace threat analytes.

    Science.gov (United States)

    Lin, Shuo; Wang, Wei; Ju, Xiao-Jie; Xie, Rui; Liu, Zhuang; Yu, Hai-Rong; Zhang, Chuan; Chu, Liang-Yin

    2016-02-23

    Real-time online detection of trace threat analytes is critical for global sustainability, whereas the key challenge is how to efficiently convert and amplify analyte signals into simple readouts. Here we report an ultrasensitive microfluidic platform incorporated with smart microgel for real-time online detection of trace threat analytes. The microgel can swell responding to specific stimulus in flowing solution, resulting in efficient conversion of the stimulus signal into significantly amplified signal of flow-rate change; thus highly sensitive, fast, and selective detection can be achieved. We demonstrate this by incorporating ion-recognizable microgel for detecting trace Pb(2+), and connecting our platform with pipelines of tap water and wastewater for real-time online Pb(2+) detection to achieve timely pollution warning and terminating. This work provides a generalizable platform for incorporating myriad stimuli-responsive microgels to achieve ever-better performance for real-time online detection of various trace threat molecules, and may expand the scope of applications of detection techniques.

  13. SU-E-T-392: Evaluation of Ion Chamber/film and Log File Based QA to Detect Delivery Errors

    International Nuclear Information System (INIS)

    Nelson, C; Mason, B; Kirsner, S; Ohrt, J

    2015-01-01

    Purpose: Ion chamber and film (ICAF) is a method used to verify patient dose prior to treatment. More recently, log file based QA has been shown as an alternative for measurement based QA. In this study, we delivered VMAT plans with and without errors to determine if ICAF and/or log file based QA was able to detect the errors. Methods: Using two VMAT patients, the original treatment plan plus 7 additional plans with delivery errors introduced were generated and delivered. The erroneous plans had gantry, collimator, MLC, gantry and collimator, collimator and MLC, MLC and gantry, and gantry, collimator, and MLC errors. The gantry and collimator errors were off by 4 0 for one of the two arcs. The MLC error introduced was one in which the opening aperture didn’t move throughout the delivery of the field. For each delivery, an ICAF measurement was made as well as a dose comparison based upon log files. Passing criteria to evaluate the plans were ion chamber less and 5% and film 90% of pixels pass the 3mm/3% gamma analysis(GA). For log file analysis 90% of voxels pass the 3mm/3% 3D GA and beam parameters match what was in the plan. Results: Two original plans were delivered and passed both ICAF and log file base QA. Both ICAF and log file QA met the dosimetry criteria on 4 of the 12 erroneous cases analyzed (2 cases were not analyzed). For the log file analysis, all 12 erroneous plans alerted a mismatch in delivery versus what was planned. The 8 plans that didn’t meet criteria all had MLC errors. Conclusion: Our study demonstrates that log file based pre-treatment QA was able to detect small errors that may not be detected using an ICAF and both methods of were able to detect larger delivery errors

  14. Detection of illicit online sales of fentanyls via Twitter [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Tim K. Mackey

    2017-11-01

    Full Text Available A counterfeit fentanyl crisis is currently underway in the United States.  Counterfeit versions of commonly abused prescription drugs laced with fentanyl are being manufactured, distributed, and sold globally, leading to an increase in overdose and death in countries like the United States and Canada.  Despite concerns from the U.S. Drug Enforcement Agency regarding covert and overt sale of fentanyls online, no study has examined the role of the Internet and social media on fentanyl illegal marketing and direct-to-consumer access.  In response, this study collected and analyzed five months of Twitter data (from June-November 2015 filtered for the keyword “fentanyl” using Amazon Web Services.  We then analyzed 28,711 fentanyl-related tweets using text filtering and a machine learning approach called a Biterm Topic Model (BTM to detect underlying latent patterns or “topics” present in the corpus of tweets.  Using this approach we detected a subset of 771 tweets marketing the sale of fentanyls online and then filtered this down to nine unique tweets containing hyperlinks to external websites.  Six hyperlinks were associated with online fentanyl classified ads, 2 with illicit online pharmacies, and 1 could not be classified due to traffic redirection.  Importantly, the one illicit online pharmacy detected was still accessible and offered the sale of fentanyls and other controlled substances direct-to-consumers with no prescription required at the time of publication of this study.   Overall, we detected a relatively small sample of Tweets promoting illegal online sale of fentanyls.  However, the detection of even a few online sellers represents a public health danger and a direct violation of law that demands further study.

  15. A New Approach to Detection of Systematic Errors in Secondary Substation Monitoring Equipment Based on Short Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Javier Moriano

    2016-01-01

    Full Text Available In recent years, Secondary Substations (SSs are being provided with equipment that allows their full management. This is particularly useful not only for monitoring and planning purposes but also for detecting erroneous measurements, which could negatively affect the performance of the SS. On the other hand, load forecasting is extremely important since they help electricity companies to make crucial decisions regarding purchasing and generating electric power, load switching, and infrastructure development. In this regard, Short Term Load Forecasting (STLF allows the electric power load to be predicted over an interval ranging from one hour to one week. However, important issues concerning error detection by employing STLF has not been specifically addressed until now. This paper proposes a novel STLF-based approach to the detection of gain and offset errors introduced by the measurement equipment. The implemented system has been tested against real power load data provided by electricity suppliers. Different gain and offset error levels are successfully detected.

  16. On-Line QRS Complex Detection Using Wavelet Filtering

    National Research Council Canada - National Science Library

    Szilagyi, L

    2001-01-01

    ...: first a wavelet transform filtering is applied to the signal, then QRS complex localization is performed using a maximum detection and peak classification algorithm The algorithm has been tested...

  17. Similarity between community structures of different online social networks and its impact on underlying community detection

    Science.gov (United States)

    Fan, W.; Yeung, K. H.

    2015-03-01

    As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.

  18. Application of round grating angle measurement composite error amendment in the online measurement accuracy improvement of large diameter

    Science.gov (United States)

    Wang, Biao; Yu, Xiaofen; Li, Qinzhao; Zheng, Yu

    2008-10-01

    The paper aiming at the influence factor of round grating dividing error, rolling-wheel produce eccentricity and surface shape errors provides an amendment method based on rolling-wheel to get the composite error model which includes all influence factors above, and then corrects the non-circle measurement angle error of the rolling-wheel. We make soft simulation verification and have experiment; the result indicates that the composite error amendment method can improve the diameter measurement accuracy with rolling-wheel theory. It has wide application prospect for the measurement accuracy higher than 5 μm/m.

  19. Detecting fast, online reasoning processes in clinical decision making.

    Science.gov (United States)

    Flores, Amanda; Cobos, Pedro L; López, Francisco J; Godoy, Antonio

    2014-06-01

    In an experiment that used the inconsistency paradigm, experienced clinical psychologists and psychology students performed a reading task using clinical reports and a diagnostic judgment task. The clinical reports provided information about the symptoms of hypothetical clients who had been previously diagnosed with a specific mental disorder. Reading times of inconsistent target sentences were slower than those of control sentences, demonstrating an inconsistency effect. The results also showed that experienced clinicians gave different weights to different symptoms according to their relevance when fluently reading the clinical reports provided, despite the fact that all the symptoms were of equal diagnostic value according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The diagnostic judgment task yielded a similar pattern of results. In contrast to previous findings, the results of the reading task may be taken as direct evidence of the intervention of reasoning processes that occur very early, rapidly, and online. We suggest that these processes are based on the representation of mental disorders and that these representations are particularly suited to fast retrieval from memory and to making inferences. They may also be related to the clinicians' causal reasoning. The implications of these results for clinician training are also discussed.

  20. FLEAD: online frequency likelihood estimation anomaly detection for mobile sensing

    NARCIS (Netherlands)

    Le Viet Duc, L Duc; Scholten, Johan; Havinga, Paul J.M.

    With the rise of smartphone platforms, adaptive sensing becomes an predominant key to overcome intricate constraints such as smartphone's capabilities and dynamic data. One way to do this is estimating the event probability based on anomaly detection to invoke heavy processes, such as switching on

  1. Towards an Enhanced Aspect-based Contradiction Detection Approach for Online Review Content

    Science.gov (United States)

    Nuradilah Azman, Siti; Ishak, Iskandar; Sharef, Nurfadhlina Mohd; Sidi, Fatimah

    2017-09-01

    User generated content as such online reviews plays an important role in customer’s purchase decisions. Many works have focused on identifying satisfaction of the reviewer in social media through the study of sentiment analysis (SA) and opinion mining. The large amount of potential application and the increasing number of opinions expresses on the web results in researchers interest on sentiment analysis and opinion mining. However, due to the reviewer’s idiosyncrasy, reviewer may have different preferences and point of view for a particular subject which in this case hotel reviews. There is still limited research that focuses on this contradiction detection in the perspective of tourism online review especially in numerical contradiction. Therefore, the aim of this paper to investigate the type of contradiction in online review which mainly focusing on hotel online review, to provide useful material on process or methods for identifying contradiction which mainly on the review itself and to determine opportunities for relevant future research for online review contradiction detection. We also proposed a model to detect numerical contradiction in user generated content for tourism industry.

  2. Use of behavioral biometrics in intrusion detection and online gaming

    Science.gov (United States)

    Yampolskiy, Roman V.; Govindaraju, Venu

    2006-04-01

    Behavior based intrusion detection is a frequently used approach for insuring network security. We expend behavior based intrusion detection approach to a new domain of game networks. Specifically, our research shows that a unique behavioral biometric can be generated based on the strategy used by an individual to play a game. We wrote software capable of automatically extracting behavioral profiles for each player in a game of Poker. Once a behavioral signature is generated for a player, it is continuously compared against player's current actions. Any significant deviations in behavior are reported to the game server administrator as potential security breaches. Our algorithm addresses a well-known problem of user verification and can be re-applied to the fields beyond game networks, such as operating systems and non-game networks security.

  3. Adapting Parameterized Motions using Iterative Learning and Online Collision Detection

    DEFF Research Database (Denmark)

    Laursen, Johan Sund; Sørensen, Lars Carøe; Schultz, Ulrik Pagh

    2018-01-01

    utilizing Gaussian Process learning. This allows for motion parameters to be optimized using real world trials which incorporate all uncertainties inherent in the assembly process without requiring advanced robot and sensor setups. The result is a simple and straightforward system which helps the user...... automatically find robust and uncertainty-tolerant motions. We present experiments for an assembly case showing both detection and learning in the real world and how these combine to a robust robot system....

  4. Applications of Graph-Theoretic Tests to Online Change Detection

    Science.gov (United States)

    2014-05-09

    stock broker decides to sell a majority of his positions due to a change in the markets; a child grabs a snack because he has become hungry; an alarm...detected and the time when a negative result will occur (i.e. machine death through mechanical failure) or a positive chance squandered (not buying ...and moving low pressure systems in the atmosphere, and these systems cause persistence to daily rainfall. The daily weather in this area is a

  5. An investigation into soft error detection efficiency at operating system level.

    Science.gov (United States)

    Asghari, Seyyed Amir; Kaynak, Okyay; Taheri, Hassan

    2014-01-01

    Electronic equipment operating in harsh environments such as space is subjected to a range of threats. The most important of these is radiation that gives rise to permanent and transient errors on microelectronic components. The occurrence rate of transient errors is significantly more than permanent errors. The transient errors, or soft errors, emerge in two formats: control flow errors (CFEs) and data errors. Valuable research results have already appeared in literature at hardware and software levels for their alleviation. However, there is the basic assumption behind these works that the operating system is reliable and the focus is on other system levels. In this paper, we investigate the effects of soft errors on the operating system components and compare their vulnerability with that of application level components. Results show that soft errors in operating system components affect both operating system and application level components. Therefore, by providing endurance to operating system level components against soft errors, both operating system and application level components gain tolerance.

  6. An Investigation into Soft Error Detection Efficiency at Operating System Level

    Directory of Open Access Journals (Sweden)

    Seyyed Amir Asghari

    2014-01-01

    Full Text Available Electronic equipment operating in harsh environments such as space is subjected to a range of threats. The most important of these is radiation that gives rise to permanent and transient errors on microelectronic components. The occurrence rate of transient errors is significantly more than permanent errors. The transient errors, or soft errors, emerge in two formats: control flow errors (CFEs and data errors. Valuable research results have already appeared in literature at hardware and software levels for their alleviation. However, there is the basic assumption behind these works that the operating system is reliable and the focus is on other system levels. In this paper, we investigate the effects of soft errors on the operating system components and compare their vulnerability with that of application level components. Results show that soft errors in operating system components affect both operating system and application level components. Therefore, by providing endurance to operating system level components against soft errors, both operating system and application level components gain tolerance.

  7. Online fouling detection in electrical circulation heaters using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Lalot, S. [M.E.T.I.E.R., Longuenesse Cedex (France); Universite de Valenciennes (France). LME; Lecoeuche, S. [M.E.T.I.E.R., Longuenesse Cedex (France); Universite de Lille (France). Laboratoire 13D

    2003-06-01

    Here is presented a method that is able to detect fouling during the service of a circulation electrical heater. The neural based technique is divided in two major steps: identification and classification. Each step uses a neural network, the connection weights of the first one being the inputs of the second network. Each step is detailed and the main characteristics and abilities of the two neural networks are given. It is shown that the method is able to discriminate fouling from viscosity modification that would lead to the same type of effect on the total heat transfer coefficient. (author)

  8. Plagiarism by Adult Learners Online: A case study in detection and remediation

    Directory of Open Access Journals (Sweden)

    Christine Jocoy

    2006-06-01

    Full Text Available Detecting and combating plagiarism from Web-based sources is a concern for administrators and instructors involved in online distance education. In this paper, we quantify copy-and-paste plagiarism among adult learners in an online geography course offered through Penn State’s World Campus Geographic Information Systems (GIS certificate program. We also evaluate the effectiveness of an “expectation management” strategy intended to discourage adult learners from unintentional violations. We found that while manual methods detected plagiarism in only about 3 percent of assignments, Turnitin.com revealed a 13 percent plagiarism rate among the same assignments. Our attempts to increase awareness and manage expectations decreased infractions measurably, but not significantly. In contrast, Turnitin.com substantially improved our ability to detect infractions. We conclude that raising awareness and managing expectations about plagiarism may be worthwhile, but is no substitute for systematic detection and vigilant enforcement, even among adult learners.

  9. Robust bivariate error detection in skewed data with application to historical radiosonde winds

    KAUST Repository

    Sun, Ying

    2017-01-18

    The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

  10. Robust bivariate error detection in skewed data with application to historical radiosonde winds

    KAUST Repository

    Sun, Ying; Hering, Amanda S.; Browning, Joshua M.

    2017-01-01

    The global historical radiosonde archives date back to the 1920s and contain the only directly observed measurements of temperature, wind, and moisture in the upper atmosphere, but they contain many random errors. Most of the focus on cleaning these large datasets has been on temperatures, but winds are important inputs to climate models and in studies of wind climatology. The bivariate distribution of the wind vector does not have elliptical contours but is skewed and heavy-tailed, so we develop two methods for outlier detection based on the bivariate skew-t (BST) distribution, using either distance-based or contour-based approaches to flag observations as potential outliers. We develop a framework to robustly estimate the parameters of the BST and then show how the tuning parameter to get these estimates is chosen. In simulation, we compare our methods with one based on a bivariate normal distribution and a nonparametric approach based on the bagplot. We then apply all four methods to the winds observed for over 35,000 radiosonde launches at a single station and demonstrate differences in the number of observations flagged across eight pressure levels and through time. In this pilot study, the method based on the BST contours performs very well.

  11. Determination of Peroxide-Based Explosives Using Liquid Chromatography with On-Line Infrared Detection

    NARCIS (Netherlands)

    Schulte-Ladbeck, Rasmus; Edelmann, Andrea; Quintas, Guillermo; Lendl, Bernhard; Karst, U.

    2006-01-01

    A nondestructive analytical method for peroxide-based explosives determination in solid samples is described. Reversed-phase high-performance liquid chromatography in combination with on-line Fourier transform infrared (FT-IR) detection is used for the analysis of triacetonetriperoxide (TATP) and

  12. Online slug detection in multi-phase transportation pipelines using electrical tomography

    DEFF Research Database (Denmark)

    Pedersen, Simon; Mai, Christian; Hansen, Leif

    2015-01-01

    in the pipelines is a highly investigated topic. To eliminate the slug in an online manner real-time slug detection methods are often required. Traditionally topside pressure transmitters upstream a 3-phase separator have been used as the controlled variable. In this paper Electrical Resistivity Tomography (ERT...

  13. Online Slug Detection in Multi-phase Transportation Pipelines Using Electrical Tomography

    DEFF Research Database (Denmark)

    Pedersen, Simon; Mai, Christian; Hansen, Leif

    2015-01-01

    in the pipelines is a highly investigated topic. To eliminate the slug in an online manner real-time slug detection methods are often required. Traditionally topside pressure transmitters upstream a 3-phase separator have been used as the controlled variable. In this paper Electrical Resistivity Tomography (ERT...

  14. PageFocus: Using paradata to detect and prevent cheating on online achievement tests.

    Science.gov (United States)

    Diedenhofen, Birk; Musch, Jochen

    2017-08-01

    Cheating threatens the validity of unproctored online achievement tests. To address this problem, we developed PageFocus, a JavaScript that detects when participants abandon test pages by switching to another window or browser tab. In a first study, we aimed at testing whether PageFocus could detect and prevent cheating. We asked 115 lab and 186 online participants to complete a knowledge test comprising items that were difficult to answer but easy to look up on the Internet. Half of the participants were invited to look up the solutions, which significantly increased their test scores. The PageFocus script detected test takers who abandoned the test page with very high sensitivity and specificity, and successfully reduced cheating by generating a popup message that asked participants not to cheat. In a second study, 510 online participants completed a knowledge test comprising items that could easily be looked up and a reasoning task involving matrices that were impossible to look up. In a first group, a performance-related monetary reward was promised to the top scorers; in a second group, participants took part in a lottery that provided performance-unrelated rewards; and in a third group, no incentive was offered. PageFocus revealed that participants cheated more when performance-related incentives were offered. As expected, however, this effect was limited to items that could easily be looked up. We recommend that PageFocus be routinely employed to detect and prevent cheating on online achievement tests.

  15. Mastitis therapy and control - Automatic on-line detection of abnormal milk.

    NARCIS (Netherlands)

    Hogeveen, H.

    2011-01-01

    Automated online detection of mastitis and abnormal milk is an important subject in the dairy industry, especially because of the introduction of automatic milking systems and the growing farm sizes with consequently less labor available per cow. Demands for performance, which is expressed as

  16. Nonlinear ultrasonic wave modulation for online fatigue crack detection

    Science.gov (United States)

    Sohn, Hoon; Lim, Hyung Jin; DeSimio, Martin P.; Brown, Kevin; Derriso, Mark

    2014-02-01

    This study presents a fatigue crack detection technique using nonlinear ultrasonic wave modulation. Ultrasonic waves at two distinctive driving frequencies are generated and corresponding ultrasonic responses are measured using permanently installed lead zirconate titanate (PZT) transducers with a potential for continuous monitoring. Here, the input signal at the lower driving frequency is often referred to as a 'pumping' signal, and the higher frequency input is referred to as a 'probing' signal. The presence of a system nonlinearity, such as a crack formation, can provide a mechanism for nonlinear wave modulation, and create spectral sidebands around the frequency of the probing signal. A signal processing technique combining linear response subtraction (LRS) and synchronous demodulation (SD) is developed specifically to extract the crack-induced spectral sidebands. The proposed crack detection method is successfully applied to identify actual fatigue cracks grown in metallic plate and complex fitting-lug specimens. Finally, the effect of pumping and probing frequencies on the amplitude of the first spectral sideband is investigated using the first sideband spectrogram (FSS) obtained by sweeping both pumping and probing signals over specified frequency ranges.

  17. Study on judgement baseline for XRF on-line detection system

    International Nuclear Information System (INIS)

    Zhang Quanshi; Bao Min

    2000-01-01

    Based on the Signal Detection Theory (SDT) and the statistics principle, the choice method of judgement baseline was studied. According to the characteristics of X-ray Fluorescence (XRF) spectra in the on-line detection system, the calculation methods for the characteristic peak of the element-tagged and background were carried out. The complex judgement baseline were rationally selected after a lot of experiments and analyzing. The operating results of near one year show that it is available

  18. A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE.

    Directory of Open Access Journals (Sweden)

    Kevin P Keegan

    Full Text Available We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation, to assess sequencing quality (alternatively referred to as "noise" or "error" within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred. Here, DRISEE is applied to (non amplicon data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs, a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.

  19. Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

    International Nuclear Information System (INIS)

    Chen, Hsin-Chen; Tan, Jun; Dolly, Steven; Kavanaugh, James; Harold Li, H.; Altman, Michael; Gay, Hiram; Thorstad, Wade L.; Mutic, Sasa; Li, Hua; Anastasio, Mark A.; Low, Daniel A.

    2015-01-01

    Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets

  20. Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Hsin-Chen; Tan, Jun; Dolly, Steven; Kavanaugh, James; Harold Li, H.; Altman, Michael; Gay, Hiram; Thorstad, Wade L.; Mutic, Sasa; Li, Hua, E-mail: huli@radonc.wustl.edu [Department of Radiation Oncology, Washington University, St. Louis, Missouri 63110 (United States); Anastasio, Mark A. [Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63110 (United States); Low, Daniel A. [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California 90095 (United States)

    2015-02-15

    Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets

  1. The Case of the Pilfered Paper: Implications of Online Writing Assistance and Web-Based Plagiarism Detection Services

    Science.gov (United States)

    Morgan, Phoebe; Vaughn, Jacqueline

    2010-01-01

    While there is nothing new about academic dishonesty, how it is committed, prevented, and detected has been dramatically transformed by the advent of online technologies. This article briefly describes the concurrent emergence of online writing assistance services and Web-based plagiarism detection tools and examines the implications of both for…

  2. Film techniques in radiotherapy for treatment verification, determination of patient exit dose, and detection of localization error

    International Nuclear Information System (INIS)

    Haus, A.G.; Marks, J.E.

    1974-01-01

    In patient radiation therapy, it is important to know that the diseased area is included in the treatment field and that normal anatomy is properly shielded or excluded. Since 1969, a film technique developed for imaging of the complete patient radiation exposure has been applied for treatment verification and for the detection and evaluation of localization errors that may occur during treatment. The technique basically consists of placing a film under the patient during the entire radiation exposure. This film should have proper sensitivity and contrast in the exit dose exposure range encountered in radiotherapy. In this communication, we describe how various exit doses fit the characteristic curve of the film; examples of films exposed to various exit doses; the technique for using the film to determine the spatial distribution of the absorbed exit dose; and types of errors commonly detected. Results are presented illustrating that, as the frequency of use of this film technique is increased, localization error is reduced significantly

  3. Online technique for detecting state of onboard fiber optic gyroscope

    International Nuclear Information System (INIS)

    Miao, Zhiyong; He, Kunpeng; Pang, Shuwan; Xu, Dingjie; Tian, Chunmiao

    2015-01-01

    Although angle random walk (ARW) of fiber optic gyroscope (FOG) has been well modeled and identified before being integrated into the high-accuracy attitude control system of satellite, aging and unexpected failures can affect the performance of FOG after launch, resulting in the variation of ARW coefficient. Therefore, the ARW coefficient can be regarded as an indicator of “state of health” for FOG diagnosis in some sense. The Allan variance method can be used to estimate ARW coefficient of FOG, however, it requires a large amount of data to be stored. Moreover, the procedure of drawing slope lines for estimation is painful. To overcome the barriers, a weighted state-space model that directly models the ARW to obtain a nonlinear state-space model was established for FOG. Then, a neural extended-Kalman filter algorithm was implemented to estimate and track the variation of ARW in real time. The results of experiment show that the proposed approach is valid to detect the state of FOG. Moreover, the proposed technique effectively avoids the storage of data

  4. Online technique for detecting state of onboard fiber optic gyroscope

    Energy Technology Data Exchange (ETDEWEB)

    Miao, Zhiyong; He, Kunpeng, E-mail: pengkhe@126.com; Pang, Shuwan [Department of Automation, Harbin Engineering University, Harbin, Heilongjiang 150000 (China); Xu, Dingjie [School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, Heilongjiang 150000 (China); Tian, Chunmiao [Department of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang 150000 (China)

    2015-02-15

    Although angle random walk (ARW) of fiber optic gyroscope (FOG) has been well modeled and identified before being integrated into the high-accuracy attitude control system of satellite, aging and unexpected failures can affect the performance of FOG after launch, resulting in the variation of ARW coefficient. Therefore, the ARW coefficient can be regarded as an indicator of “state of health” for FOG diagnosis in some sense. The Allan variance method can be used to estimate ARW coefficient of FOG, however, it requires a large amount of data to be stored. Moreover, the procedure of drawing slope lines for estimation is painful. To overcome the barriers, a weighted state-space model that directly models the ARW to obtain a nonlinear state-space model was established for FOG. Then, a neural extended-Kalman filter algorithm was implemented to estimate and track the variation of ARW in real time. The results of experiment show that the proposed approach is valid to detect the state of FOG. Moreover, the proposed technique effectively avoids the storage of data.

  5. Detection of Common Errors in Turkish EFL Students' Writing through a Corpus Analytic Approach

    Science.gov (United States)

    Demirel, Elif Tokdemir

    2017-01-01

    The present study aims to explore Turkish EFL students' major writing difficulties by analyzing the frequent writing errors in academic essays. Accordingly, the study examined errors in a corpus of 150 academic essays written by Turkish EFL students studying at the Department of English Language and Literature at a public university in Turkey. The…

  6. Minimizing driver errors: examining factors leading to failed target tracking and detection.

    Science.gov (United States)

    2013-06-01

    Driving a motor vehicle is a common practice for many individuals. Although driving becomes : repetitive and a very habitual task, errors can occur that lead to accidents. One factor that can be a : cause for such errors is a lapse in attention or a ...

  7. Phase Error Caused by Speed Mismatch Analysis in the Line-Scan Defect Detection by Using Fourier Transform Technique

    Directory of Open Access Journals (Sweden)

    Eryi Hu

    2015-01-01

    Full Text Available The phase error caused by the speed mismatch issue is researched in the line-scan images capturing 3D profile measurement. The experimental system is constructed by a line-scan CCD camera, an object moving device, a digital fringe pattern projector, and a personal computer. In the experiment procedure, the detected object is moving relative to the image capturing system by using a motorized translation stage in a stable velocity. The digital fringe pattern is projected onto the detected object, and then the deformed patterns are captured and recorded in the computer. The object surface profile can be calculated by the Fourier transform profilometry. However, the moving speed mismatch error will still exist in most of the engineering application occasion even after an image system calibration. When the moving speed of the detected object is faster than the expected value, the captured image will be compressed in the moving direction of the detected object. In order to overcome this kind of measurement error, an image recovering algorithm is proposed to reconstruct the original compressed image. Thus, the phase values can be extracted much more accurately by the reconstructed images. And then, the phase error distribution caused by the speed mismatch is analyzed by the simulation and experimental methods.

  8. Error Detection and Self-Assessment as Mechanisms to Promote Self-Regulation of Learning among Secondary Education Students

    Science.gov (United States)

    Zamora, Ángela; Suárez, José Manuel; Ardura, Diego

    2018-01-01

    The authors' objective was to study the role of error detection and retroactive self-regulation as determinants of performance in secondary education students. A total of 198 students participated in the quasiexperimental study, which involved a control group and two experimental groups. This enabled the authors to analyze the effects of both…

  9. The role of comprehensive check at the blood bank reception on blood requisitions in detecting potential transfusion errors.

    Science.gov (United States)

    Jain, Ashish; Kumari, Sonam; Marwaha, Neelam; Sharma, Ratti Ram

    2015-06-01

    Pre-transfusion testing includes proper requisitions, compatibility testing and pre-release checks. Proper labelling of samples and blood units and accurate patient details check helps to minimize the risk of errors in transfusion. This study was aimed to identify requisition errors before compatibility testing. The study was conducted in the blood bank of a tertiary care hospital in north India over a period of 3 months. The requisitions were screened at the reception counter and inside the pre-transfusion testing laboratory for errors. This included checking the Central Registration number (C.R. No.) and name of patient on the requisition form and the sample label; appropriateness of sample container and sample label; incomplete requisitions; blood group discrepancy. Out of the 17,148 blood requisitions, 474 (2.76 %) requisition errors were detected before the compatibility testing. There were 192 (1.11 %) requisitions where the C.R. No. on the form and the sample were not tallying and in 70 (0.40 %) requisitions patient's name on the requisition form and the sample were different. Highest number of requisitions errors were observed in those received from the Emergency and Trauma services (27.38 %) followed by Medical wards (15.82 %) and the lowest number (3.16 %) of requisition errors were observed from Hematology and Oncology wards. C.R. No. error was the most common error observed in our study. Thus a careful check of the blood requisitions at the blood bank reception counter helps in identifying the potential transfusion errors.

  10. Online Detection of Peroxidase Using 3D Printing, Active Magnetic Mixing, and Spectra Analysis

    Directory of Open Access Journals (Sweden)

    Shanshan Bai

    2017-01-01

    Full Text Available A new method for online detection of peroxidase (POD using 3D printing, active magnetic mixing, fluidic control, and optical detection was developed and demonstrated in this study. The proposed POD detection system consisted of a 3D printing and active magnetic mixing based fluidic chip for online catalytic reaction, an optical detector with a fluidic flow cell for quantitative determination of the final catalysate, and a single-chip microcontroller based controller for automatic control of two rotating magnetic fields and four precise peristaltic pumps. Horseradish peroxidase (HRP was used as research model and a linear relationship between the absorbance at the characteristic wavelength of 450 nm and the concentration of HRP of 1/4–1/128 μg mL−1 was obtained as A  =  0.257ln⁡(C + 1.425 (R2  = 0.976. For the HRP spiked pork tests, the recoveries of HRP ranged from 93.5% to 110.4%, indicating that this proposed system was capable of detecting HRP in real samples. It has the potential to be extended for online detection of the activity of other enzymes and integration with ELISA method for biological and chemical analysis.

  11. Uric acid, an important screening tool to detect inborn errors of metabolism: a case series.

    Science.gov (United States)

    Jasinge, Eresha; Kularatnam, Grace Angeline Malarnangai; Dilanthi, Hewa Warawitage; Vidanapathirana, Dinesha Maduri; Jayasena, Kandana Liyanage Subhashinie Priyadarshika Kapilani Menike; Chandrasiri, Nambage Dona Priyani Dhammika; Indika, Neluwa Liyanage Ruwan; Ratnayake, Pyara Dilani; Gunasekara, Vindya Nandani; Fairbanks, Lynette Dianne; Stiburkova, Blanka

    2017-09-06

    Uric acid is the metabolic end product of purine metabolism in humans. Altered serum and urine uric acid level (both above and below the reference ranges) is an indispensable marker in detecting rare inborn errors of metabolism. We describe different case scenarios of 4 Sri Lankan patients related to abnormal uric acid levels in blood and urine. CASE 1: A one-and-half-year-old boy was investigated for haematuria and a calculus in the bladder. Xanthine crystals were seen in microscopic examination of urine sediment. Low uric acid concentrations in serum and low urinary fractional excretion of uric acid associated with high urinary excretion of xanthine and hypoxanthine were compatible with xanthine oxidase deficiency. CASE 2: An 8-month-old boy presented with intractable seizures, feeding difficulties, screaming episodes, microcephaly, facial dysmorphism and severe neuro developmental delay. Low uric acid level in serum, low fractional excretion of uric acid and radiological findings were consistent with possible molybdenum cofactor deficiency. Diagnosis was confirmed by elevated levels of xanthine, hypoxanthine and sulfocysteine levels in urine. CASE 3: A 3-year-10-month-old boy presented with global developmental delay, failure to thrive, dystonia and self-destructive behaviour. High uric acid levels in serum, increased fractional excretion of uric acid and absent hypoxanthine-guanine phosphoribosyltransferase enzyme level confirmed the diagnosis of Lesch-Nyhan syndrome. CASE 4: A 9-year-old boy was investigated for lower abdominal pain, gross haematuria and right renal calculus. Low uric acid level in serum and increased fractional excretion of uric acid pointed towards hereditary renal hypouricaemia which was confirmed by genetic studies. Abnormal uric acid level in blood and urine is a valuable tool in screening for clinical conditions related to derangement of the nucleic acid metabolic pathway.

  12. [Event-related EEG potentials associated with error detection in psychiatric disorder: literature review].

    Science.gov (United States)

    Balogh, Lívia; Czobor, Pál

    2010-01-01

    Error-related bioelectric signals constitute a special subgroup of event-related potentials. Researchers have identified two evoked potential components to be closely related to error processing, namely error-related negativity (ERN) and error-positivity (Pe), and they linked these to specific cognitive functions. In our article first we give a brief description of these components, then based on the available literature, we review differences in error-related evoked potentials observed in patients across psychiatric disorders. The PubMed and Medline search engines were used in order to identify all relevant articles, published between 2000 and 2009. For the purpose of the current paper we reviewed publications summarizing results of clinical trials. Patients suffering from schizophrenia, anorexia nervosa or borderline personality disorder exhibited a decrease in the amplitude of error-negativity when compared with healthy controls, while in cases of depression and anxiety an increase in the amplitude has been observed. Some of the articles suggest specific personality variables, such as impulsivity, perfectionism, negative emotions or sensitivity to punishment to underlie these electrophysiological differences. Research in the field of error-related electric activity has come to the focus of psychiatry research only recently, thus the amount of available data is significantly limited. However, since this is a relatively new field of research, the results available at present are noteworthy and promising for future electrophysiological investigations in psychiatric disorders.

  13. 16-bit error detection and correction (EDAC) controller design using FPGA for critical memory applications

    International Nuclear Information System (INIS)

    Misra, M.K.; Sridhar, N.; Krishnakumar, B.; Ilango Sambasivan, S.

    2002-01-01

    Full text: Complex electronic systems require the utmost reliability, especially when the storage and retrieval of critical data demands faultless operation, the system designer must strive for the highest reliability possible. Extra effort must be expended to achieve this reliability. Fortunately, not all systems must operate with these ultra reliability requirements. The majority of systems operate in an area where system failure is not hazardous. But the applications like nuclear reactors, medical and avionics are the areas where system failure may prove to have harsh consequences. High-density memories generate errors in their stored data due to external disturbances like power supply surges, system noise, natural radiation etc. These errors are called soft errors or transient errors, since they don't cause permanent damage to the memory cell. Hard errors may also occur on system memory boards. These hard errors occur if one RAM component or RAM cell fails and is stuck at either 0 or 1. Although less frequent, hard errors may cause a complete system failure. These are the major problems associated with memories

  14. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

    Energy Technology Data Exchange (ETDEWEB)

    Grimm, Lars J., E-mail: Lars.grimm@duke.edu; Ghate, Sujata V.; Yoon, Sora C.; Kim, Connie [Department of Radiology, Duke University Medical Center, Box 3808, Durham, North Carolina 27710 (United States); Kuzmiak, Cherie M. [Department of Radiology, University of North Carolina School of Medicine, 2006 Old Clinic, CB No. 7510, Chapel Hill, North Carolina 27599 (United States); Mazurowski, Maciej A. [Duke University Medical Center, Box 2731 Medical Center, Durham, North Carolina 27710 (United States)

    2014-03-15

    Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

  15. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

    International Nuclear Information System (INIS)

    Grimm, Lars J.; Ghate, Sujata V.; Yoon, Sora C.; Kim, Connie; Kuzmiak, Cherie M.; Mazurowski, Maciej A.

    2014-01-01

    Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees

  16. [Study on the Effects and Compensation Effect of Recording Parameters Error on Imaging Performance of Holographic Grating in On-Line Spectral Diagnose].

    Science.gov (United States)

    Jiang, Yan-xiu; Bayanheshig; Yang, Shuo; Zhao, Xu-long; Wu, Na; Li, Wen-hao

    2016-03-01

    To making the high resolution grating, a numerical calculation was used to analyze the effect of recording parameters on groove density, focal curve and imaging performance of the grating and their compensation. Based on Fermat' s principle, light path function and aberration, the effect on imaging performance of the grating was analyzed. In the case of fixed using parameters, the error of the recording angle has a greater influence on imaging performance, therefore the gain of the weight of recording angle can improve the accuracy of the recording angle values in the optimization; recording distance has little influence on imaging performance; the relative errors of recording parameters cause the change of imaging performance of the grating; the results indicate that recording parameter errors can be compensated by adjusting its corresponding parameter. The study can give theoretical guidance to the fabrication for high resolution varied-line-space plane holographic grating in on-line spectral diagnostic and reduce the alignment difficulty by analyze the main error effect the imaging performance and propose the compensation method.

  17. Development of the On-line Acoustic Leak Detection Tool for the SFR Steam Generator Protection

    International Nuclear Information System (INIS)

    Kim, Tae-Joon; Jeong, Ji-Young; Kim, Jong-Man; Kim, Byung-Ho; Kim, Seong-O

    2007-01-01

    The successful detection of a water/steam into a sodium leak in the SFR SG (steam generator) at an early phase of a leak origin depends on the fast response and sensitivity of a leak detection system. This intention of an acoustic leak detection system is stipulated by a key impossibility of a fast detecting of an intermediate leak by the present nominal systems such as the hydrogen meter. Subject of this study is to introduce the detection performance of an on-line acoustic leak detection tool discriminated by a back-propagation neural network with a preprocessing of the 1/m Octave band analysis, and to introduce the status of an on-line development being developed with the acoustic leak detection tool(S/W) in KAERI. For a performance test, it was used with the acoustic signals for a sodium-water reaction from the injected steam into water experiments in KAERI, the acoustic signals injected from the water into the sodium obtained in IPPE, and the background noise of the PFR superheater

  18. A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series

    Energy Technology Data Exchange (ETDEWEB)

    Chandola, Varun [ORNL; Vatsavai, Raju [ORNL

    2011-01-01

    Online time series change detection is a critical component of many monitoring systems, such as space and air-borne remote sensing instruments, cardiac monitors, and network traffic profilers, which continuously analyze observations recorded by sensors. Data collected by such sensors typically has a periodic (seasonal) component. Most existing time series change detection methods are not directly applicable to handle such data, either because they are not designed to handle periodic time series or because they cannot operate in an online mode. We propose an online change detection algorithm which can handle periodic time series. The algorithm uses a Gaussian process based non-parametric time series prediction model and monitors the difference between the predictions and actual observations within a statistically principled control chart framework to identify changes. A key challenge in using Gaussian process in an online mode is the need to solve a large system of equations involving the associated covariance matrix which grows with every time step. The proposed algorithm exploits the special structure of the covariance matrix and can analyze a time series of length T in O(T^2) time while maintaining a O(T) memory footprint, compared to O(T^4) time and O(T^2) memory requirement of standard matrix manipulation methods. We experimentally demonstrate the superiority of the proposed algorithm over several existing time series change detection algorithms on a set of synthetic and real time series. Finally, we illustrate the effectiveness of the proposed algorithm for identifying land use land cover changes using Normalized Difference Vegetation Index (NDVI) data collected for an agricultural region in Iowa state, USA. Our algorithm is able to detect different types of changes in a NDVI validation data set (with ~80% accuracy) which occur due to crop type changes as well as disruptive changes (e.g., natural disasters).

  19. Real-time beam monitoring for error detection in IMRT plans and impact on dose-volume histograms. A multi-center study

    Energy Technology Data Exchange (ETDEWEB)

    Marrazzo, Livia; Arilli, Chiara; Casati, Marta [Careggi University Hospital, Medical Physic Unit, Florence (Italy); Pasler, Marlies [Lake Constance Radiation Oncology Center, Singen-Friedrichshafen (Germany); Kusters, Martijn; Canters, Richard [Radboud University Medical Center, Department of Radiation Oncology, Nijmegen (Netherlands); Fedeli, Luca; Calusi, Silvia [University of Florence, Department of Experimental and Clinical Biomedical Sciences ' ' Mario Serio' ' , Florence (Italy); Talamonti, Cinzia; Pallotta, Stefania [Careggi University Hospital, Medical Physic Unit, Florence (Italy); University of Florence, Department of Experimental and Clinical Biomedical Sciences ' ' Mario Serio' ' , Florence (Italy); Simontacchi, Gabriele [Careggi University Hospital, Radiation Oncology Unit, Florence (Italy); Livi, Lorenzo [University of Florence, Department of Experimental and Clinical Biomedical Sciences ' ' Mario Serio' ' , Florence (Italy); Careggi University Hospital, Radiation Oncology Unit, Florence (Italy)

    2018-03-15

    This study aimed to test the sensitivity of a transmission detector for online dose monitoring of intensity-modulated radiation therapy (IMRT) for detecting small delivery errors. Furthermore, the correlation of changes in detector output induced by small delivery errors with other metrics commonly employed to quantify the deviations between calculated and delivered dose distributions was investigated. Transmission detector measurements were performed at three institutions. Seven types of errors were induced in nine clinical step-and-shoot (S and S) IMRT plans by modifying the number of monitor units (MU) and introducing small deviations in leaf positions. Signal reproducibility was investigated for short- and long-term stability. Calculated dose distributions were compared in terms of γ passing rates and dose-volume histogram (DVH) metrics (e.g., D{sub mean}, D{sub x%}, V{sub x%}). The correlation between detector signal variations, γ passing rates, and DVH parameters was investigated. Both short- and long-term reproducibility was within 1%. Dose variations down to 1 MU (∇signal 1.1 ± 0.4%) as well as changes in field size and positions down to 1 mm (∇signal 2.6 ± 1.0%) were detected, thus indicating high error-detection sensitivity. A moderate correlation of detector signal was observed with γ passing rates (R{sup 2} = 0.57-0.70), while a good correlation was observed with DVH metrics (R{sup 2} = 0.75-0.98). The detector is capable of detecting small delivery errors in MU and leaf positions, and is thus a highly sensitive dose monitoring device for S and S IMRT for clinical practice. The results of this study indicate a good correlation of detector signal with DVH metrics; therefore, clinical action levels can be defined based on the presented data. (orig.) [German] In dieser Arbeit wurde die Sensitivitaet bezueglich der Fehlererkennung eines Transmissionsdetektors fuer die Online-Dosisueberwachung von intensitaetsmodulierter Strahlentherapie (IMRT

  20. What are incident reports telling us? A comparative study at two Australian hospitals of medication errors identified at audit, detected by staff and reported to an incident system.

    Science.gov (United States)

    Westbrook, Johanna I; Li, Ling; Lehnbom, Elin C; Baysari, Melissa T; Braithwaite, Jeffrey; Burke, Rosemary; Conn, Chris; Day, Richard O

    2015-02-01

    To (i) compare medication errors identified at audit and observation with medication incident reports; (ii) identify differences between two hospitals in incident report frequency and medication error rates; (iii) identify prescribing error detection rates by staff. Audit of 3291 patient records at two hospitals to identify prescribing errors and evidence of their detection by staff. Medication administration errors were identified from a direct observational study of 180 nurses administering 7451 medications. Severity of errors was classified. Those likely to lead to patient harm were categorized as 'clinically important'. Two major academic teaching hospitals in Sydney, Australia. Rates of medication errors identified from audit and from direct observation were compared with reported medication incident reports. A total of 12 567 prescribing errors were identified at audit. Of these 1.2/1000 errors (95% CI: 0.6-1.8) had incident reports. Clinically important prescribing errors (n = 539) were detected by staff at a rate of 218.9/1000 (95% CI: 184.0-253.8), but only 13.0/1000 (95% CI: 3.4-22.5) were reported. 78.1% (n = 421) of clinically important prescribing errors were not detected. A total of 2043 drug administrations (27.4%; 95% CI: 26.4-28.4%) contained ≥ 1 errors; none had an incident report. Hospital A had a higher frequency of incident reports than Hospital B, but a lower rate of errors at audit. Prescribing errors with the potential to cause harm frequently go undetected. Reported incidents do not reflect the profile of medication errors which occur in hospitals or the underlying rates. This demonstrates the inaccuracy of using incident frequency to compare patient risk or quality performance within or across hospitals. New approaches including data mining of electronic clinical information systems are required to support more effective medication error detection and mitigation. © The Author 2015. Published by Oxford University Press in association

  1. Novelty detection methods for online health monitoring and post data analysis of turbopumps

    International Nuclear Information System (INIS)

    Lei Hu; Niaoqing, Hu; Xinpeng, Zhang; Fengshou, Gu; Ming, Gao

    2013-01-01

    As novelty detection works when only normal data are available, it is of considerable promise for health monitoring in cases lacking fault samples and prior knowledge. We present two novelty detection methods for health monitoring of turbopumps in large-scale liquid propellant rocket engines. The first method is the adaptive Gaussian threshold model. This method is designed to monitor the vibration of the turbopumps online because it has minimal computational complexity and is easy for implementation in real time. The second method is the one-class support vector machine (OCSVM) which is developed for post analysis of historical vibration signals. Via post analysis the method not only confirms the online monitoring results but also provides diagnostic results so that faults from sensors are separated from those actually from the turbopumps. Both of these two methods are validated to be efficient for health monitoring of the turbopumps.

  2. The application of CPLD in online nuclear detection meter of ore grade

    International Nuclear Information System (INIS)

    Yin Yiqiang; Yin Deyou; Gong Yalin; Shang Qingmin; Xiao Xiandong; Zhou Hongjun; Yu Haiming

    2010-01-01

    The pulse height analysis circuit for nuclear pulse signals is an important function cell of online nuclear detection meter, requiring high speed and credible logic circuit to eliminate the signal pileup rejection, overload detection, instrumentation measurement dead time on the adverse effects of spectrum. In order to improve the performance of nuclear detection meter, some function circuits are used, such as live time offset, overload detection and pileup rejection. The CPLD and multi single-channel spectrum measurement method used in ore grade nuclear instrumentation, eliminating the pileup, overload signal and accurately compensated the measurement of dead time, thus the circuit functions above are carried out credibly and the meter detection accuracy is improved drastically. (authors)

  3. Automatic on-line detection system design research on internal defects of metal materials based on optical fiber F-P sensing technology

    Science.gov (United States)

    Xia, Liu; Shan, Ning; Chao, Ban; Caoshan, Wang

    2016-10-01

    Metal materials have been used in aerospace and other industrial fields widely because of its excellent characteristics, so its internal defects detection is very important. Ultrasound technology is used widely in the fields of nondestructive detection because of its excellent characteristic. But the conventional detection instrument for ultrasound, which has shortcomings such as low intelligent level and long development cycles, limits its development. In this paper, the theory of ultrasound detection is analyzed. A computational method of the defects distributional position is given. The non-contact type optical fiber F-P interference cavity structure is designed and the length of origin cavity is given. The real-time on-line ultrasound detecting experiment devices for internal defects of metal materials is established based on the optical fiber F-P sensing system. The virtual instrument of automation ultrasound detection internal defects is developed based on LabVIEW software and the experimental study is carried out. The results show that this system can be used in internal defect real-time on-line locating of engineering structures effectively. This system has higher measurement precision. Relative error is 6.7%. It can be met the requirement of engineering practice. The system is characterized by simple operation, easy realization. The software has a friendly interface, good expansibility, and high intelligent level.

  4. Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit.

    Science.gov (United States)

    Ni, Yizhao; Lingren, Todd; Hall, Eric S; Leonard, Matthew; Melton, Kristin; Kirkendall, Eric S

    2018-05-01

    Timely identification of medication administration errors (MAEs) promises great benefits for mitigating medication errors and associated harm. Despite previous efforts utilizing computerized methods to monitor medication errors, sustaining effective and accurate detection of MAEs remains challenging. In this study, we developed a real-time MAE detection system and evaluated its performance prior to system integration into institutional workflows. Our prospective observational study included automated MAE detection of 10 high-risk medications and fluids for patients admitted to the neonatal intensive care unit at Cincinnati Children's Hospital Medical Center during a 4-month period. The automated system extracted real-time medication use information from the institutional electronic health records and identified MAEs using logic-based rules and natural language processing techniques. The MAE summary was delivered via a real-time messaging platform to promote reduction of patient exposure to potential harm. System performance was validated using a physician-generated gold standard of MAE events, and results were compared with those of current practice (incident reporting and trigger tools). Physicians identified 116 MAEs from 10 104 medication administrations during the study period. Compared to current practice, the sensitivity with automated MAE detection was improved significantly from 4.3% to 85.3% (P = .009), with a positive predictive value of 78.0%. Furthermore, the system showed potential to reduce patient exposure to harm, from 256 min to 35 min (P patient exposure to potential harm following MAE events.

  5. Improvement in Detection of Wrong-Patient Errors When Radiologists Include Patient Photographs in Their Interpretation of Portable Chest Radiographs.

    Science.gov (United States)

    Tridandapani, Srini; Olsen, Kevin; Bhatti, Pamela

    2015-12-01

    This study was conducted to determine whether facial photographs obtained simultaneously with radiographs improve radiologists' detection rate of wrong-patient errors, when they are explicitly asked to include the photographs in their evaluation. Radiograph-photograph combinations were obtained from 28 patients at the time of portable chest radiography imaging. From these, pairs of radiographs were generated. Each unique pair consisted of one new and one old (comparison) radiograph. Twelve pairs of mismatched radiographs (i.e., pairs containing radiographs of different patients) were also generated. In phase 1 of the study, 5 blinded radiologist observers were asked to interpret 20 pairs of radiographs without the photographs. In phase 2, each radiologist interpreted another 20 pairs of radiographs with the photographs. Radiologist observers were not instructed about the purpose of the photographs but were asked to include the photographs in their review. The detection rate of mismatched errors was recorded along with the interpretation time for each session for each observer. The two-tailed Fisher exact test was used to evaluate differences in mismatch detection rates between the two phases. A p value of error detection rates without (0/20 = 0%) and with (17/18 = 94.4%) photographs were different (p = 0.0001). The average interpretation times for the set of 20 radiographs were 26.45 (SD 8.69) and 20.55 (SD 3.40) min, for phase 1 and phase 2, respectively (two-tailed Student t test, p = 0.1911). When radiologists include simultaneously obtained photographs in their review of portable chest radiographs, there is a significant improvement in the detection of labeling errors. No statistically significant difference in interpretation time was observed. This may lead to improved patient safety without affecting radiologists' throughput.

  6. Detection of patient setup errors with a portal image - DRR registration software application.

    Science.gov (United States)

    Sutherland, Kenneth; Ishikawa, Masayori; Bengua, Gerard; Ito, Yoichi M; Miyamoto, Yoshiko; Shirato, Hiroki

    2011-02-18

    The purpose of this study was to evaluate a custom portal image - digitally reconstructed radiograph (DRR) registration software application. The software works by transforming the portal image into the coordinate space of the DRR image using three control points placed on each image by the user, and displaying the fused image. In order to test statistically that the software actually improves setup error estimation, an intra- and interobserver phantom study was performed. Portal images of anthropomorphic thoracic and pelvis phantoms with virtually placed irradiation fields at known setup errors were prepared. A group of five doctors was first asked to estimate the setup errors by examining the portal and DRR image side-by-side, not using the software. A second group of four technicians then estimated the same set of images using the registration software. These two groups of human subjects were then compared with an auto-registration feature of the software, which is based on the mutual information between the portal and DRR images. For the thoracic case, the average distance between the actual setup error and the estimated error was 4.3 ± 3.0 mm for doctors using the side-by-side method, 2.1 ± 2.4 mm for technicians using the registration method, and 0.8 ± 0.4mm for the automatic algorithm. For the pelvis case, the average distance between the actual setup error and estimated error was 2.0 ± 0.5 mm for the doctors using the side-by-side method, 2.5 ± 0.4 mm for technicians using the registration method, and 2.0 ± 1.0 mm for the automatic algorithm. The ability of humans to estimate offset values improved statistically using our software for the chest phantom that we tested. Setup error estimation was further improved using our automatic error estimation algorithm. Estimations were not statistically different for the pelvis case. Consistency improved using the software for both the chest and pelvis phantoms. We also tested the automatic algorithm with a

  7. The importance of intra-hospital pharmacovigilance in the detection of medication errors

    Science.gov (United States)

    Villegas, Francisco; Figueroa-Montero, David; Barbero-Becerra, Varenka; Juárez-Hernández, Eva; Uribe, Misael; Chávez-Tapia, Norberto; González-Chon, Octavio

    2018-01-01

    Hospitalized patients are susceptible to medication errors, which represent between the fourth and the sixth cause of death. The department of intra-hospital pharmacovigilance intervenes in the entire process of medication with the purpose to prevent, repair and assess damages. To analyze medication errors reported by Mexican Fundación Clínica Médica Sur pharmacovigilance system and their impact on patients. Prospective study carried out from 2012 to 2015, where medication prescriptions given to patients were recorded. Owing to heterogeneity, data were described as absolute numbers in a logarithmic scale. 292 932 prescriptions of 56 368 patients were analyzed, and 8.9% of medication errors were identified. The treating physician was responsible of 83.32% of medication errors, residents of 6.71% and interns of 0.09%. No error caused permanent damage or death. This is the pharmacovigilance study with the largest sample size reported. Copyright: © 2018 SecretarÍa de Salud.

  8. Residual setup errors caused by rotation and non-rigid motion in prone-treated cervical cancer patients after online CBCT image-guidance

    International Nuclear Information System (INIS)

    Ahmad, Rozilawati; Hoogeman, Mischa S.; Quint, Sandra; Mens, Jan Willem; Osorio, Eliana M. Vásquez; Heijmen, Ben J.M.

    2012-01-01

    Purpose: To quantify the impact of uncorrected or partially corrected pelvis rotation and spine bending on region-specific residual setup errors in prone-treated cervical cancer patients. Methods and materials: Fifteen patients received an in-room CBCT scan twice a week. CBCT scans were registered to the planning CT-scan using a pelvic clip box and considering both translations and rotations. For daily correction of the detected translational pelvis setup errors by couch shifts, residual setup errors were determined for L5, L4 and seven other points of interest (POIs). The same was done for a procedure with translational corrections and limited rotational correction (±3°) by a 6D positioning device. Results: With translational correction only, residual setup errors were large especially for L5/L4 in AP direction (Σ = 5.1/5.5 mm). For the 7 POIs the residual setup errors ranged from 1.8 to 5.6 mm (AP). Using the 6D positioning device, the errors were substantially smaller (for L5/L4 in AP direction Σ = 2.7/2.2 mm). Using this device, the percentage of fractions with a residual AP displacement for L4 > 5 mm reduced from 47% to 9%. Conclusions: Setup variations caused by pelvis rotations are large and cannot be ignored in prone treatment of cervical cancer patients. Corrections with a 6D positioning device may considerably reduce resulting setup errors, but the residual setup errors should still be accounted for by appropriate CTV-to-PTV margins.

  9. Uncertain Reasoning for Detection of Selling Stolen Goods in Online Auctions Using Contextual Information

    Directory of Open Access Journals (Sweden)

    Ladislav Beranek

    2014-01-01

    Full Text Available This work describes the design of a decision support system for detection of fraudulent behavior of selling stolen goods in online auctions. In this system, each seller is associated with a type of certification, namely “proper seller,” “suspect seller,” and “selling stolen goods.” The certification level is determined on the basis of a seller’s behaviors and especially on the basis of contextual information whose origin is outside online auctions portals. In this paper, we focus on representing knowledge about sellers in online auctions, the influence of additional information available from other Internet source, and reasoning on bidders’ trustworthiness under uncertainties using Dempster-Shafer theory of evidence. To demonstrate the practicability of our approach, we performed a case study using real auction data from Czech auction portal Aukro. The analysis results show that our approach can be used to detect selling stolen goods. By applying Dempster-Shafer theory to combine multiple sources of evidence for the detection of this fraudulent behavior, the proposed approach can reduce the number of false positive results in comparison to approaches using a single source of evidence.

  10. WE-AB-BRA-09: Sensitivity of Plan Re-Optimization to Errors in Deformable Image Registration in Online Adaptive Image-Guided Radiation Therapy

    International Nuclear Information System (INIS)

    McClain, B; Olsen, J; Green, O; Yang, D; Santanam, L; Olsen, L; Zhao, T; Rodriguez, V; Wooten, H; Mutic, S; Kashani, R; Victoria, J; Dempsey, J

    2015-01-01

    Purpose: Online adaptive therapy (ART) relies on auto-contouring using deformable image registration (DIR). DIR’s inherent uncertainties require user intervention and manual edits while the patient is on the table. We investigated the dosimetric impact of DIR errors on the quality of re-optimized plans, and used the findings to establish regions for focusing manual edits to where DIR errors can Result in clinically relevant dose differences. Methods: Our clinical implementation of online adaptive MR-IGRT involves using DIR to transfer contours from CT to daily MR, followed by a physicians’ edits. The plan is then re-optimized to meet the organs at risk (OARs) constraints. Re-optimized abdomen and pelvis plans generated based on physician edited OARs were selected as the baseline for evaluation. Plans were then re-optimized on auto-deformed contours with manual edits limited to pre-defined uniform rings (0 to 5cm) around the PTV. A 0cm ring indicates that the auto-deformed OARs were used without editing. The magnitude of the variations caused by the non-deterministic optimizer was quantified by repeat re-optimizations on the same geometry to determine the mean and standard deviation (STD). For each re-optimized plan, various volumetric parameters for the PTV, the OARs were extracted along with DVH and isodose evaluation. A plan was deemed acceptable if the variation from the baseline plan was within one STD. Results: Initial results show that for abdomen and pancreas cases, a minimum of 5cm margin around the PTV is required for contour corrections, while for pelvic and liver cases a 2–3 cm margin is sufficient. Conclusion: Focusing manual contour edits to regions of dosimetric relevance can reduce contouring time in the online ART process while maintaining a clinically comparable plan. Future work will further refine the contouring region by evaluating the path along the beams, dose gradients near the target and OAR dose metrics

  11. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features.

    Science.gov (United States)

    Grimm, Lars J; Ghate, Sujata V; Yoon, Sora C; Kuzmiak, Cherie M; Kim, Connie; Mazurowski, Maciej A

    2014-03-01

    The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502-0.739, 95% Confidence Interval: 0.543-0.680,p errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

  12. Extending Dylan's type system for better type inference and error detection

    DEFF Research Database (Denmark)

    Mehnert, Hannes

    2010-01-01

    a dynamically typed language. Dylan poses several special challenges for gradual typing, such as multiple return values, variable-arity methods and generic functions (multiple dispatch). In this paper Dylan is extended with function types and parametric polymorphism. We implemented the type system...... and aunification-based type inference algorithm in the mainstream Dylan compiler. As case study we use the Dylan standard library (roughly 32000 lines of code), which witnesses that the implementation generates faster code with fewer errors. Some previously undiscovered errors in the Dylan library were revealed....

  13. Development of online cable eccentricity detection system based on X-ray CCD

    International Nuclear Information System (INIS)

    Chen Jianzhen; Li Bin; Wei Kaixia; Guo Lanying; Qu Guopu

    2008-01-01

    An improved technology of online cable eccentricity detection, based on X-ray CCD, greatly improves the measuring precision and the responding speed. The theory of eccentricity measuring based on X-ray CCD, and the structure of an apparatus are described. The apparatus is composed of scanning drive subsystem, X-ray generation components, data acquiring subsystem and high performance computer system. The measuring results are also presented. The features of this cable eccentricity detection technology are compared with the features of other technologies. (authors)

  14. Assessing segmentation processes by click detection: online measure of statistical learning, or simple interference?

    Science.gov (United States)

    Franco, Ana; Gaillard, Vinciane; Cleeremans, Axel; Destrebecqz, Arnaud

    2015-12-01

    Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212-223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.

  15. Measuring and detecting errors in occupational coding: an analysis of SHARE data

    NARCIS (Netherlands)

    Belloni, M.; Brugiavini, A.; Meschi, E.; Tijdens, K.

    2016-01-01

    This article studies coding errors in occupational data, as the quality of this data is important but often neglected. In particular, we recoded open-ended questions on occupation for last and current job in the Dutch sample of the “Survey of Health, Ageing and Retirement in Europe” (SHARE) using a

  16. Leveraging Automatic Speech Recognition Errors to Detect Challenging Speech Segments in TED Talks

    Science.gov (United States)

    Mirzaei, Maryam Sadat; Meshgi, Kourosh; Kawahara, Tatsuya

    2016-01-01

    This study investigates the use of Automatic Speech Recognition (ASR) systems to epitomize second language (L2) listeners' problems in perception of TED talks. ASR-generated transcripts of videos often involve recognition errors, which may indicate difficult segments for L2 listeners. This paper aims to discover the root-causes of the ASR errors…

  17. Sharp Threshold Detection Based on Sup-norm Error rates in High-dimensional Models

    DEFF Research Database (Denmark)

    Callot, Laurent; Caner, Mehmet; Kock, Anders Bredahl

    focused almost exclusively on estimation errors in stronger norms. We show that this sup-norm bound can be used to distinguish between zero and non-zero coefficients at a much finer scale than would have been possible using classical oracle inequalities. Thus, our sup-norm bound is tailored to consistent...

  18. Developing an EEG based On-line Closed-loop Lapse Detection and Mitigation System

    Directory of Open Access Journals (Sweden)

    Yu-Te eWang

    2014-10-01

    Full Text Available In America, sixty percent of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-realty environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory feedback was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing feedback to subjects suffering momentary cognitive lapses, and assess the efficacy of the feedback in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.

  19. Developing an EEG-based on-line closed-loop lapse detection and mitigation system.

    Science.gov (United States)

    Wang, Yu-Te; Huang, Kuan-Chih; Wei, Chun-Shu; Huang, Teng-Yi; Ko, Li-Wei; Lin, Chin-Teng; Cheng, Chung-Kuan; Jung, Tzyy-Ping

    2014-01-01

    In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.

  20. On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

    Directory of Open Access Journals (Sweden)

    Mark Frogley

    2013-01-01

    Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.

  1. FPGA-Based Online PQD Detection and Classification through DWT, Mathematical Morphology and SVD

    Directory of Open Access Journals (Sweden)

    Misael Lopez-Ramirez

    2018-03-01

    Full Text Available Power quality disturbances (PQD in electric distribution systems can be produced by the utilization of non-linear loads or environmental circumstances, causing electrical equipment malfunction and reduction of its useful life. Detecting and classifying different PQDs implies great efforts in planning and structuring the monitoring system. The main disadvantage of most works in the literature is that they treat a limited number of electrical disturbances through personal computer (PC-based computation techniques, which makes it difficult to perform an online PQD classification. In this work, the novel contribution is a methodology for PQD recognition and classification through discrete wavelet transform, mathematical morphology, decomposition of singular values, and statistical analysis. Furthermore, the timely and reliable classification of different disturbances is necessary; hence, a field programmable gate array (FPGA-based integrated circuit is developed to offer a portable hardware processing unit to perform fast, online PQD classification. The obtained numerical and experimental results demonstrate that the proposed method guarantees high effectiveness during online PQD detection and classification of real voltage/current signals.

  2. Secure access control and large scale robust representation for online multimedia event detection.

    Science.gov (United States)

    Liu, Changyu; Lu, Bin; Li, Huiling

    2014-01-01

    We developed an online multimedia event detection (MED) system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC) model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK) event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.

  3. Secure Access Control and Large Scale Robust Representation for Online Multimedia Event Detection

    Directory of Open Access Journals (Sweden)

    Changyu Liu

    2014-01-01

    Full Text Available We developed an online multimedia event detection (MED system. However, there are a secure access control issue and a large scale robust representation issue when we want to integrate traditional event detection algorithms into the online environment. For the first issue, we proposed a tree proxy-based and service-oriented access control (TPSAC model based on the traditional role based access control model. Verification experiments were conducted on the CloudSim simulation platform, and the results showed that the TPSAC model is suitable for the access control of dynamic online environments. For the second issue, inspired by the object-bank scene descriptor, we proposed a 1000-object-bank (1000OBK event descriptor. Feature vectors of the 1000OBK were extracted from response pyramids of 1000 generic object detectors which were trained on standard annotated image datasets, such as the ImageNet dataset. A spatial bag of words tiling approach was then adopted to encode these feature vectors for bridging the gap between the objects and events. Furthermore, we performed experiments in the context of event classification on the challenging TRECVID MED 2012 dataset, and the results showed that the robust 1000OBK event descriptor outperforms the state-of-the-art approaches.

  4. DOSEmanPRO - active electronic online personal air sampler for detection of radon progeny long lived alpha nuclides

    International Nuclear Information System (INIS)

    Streil, T.; Oeser, V.

    2002-01-01

    Full text: Using the micro system - technology we developed a online personal air sampler not bigger than a mobile phone, to open a new dimension in personal dosimetry of inhaled radioactive aerosols. The DOSEman PRO containing an internal pump with a continuous air flow of 0.15 I/min sample the radon progeny or other nuclides on a millipore filter with excellent spectroscopic resolution. A 1.5 cm 2 light protected ion-implanted silicon detector analyses the alpha radiation at the filter. This small detector head contains also the pre amplification and pulse processing. The alpha radiation of the radon progeny and the long lived alpha nuclides is analyzed by a 60 channel spectrometer. The energy resolution of the online analyzed filter spectra is in the order of 150 keV. Mechanical and electronic design enables one to distinguish the long lived alpha nuclides from the radon and thoron progeny very easily. Using a special algorithm we correct the influence of the tailing of the radon progeny to the long lived alpha nuclides and take into consideration possible interference in determining the long lived alpha nuclides. Because of the air sampling volume of nearly 10 I/h, the system has a high efficiency. The detection limit by 2 hours sampling time is 0.05 Bq/m 3 alpha nuclide concentration. In a modified device for air sampling especially of long-lived alpha nuclides like uranium, radium or plutonium, the flow rate is increased to 0,3 1/min e.g. during a 10 h sampling period we can detect 0.005 Bq/m 3 in a low radon atmosphere. Assuming increased radon progeny concentration, the statistical error for the long lived alpha nuclides will be higher, but in most of the cases for use in nuclear facilities low radon concentrations are ambient conditions. This concept of an electronic personal air sampler with an alpha spectroscopy offers some outstanding advantages compared to passive dosimeters or off-line alpha air filters: The dose value and the nuclide concentration is

  5. Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions

    Directory of Open Access Journals (Sweden)

    Zuojin Li

    2017-03-01

    Full Text Available This paper presents a drowsiness on-line detection system for monitoring driver fatigue level under real driving conditions, based on the data of steering wheel angles (SWA collected from sensors mounted on the steering lever. The proposed system firstly extracts approximate entropy (ApEnfeaturesfromfixedslidingwindowsonreal-timesteeringwheelanglestimeseries. Afterthat, this system linearizes the ApEn features series through an adaptive piecewise linear fitting using a given deviation. Then, the detection system calculates the warping distance between the linear features series of the sample data. Finally, this system uses the warping distance to determine the drowsiness state of the driver according to a designed binary decision classifier. The experimental data were collected from 14.68 h driving under real road conditions, including two fatigue levels: “wake” and “drowsy”. The results show that the proposed system is capable of working online with an average 78.01% accuracy, 29.35% false detections of the “awake” state, and 15.15% false detections of the “drowsy” state. The results also confirm that the proposed method based on SWA signal is valuable for applications in preventing traffic accidents caused by driver fatigue.

  6. Automatic detection of patient identification and positioning errors in radiotherapy treatment using 3D setup images

    OpenAIRE

    Jani, Shyam

    2015-01-01

    The success of modern radiotherapy treatment depends on the correct alignment of the radiation beams with the target region in the patient. In the conventional paradigm of image-guided radiation therapy, 2D or 3D setup images are taken immediately prior to treatment and are used by radiation therapy technologists to localize the patient to the same position as defined from the reference planning CT dataset. However, numerous reports in the literature have described errors during this step, wh...

  7. [The fate of scientific articles when errors and scientific misconduct are detected].

    Science.gov (United States)

    Vinther, Siri; Rosenberg, Jacob

    2014-01-20

    When a minor error is noted in a scientific article, the publishing journal should issue a correction. Issuing an expression of concern is relevant when scientific misconduct is suspected. If the suspicion proves to be well founded, the journal should retract the article. The number of retractions is increasing, and this emphasizes the need for unequivocal concepts and guidelines. The reason a given article is corrected or retracted should be unambiguous and articles as well as notices should be indexed properly.

  8. Development of a Compton camera for online ion beam range verification via prompt γ detection

    Energy Technology Data Exchange (ETDEWEB)

    Aldawood, S. [LMU Munich, Garching (Germany); King Saud University, Riyadh (Saudi Arabia); Liprandi, S.; Marinsek, T.; Bortfeldt, J.; Lang, C.; Lutter, R.; Dedes, G.; Parodi, K.; Thirolf, P.G. [LMU Munich, Garching (Germany); Maier, L.; Gernhaeuser, R. [TU Munich, Garching (Germany); Kolff, H. van der [LMU Munich, Garching (Germany); TU Delft (Netherlands); Castelhano, I. [LMU Munich, Garching (Germany); University of Lisbon, Lisbon (Portugal); Schaart, D.R. [TU Delft (Netherlands)

    2015-07-01

    Precise and preferably online ion beam range verification is a mandatory prerequisite to fully exploit the advantages of hadron therapy in cancer treatment. An imaging system is being developed in Garching aiming to detect promptγ rays induced by nuclear reactions between the ion beam and biological tissue. The Compton camera prototype consists of a stack of six customized double-sided Si-strip detectors (DSSSD, 50 x 50 mm{sup 2}, 0.5 mm thick, 128 strips/side) acting as scatterer, while the absorber is formed by a monolithic LaBr{sub 3}:Ce scintillator crystal (50 x 50 x 30 mm{sup 3}) read out by a position-sensitive multi-anode photomultiplier (Hamamatsu H9500). The on going characterization of the Compton camera properties and its individual components both offline in the laboratory as well as online using proton beam are presented.

  9. First online real-time evaluation of motion-induced 4D dose errors during radiotherapy delivery

    DEFF Research Database (Denmark)

    Ravkilde, Thomas; Skouboe, Simon; Hansen, Rune

    2018-01-01

    PURPOSE: In radiotherapy, dose deficits caused by tumor motion often far outweigh the discrepancies typically allowed in plan-specific quality assurance (QA). Yet, tumor motion is not usually included in present QA. We here present a novel method for online treatment verification by real......-time motion-including 4D dose reconstruction and dose evaluation and demonstrate its use during stereotactic body radiotherapy (SBRT) delivery with and without MLC tracking. METHODS: Five volumetric modulated arc therapy (VMAT) plans were delivered with and without MLC tracking to a motion stage carrying...... a Delta4 dosimeter. The VMAT plans have previously been used for (non-tracking) liver SBRT with intra-treatment tumor motion recorded by kilovoltage intrafraction monitoring (KIM). The motion stage reproduced the KIM-measured tumor motions in 3D while optical monitoring guided the MLC tracking. Linac...

  10. Limit of detection in the presence of instrumental and non-instrumental errors: study of the possible sources of error and application to the analysis of 41 elements at trace levels by inductively coupled plasma-mass spectrometry technique

    International Nuclear Information System (INIS)

    Badocco, Denis; Lavagnini, Irma; Mondin, Andrea; Tapparo, Andrea; Pastore, Paolo

    2015-01-01

    In this paper the detection limit was estimated when signals were affected by two error contributions, namely instrumental errors and operational-non-instrumental errors. The detection limit was theoretically obtained following the hypothesis testing schema implemented with the calibration curve methodology. The experimental calibration design was based on J standards measured I times with non-instrumental errors affecting each standard systematically but randomly among the J levels. A two-component variance regression was performed to determine the calibration curve and to define the detection limit in these conditions. The detection limit values obtained from the calibration at trace levels of 41 elements by ICP-MS resulted larger than those obtainable from a one component variance regression. The role of the reagent impurities on the instrumental errors was ascertained and taken into account. Environmental pollution was studied as source of non-instrumental errors. The environmental pollution role was evaluated by Principal Component Analysis technique (PCA) applied to a series of nine calibrations performed in fourteen months. The influence of the seasonality of the environmental pollution on the detection limit was evidenced for many elements usually present in the urban air particulate. The obtained results clearly indicated the need of using the two-component variance regression approach for the calibration of all the elements usually present in the environment at significant concentration levels. - Highlights: • Limit of detection was obtained considering a two variance component regression. • Calibration data may be affected by instrumental and operational conditions errors. • Calibration model was applied to determine 41 elements at trace level by ICP-MS. • Non instrumental errors were evidenced by PCA analysis

  11. Detection and Localization of Tooth Breakage Fault on Wind Turbine Planetary Gear System considering Gear Manufacturing Errors

    Directory of Open Access Journals (Sweden)

    Y. Gui

    2014-01-01

    Full Text Available Sidebands of vibration spectrum are sensitive to the fault degree and have been proved to be useful for tooth fault detection and localization. However, the amplitude and frequency modulation due to manufacturing errors (which are inevitable in actual planetary gear system lead to much more complex sidebands. Thus, in the paper, a lumped parameter model for a typical planetary gear system with various types of errors is established. In the model, the influences of tooth faults on time-varying mesh stiffness and tooth impact force are derived analytically. Numerical methods are then utilized to obtain the response spectra of the system with tooth faults with and without errors. Three system components (including sun, planet, and ring gears with tooth faults are considered in the discussion, respectively. Through detailed comparisons of spectral sidebands, fault characteristic frequencies of the system are acquired. Dynamic experiments on a planetary gear-box test rig are carried out to verify the simulation results and these results are of great significances for the detection and localization of tooth faults in wind turbines.

  12. On the robustness of EC-PC spike detection method for online neural recording.

    Science.gov (United States)

    Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

    2014-09-30

    Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Quality controls in integrative approaches to detect errors and inconsistencies in biological databases

    Directory of Open Access Journals (Sweden)

    Ghisalberti Giorgio

    2010-12-01

    Full Text Available Numerous biomolecular data are available, but they are scattered in many databases and only some of them are curated by experts. Most available data are computationally derived and include errors and inconsistencies. Effective use of available data in order to derive new knowledge hence requires data integration and quality improvement. Many approaches for data integration have been proposed. Data warehousing seams to be the most adequate when comprehensive analysis of integrated data is required. This makes it the most suitable also to implement comprehensive quality controls on integrated data. We previously developed GFINDer (http://www.bioinformatics.polimi.it/GFINDer/, a web system that supports scientists in effectively using available information. It allows comprehensive statistical analysis and mining of functional and phenotypic annotations of gene lists, such as those identified by high-throughput biomolecular experiments. GFINDer backend is composed of a multi-organism genomic and proteomic data warehouse (GPDW. Within the GPDW, several controlled terminologies and ontologies, which describe gene and gene product related biomolecular processes, functions and phenotypes, are imported and integrated, together with their associations with genes and proteins of several organisms. In order to ease maintaining updated the GPDW and to ensure the best possible quality of data integrated in subsequent updating of the data warehouse, we developed several automatic procedures. Within them, we implemented numerous data quality control techniques to test the integrated data for a variety of possible errors and inconsistencies. Among other features, the implemented controls check data structure and completeness, ontological data consistency, ID format and evolution, unexpected data quantification values, and consistency of data from single and multiple sources. We use the implemented controls to analyze the quality of data available from several

  14. On the Optimal Detection and Error Performance Analysis of the Hardware Impaired Systems

    KAUST Repository

    Javed, Sidrah; Amin, Osama; Ikki, Salama S.; Alouini, Mohamed-Slim

    2018-01-01

    The conventional minimum Euclidean distance (MED) receiver design is based on the assumption of ideal hardware transceivers and proper Gaussian noise in communication systems. Throughout this study, an accurate statistical model of various hardware impairments (HWIs) is presented. Then, an optimal maximum likelihood (ML) receiver is derived considering the distinct characteristics of the HWIs comprised of additive improper Gaussian noise and signal distortion. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds are derived. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver and the tightness of the derived bounds.

  15. On the Optimal Detection and Error Performance Analysis of the Hardware Impaired Systems

    KAUST Repository

    Javed, Sidrah

    2018-01-15

    The conventional minimum Euclidean distance (MED) receiver design is based on the assumption of ideal hardware transceivers and proper Gaussian noise in communication systems. Throughout this study, an accurate statistical model of various hardware impairments (HWIs) is presented. Then, an optimal maximum likelihood (ML) receiver is derived considering the distinct characteristics of the HWIs comprised of additive improper Gaussian noise and signal distortion. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds are derived. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver and the tightness of the derived bounds.

  16. Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Yun-Long Kong

    2018-03-01

    Full Text Available A satellite image time series (SITS contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natural events (for example, fires, floods, plant diseases, and insect pests and human activities (for example, deforestation and urbanisation will disturb this pattern and cause a relatively profound change on the Earth’s surface. These events are usually referred to as disturbances. However, disturbances in ecosystems are not easy to detect from SITS data, because SITS contain combined information on disturbances, phenological variations and noise in remote sensing data. In this paper, a novel framework is proposed for online disturbance detection from SITS. The framework is based on long short-term memory (LSTM networks. First, LSTM networks are trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Last, the predicted data are compared with real data, and the noticeable deviations reveal disturbances. Experimental results using 16-day compositions of the moderate resolution imaging spectroradiometer (MOD13Q1 illustrate the effectiveness and stability of the proposed approach for online disturbance detection.

  17. On-line detection of small radioactive ions by capillary electrophoresis

    International Nuclear Information System (INIS)

    Klunder, G.L.; Andrews, J.E. Jr.; Russo, R.E.

    1994-01-01

    Worldwide environmental interests have placed a great demand on developing techniques for rapid characterization of contaminated soil and groundwater. Detection of radioactive contaminants is necessary for monitoring effluents from nuclear processes or to assure proper long term storage of radioactive waste. The authors have been investigating the chemistry required to separate representative radioactive small cations and anions by capillary electrophoresis. In order to evaluate the separation chemistry, detection of stable isotopes of the representative ions was achieved by indirect absorption for cations and direct absorption for anions. Several buffer systems which have been considered in the optimization of the separations will be discussed. The authors have designed and tested two on-line radioactivity detectors for capillary electrophoresis. An on-line solid state CdTe detector was constructed for this study and a scintillation detector has been designed using a high gain photodiode light sensor. Different scintillation materials have been tested. Comparison of the detectors, design considerations, efficiency and limits of detection will be presented

  18. Threshold-based detection for amplify-and-forward cooperative communication systems with channel estimation error

    KAUST Repository

    Abuzaid, Abdulrahman I.

    2014-09-01

    Efficient receiver designs for cooperative communication systems are becoming increasingly important. In previous work, cooperative networks communicated with the use of $L$ relays. As the receiver is constrained, it can only process $U$ out of $L$ relays. Channel shortening and reduced-rank techniques were employed to design the preprocessing matrix. In this paper, a receiver structure is proposed which combines the joint iterative optimization (JIO) algorithm and our proposed threshold selection criteria. This receiver structure assists in determining the optimal $U-{opt}$. Furthermore, this receiver provides the freedom to choose $U ≤ U-{opt}$ for each frame depending upon the tolerable difference allowed for mean square error (MSE). Our study and simulation results show that by choosing an appropriate threshold, it is possible to gain in terms of complexity savings without affecting the BER performance of the system. Furthermore, in this paper the effect of channel estimation errors is investigated on the MSE performance of the amplify-and-forward (AF) cooperative relaying system.

  19. Improving staff response to seizures on the epilepsy monitoring unit with online EEG seizure detection algorithms.

    Science.gov (United States)

    Rommens, Nicole; Geertsema, Evelien; Jansen Holleboom, Lisanne; Cox, Fieke; Visser, Gerhard

    2018-05-11

    User safety and the quality of diagnostics on the epilepsy monitoring unit (EMU) depend on reaction to seizures. Online seizure detection might improve this. While good sensitivity and specificity is reported, the added value above staff response is unclear. We ascertained the added value of two electroencephalograph (EEG) seizure detection algorithms in terms of additional detected seizures or faster detection time. EEG-video seizure recordings of people admitted to an EMU over one year were included, with a maximum of two seizures per subject. All recordings were retrospectively analyzed using Encevis EpiScan and BESA Epilepsy. Detection sensitivity and latency of the algorithms were compared to staff responses. False positive rates were estimated on 30 uninterrupted recordings (roughly 24 h per subject) of consecutive subjects admitted to the EMU. EEG-video recordings used included 188 seizures. The response rate of staff was 67%, of Encevis 67%, and of BESA Epilepsy 65%. Of the 62 seizures missed by staff, 66% were recognized by Encevis and 39% by BESA Epilepsy. The median latency was 31 s (staff), 10 s (Encevis), and 14 s (BESA Epilepsy). After correcting for walking time from the observation room to the subject, both algorithms detected faster than staff in 65% of detected seizures. The full recordings included 617 h of EEG. Encevis had a median false positive rate of 4.9 per 24 h and BESA Epilepsy of 2.1 per 24 h. EEG-video seizure detection algorithms may improve reaction to seizures by improving the total number of seizures detected and the speed of detection. The false positive rate is feasible for use in a clinical situation. Implementation of these algorithms might result in faster diagnostic testing and better observation during seizures. Copyright © 2018. Published by Elsevier Inc.

  20. On-line automatic detection of wood pellets in pneumatically conveyed wood dust flow

    Science.gov (United States)

    Sun, Duo; Yan, Yong; Carter, Robert M.; Gao, Lingjun; Qian, Xiangchen; Lu, Gang

    2014-04-01

    This paper presents a piezoelectric transducer based system for on-line automatic detection of wood pellets in wood dust flow in pneumatic conveying pipelines. The piezoelectric transducer senses non-intrusively the collisions between wood pellets and the pipe wall. Wavelet-based denoising is adopted to eliminate environmental noise and recover the collision events. Then the wood pellets are identified by sliding a time window through the denoised signal with a suitable threshold. Experiments were carried out on a laboratory test rig and on an industrial pneumatic conveying pipeline to assess the effectiveness and operability of the system.

  1. Deception Detection: The Relationship of Levels of Trust and Perspective Taking in Real-Time Online and Offline Communication Environments.

    Science.gov (United States)

    Friend, Catherine; Fox Hamilton, Nicola

    2016-09-01

    Where humans have been found to detect lies or deception only at the rate of chance in offline face-to-face communication (F2F), computer-mediated communication (CMC) online can elicit higher rates of trust and sharing of personal information than F2F. How do levels of trust and empathetic personality traits like perspective taking (PT) relate to deception detection in real-time CMC compared to F2F? A between groups correlational design (N = 40) demonstrated that, through a paired deceptive conversation task with confederates, levels of participant trust could predict accurate detection online but not offline. Second, participant PT abilities could not predict accurate detection in either conversation medium. Finally, this study found that conversation medium also had no effect on deception detection. This study finds support for the effects of the Truth Bias and online disinhibition in deception, and further implications in law enforcement are discussed.

  2. A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

    Directory of Open Access Journals (Sweden)

    Xingwu Zhang

    2016-01-01

    Full Text Available Milling vibration is one of the most serious factors affecting machining quality and precision. In this paper a novel hybrid error criterion-based frequency-domain LMS active control method is constructed and used for vibration suppression of milling processes by piezoelectric actuators and sensors, in which only one Fast Fourier Transform (FFT is used and no Inverse Fast Fourier Transform (IFFT is involved. The correction formulas are derived by a steepest descent procedure and the control parameters are analyzed and optimized. Then, a novel hybrid error criterion is constructed to improve the adaptability, reliability and anti-interference ability of the constructed control algorithm. Finally, based on piezoelectric actuators and acceleration sensors, a simulation of a spindle and a milling process experiment are presented to verify the proposed method. Besides, a protection program is added in the control flow to enhance the reliability of the control method in applications. The simulation and experiment results indicate that the proposed method is an effective and reliable way for on-line vibration suppression, and the machining quality can be obviously improved.

  3. An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection

    Directory of Open Access Journals (Sweden)

    Sen Zhang

    2015-01-01

    Full Text Available The concentration of alumina in the electrolyte is of great significance during the production of aluminum; it may affect the stability of aluminum reduction cell and the current efficiency. However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell. At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement. In this paper, a novel soft sensing method based on a modified extreme learning machine (MELM for online measurement of the alumina concentration is proposed. The modified ELM algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references. It randomly chooses the input weights and analytically determines the output weights without manual intervention. The simulation results show that the approach can give more accurate estimations of alumina concentration with faster learning speed compared with other methods such as BP and SVM.

  4. Online extremism and the communities that sustain it: Detecting the ISIS supporting community on Twitter

    Science.gov (United States)

    Joseph, Kenneth; Carley, Kathleen M.

    2017-01-01

    The Islamic State of Iraq and ash-Sham (ISIS) continues to use social media as an essential element of its campaign to motivate support. On Twitter, ISIS’ unique ability to leverage unaffiliated sympathizers that simply retweet propaganda has been identified as a primary mechanism in their success in motivating both recruitment and “lone wolf” attacks. The present work explores a large community of Twitter users whose activity supports ISIS propaganda diffusion in varying degrees. Within this ISIS supporting community, we observe a diverse range of actor types, including fighters, propagandists, recruiters, religious scholars, and unaffiliated sympathizers. The interaction between these users offers unique insight into the people and narratives critical to ISIS’ sustainment. In their entirety, we refer to this diverse set of users as an online extremist community or OEC. We present Iterative Vertex Clustering and Classification (IVCC), a scalable analytic approach for OEC detection in annotated heterogeneous networks, and provide an illustrative case study of an online community of over 22,000 Twitter users whose online behavior directly advocates support for ISIS or contibutes to the group’s propaganda dissemination through retweets. PMID:29194446

  5. A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

    Science.gov (United States)

    Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

    2017-09-29

    The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

  6. A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

    Directory of Open Access Journals (Sweden)

    Rui Sun

    2017-09-01

    Full Text Available The use of Unmanned Aerial Vehicles (UAVs has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

  7. Generalized linear mixed model for binary outcomes when covariates are subject to measurement errors and detection limits.

    Science.gov (United States)

    Xie, Xianhong; Xue, Xiaonan; Strickler, Howard D

    2018-01-15

    Longitudinal measurement of biomarkers is important in determining risk factors for binary endpoints such as infection or disease. However, biomarkers are subject to measurement error, and some are also subject to left-censoring due to a lower limit of detection. Statistical methods to address these issues are few. We herein propose a generalized linear mixed model and estimate the model parameters using the Monte Carlo Newton-Raphson (MCNR) method. Inferences regarding the parameters are made by applying Louis's method and the delta method. Simulation studies were conducted to compare the proposed MCNR method with existing methods including the maximum likelihood (ML) method and the ad hoc approach of replacing the left-censored values with half of the detection limit (HDL). The results showed that the performance of the MCNR method is superior to ML and HDL with respect to the empirical standard error, as well as the coverage probability for the 95% confidence interval. The HDL method uses an incorrect imputation method, and the computation is constrained by the number of quadrature points; while the ML method also suffers from the constrain for the number of quadrature points, the MCNR method does not have this limitation and approximates the likelihood function better than the other methods. The improvement of the MCNR method is further illustrated with real-world data from a longitudinal study of local cervicovaginal HIV viral load and its effects on oncogenic HPV detection in HIV-positive women. Copyright © 2017 John Wiley & Sons, Ltd.

  8. Sampling for quality assurance of grading decisions in diabetic retinopathy screening: designing the system to detect errors.

    Science.gov (United States)

    Slattery, Jim

    2005-01-01

    To evaluate various designs for a quality assurance system to detect and control human errors in a national screening programme for diabetic retinopathy. A computer simulation was performed of some possible ways of sampling the referral decisions made during grading and of different criteria for initiating more intensive QA investigations. The effectiveness of QA systems was assessed by the ability to detect a grader making occasional errors in referral. Substantial QA sample sizes are needed to ensure against inappropriate failure to refer. Detection of a grader who failed to refer one in ten cases can be achieved with a probability of 0.58 using an annual sample size of 300 and 0.77 using a sample size of 500. An unmasked verification of a sample of non-referrals by a specialist is the most effective method of internal QA for the diabetic retinopathy screening programme. Preferential sampling of those with some degree of disease may improve the efficiency of the system.

  9. The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

    Science.gov (United States)

    Whiteman, David N.; Vermeesch, Kevin C.; Oman, Luke D.; Weatherhead, Elizabeth C.

    2011-01-01

    Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

  10. Dosimetric Effect of Intrafraction Motion and Residual Setup Error for Hypofractionated Prostate Intensity-Modulated Radiotherapy With Online Cone Beam Computed Tomography Image Guidance

    International Nuclear Information System (INIS)

    Adamson, Justus; Wu Qiuwen; Yan Di

    2011-01-01

    Purpose: To quantify the dosimetric effect and margins required to account for prostate intrafractional translation and residual setup error in a cone beam computed tomography (CBCT)-guided hypofractionated radiotherapy protocol. Methods and Materials: Prostate position after online correction was measured during dose delivery using simultaneous kV fluoroscopy and posttreatment CBCT in 572 fractions to 30 patients. We reconstructed the dose distribution to the clinical tumor volume (CTV) using a convolution of the static dose with a probability density function (PDF) based on the kV fluoroscopy, and we calculated the minimum dose received by 99% of the CTV (D 99 ). We compared reconstructed doses when the convolution was performed per beam, per patient, and when the PDF was created using posttreatment CBCT. We determined the minimum axis-specific margins to limit CTV D 99 reduction to 1%. Results: For 3-mm margins, D 99 reduction was ≤5% for 29/30 patients. Using post-CBCT rather than localizations at treatment delivery exaggerated dosimetric effects by ∼47%, while there was no such bias between the dose convolved with a beam-specific and patient-specific PDF. After eight fractions, final cumulative D 99 could be predicted with a root mean square error of <1%. For 90% of patients, the required margins were ≤2, 4, and 3 mm, with 70%, 40%, and 33% of patients requiring no right-left (RL), anteroposterior (AP), and superoinferior margins, respectively. Conclusions: For protocols with CBCT guidance, RL, AP, and SI margins of 2, 4, and 3 mm are sufficient to account for translational errors; however, the large variation in patient-specific margins suggests that adaptive management may be beneficial.

  11. Dosimetric effect of intrafraction motion and residual setup error for hypofractionated prostate intensity-modulated radiotherapy with online cone beam computed tomography image guidance.

    LENUS (Irish Health Repository)

    Adamson, Justus

    2012-02-01

    PURPOSE: To quantify the dosimetric effect and margins required to account for prostate intrafractional translation and residual setup error in a cone beam computed tomography (CBCT)-guided hypofractionated radiotherapy protocol. METHODS AND MATERIALS: Prostate position after online correction was measured during dose delivery using simultaneous kV fluoroscopy and posttreatment CBCT in 572 fractions to 30 patients. We reconstructed the dose distribution to the clinical tumor volume (CTV) using a convolution of the static dose with a probability density function (PDF) based on the kV fluoroscopy, and we calculated the minimum dose received by 99% of the CTV (D(99)). We compared reconstructed doses when the convolution was performed per beam, per patient, and when the PDF was created using posttreatment CBCT. We determined the minimum axis-specific margins to limit CTV D(99) reduction to 1%. RESULTS: For 3-mm margins, D(99) reduction was <\\/=5% for 29\\/30 patients. Using post-CBCT rather than localizations at treatment delivery exaggerated dosimetric effects by ~47%, while there was no such bias between the dose convolved with a beam-specific and patient-specific PDF. After eight fractions, final cumulative D(99) could be predicted with a root mean square error of <1%. For 90% of patients, the required margins were <\\/=2, 4, and 3 mm, with 70%, 40%, and 33% of patients requiring no right-left (RL), anteroposterior (AP), and superoinferior margins, respectively. CONCLUSIONS: For protocols with CBCT guidance, RL, AP, and SI margins of 2, 4, and 3 mm are sufficient to account for translational errors; however, the large variation in patient-specific margins suggests that adaptive management may be beneficial.

  12. Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection

    Directory of Open Access Journals (Sweden)

    Bloch Isabelle

    2007-01-01

    Full Text Available This paper describes a system for optical music recognition (OMR in case of monophonic typeset scores. After clarifying the difficulties specific to this domain, we propose appropriate solutions at both image analysis level and high-level interpretation. Thus, a recognition and segmentation method is designed, that allows dealing with common printing defects and numerous symbol interconnections. Then, musical rules are modeled and integrated, in order to make a consistent decision. This high-level interpretation step relies on the fuzzy sets and possibility framework, since it allows dealing with symbol variability, flexibility, and imprecision of music rules, and merging all these heterogeneous pieces of information. Other innovative features are the indication of potential errors and the possibility of applying learning procedures, in order to gain in robustness. Experiments conducted on a large data base show that the proposed method constitutes an interesting contribution to OMR.

  13. Neurometaplasticity: Glucoallostasis control of plasticity of the neural networks of error commission, detection, and correction modulates neuroplasticity to influence task precision

    Science.gov (United States)

    Welcome, Menizibeya O.; Dane, Şenol; Mastorakis, Nikos E.; Pereverzev, Vladimir A.

    2017-12-01

    The term "metaplasticity" is a recent one, which means plasticity of synaptic plasticity. Correspondingly, neurometaplasticity simply means plasticity of neuroplasticity, indicating that a previous plastic event determines the current plasticity of neurons. Emerging studies suggest that neurometaplasticity underlie many neural activities and neurobehavioral disorders. In our previous work, we indicated that glucoallostasis is essential for the control of plasticity of the neural network that control error commission, detection and correction. Here we review recent works, which suggest that task precision depends on the modulatory effects of neuroplasticity on the neural networks of error commission, detection, and correction. Furthermore, we discuss neurometaplasticity and its role in error commission, detection, and correction.

  14. Reinventing Image Detective: An Evidence-Based Approach to Citizen Science Online

    Science.gov (United States)

    Romano, C.; Graff, P. V.; Runco, S.

    2017-12-01

    Usability studies demonstrate that web users are notoriously impatient, spending as little as 15 seconds on a home page. How do you get users to stay long enough to understand a citizen science project? How do you get users to complete complex citizen science tasks online?Image Detective, a citizen science project originally developed by scientists and science engagement specialists at the NASA Johnson Space center to engage the public in the analysis of images taken from space by astronauts to help enhance NASA's online database of astronaut imagery, partnered with the CosmoQuest citizen science platform to modernize, offering new and improved options for participation in Image Detective. The challenge: to create a web interface that builds users' skills and knowledge, creating engagement while learning complex concepts essential to the accurate completion of tasks. The project team turned to usability testing for an objective understanding of how users perceived Image Detective and the steps required to complete required tasks. A group of six users was recruited online for unmoderated and initial testing. The users followed a think-aloud protocol while attempting tasks, and were recorded on video and audio. The usability test examined users' perception of four broad areas: the purpose of and context for Image Detective; the steps required to successfully complete the analysis (differentiating images of Earth's surface from those showing outer space and identifying common surface features); locating the image center point on a map of Earth; and finally, naming geographic locations or natural events seen in the image.Usability test findings demonstrated that the following best practices can increase participation in Image Detective and can be applied to the successful implementation of any citizen science project:• Concise explanation of the project, its context, and its purpose;• Including a mention of the funding agency (in this case, NASA);• A preview of

  15. Detecting causality from online psychiatric texts using inter-sentential language patterns

    Directory of Open Access Journals (Sweden)

    Wu Jheng-Long

    2012-07-01

    Full Text Available Abstract Background Online psychiatric texts are natural language texts expressing depressive problems, published by Internet users via community-based web services such as web forums, message boards and blogs. Understanding the cause-effect relations embedded in these psychiatric texts can provide insight into the authors’ problems, thus increasing the effectiveness of online psychiatric services. Methods Previous studies have proposed the use of word pairs extracted from a set of sentence pairs to identify cause-effect relations between sentences. A word pair is made up of two words, with one coming from the cause text span and the other from the effect text span. Analysis of the relationship between these words can be used to capture individual word associations between cause and effect sentences. For instance, (broke up, life and (boyfriend, meaningless are two word pairs extracted from the sentence pair: “I broke up with my boyfriend. Life is now meaningless to me”. The major limitation of word pairs is that individual words in sentences usually cannot reflect the exact meaning of the cause and effect events, and thus may produce semantically incomplete word pairs, as the previous examples show. Therefore, this study proposes the use of inter-sentential language patterns such as ≪broke up, boyfriend>, Results Performance was evaluated on a corpus of texts collected from PsychPark (http://www.psychpark.org, a virtual psychiatric clinic maintained by a group of volunteer professionals from the Taiwan Association of Mental Health Informatics. Experimental results show that the use of inter-sentential language patterns outperformed the use of word pairs proposed in previous studies. Conclusions This study demonstrates the acquisition of inter-sentential language patterns for causality detection from online psychiatric texts. Such semantically more complete and precise features can improve causality detection performance.

  16. System for detecting operating errors in a variable valve timing engine using pressure sensors

    Science.gov (United States)

    Wiles, Matthew A.; Marriot, Craig D

    2013-07-02

    A method and control module includes a pressure sensor data comparison module that compares measured pressure volume signal segments to ideal pressure volume segments. A valve actuation hardware remedy module performs a hardware remedy in response to comparing the measured pressure volume signal segments to the ideal pressure volume segments when a valve actuation hardware failure is detected.

  17. An Online Change of Activity in Energy Spectrum for Detection on an Early Intervention Robot

    Energy Technology Data Exchange (ETDEWEB)

    Boudergui, K.; Laine, F. [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif Sur Yvette (France); Montagu, T. [CEA, LIST, Laboratoire de Modelisation et de Simulation des Systemes, 91191 Gif-sur-Yvette (France); Blanc, P. [IMS, Innovation and Measurement Systems, 94100 Saint-Maur-des-Fosses (France); Deltour, A. [ECA Robotics, 91892 Orsay Cedex (France); Mozziconacci, S. [SDIS13, 13110 Port de Bouc (France)

    2015-07-01

    With the growth of industrial risks and the multiplication of CBRNe (Chemical Biological Radiological and explosive) attacks through toxic chemicals, biological or radiological threats, public services and military authorities face with increasingly critical situations, whose management is strongly conditioned by fast and reliable establishment of an informative diagnostic. Right after an attack, the five first minutes are crucial to define the various scenarios and the most dangerous for a human intervention. Therefore the use of robots is considered essential by all stakeholders of security. In this context, the SISPEO project (Systeme d'Intervention Sapeurs Pompiers Robotise) aims to create/build/design a robust response through a robotic platform for early intervention services such as civil and military security in hostile environments. CEA LIST has proposed an adapted solution to detect and characterize nuclear and radiological risks online and in motion, using a miniature embedded CdZnTe (CZT) crystal Gamma-ray spectrometer. This paper presents experimental results for this miniature embedded CZT spectrometer and its associated mathematical method to detect and characterize radiological threats online and in motion. (authors)

  18. A Virtual Sensor for Online Fault Detection of Multitooth-Tools

    Directory of Open Access Journals (Sweden)

    Andres Bustillo

    2011-03-01

    Full Text Available The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.

  19. A Virtual Sensor for Online Fault Detection of Multitooth-Tools

    Science.gov (United States)

    Bustillo, Andres; Correa, Maritza; Reñones, Anibal

    2011-01-01

    The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases. PMID:22163766

  20. An Online Change of Activity in Energy Spectrum for Detection on an Early Intervention Robot

    International Nuclear Information System (INIS)

    Boudergui, K.; Laine, F.; Montagu, T.; Blanc, P.; Deltour, A.; Mozziconacci, S.

    2015-01-01

    With the growth of industrial risks and the multiplication of CBRNe (Chemical Biological Radiological and explosive) attacks through toxic chemicals, biological or radiological threats, public services and military authorities face with increasingly critical situations, whose management is strongly conditioned by fast and reliable establishment of an informative diagnostic. Right after an attack, the five first minutes are crucial to define the various scenarios and the most dangerous for a human intervention. Therefore the use of robots is considered essential by all stakeholders of security. In this context, the SISPEO project (Systeme d'Intervention Sapeurs Pompiers Robotise) aims to create/build/design a robust response through a robotic platform for early intervention services such as civil and military security in hostile environments. CEA LIST has proposed an adapted solution to detect and characterize nuclear and radiological risks online and in motion, using a miniature embedded CdZnTe (CZT) crystal Gamma-ray spectrometer. This paper presents experimental results for this miniature embedded CZT spectrometer and its associated mathematical method to detect and characterize radiological threats online and in motion. (authors)

  1. Smart Sensor for Online Detection of Multiple-Combined Faults in VSD-Fed Induction Motors

    Science.gov (United States)

    Garcia-Ramirez, Armando G.; Osornio-Rios, Roque A.; Granados-Lieberman, David; Garcia-Perez, Arturo; Romero-Troncoso, Rene J.

    2012-01-01

    Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a common situation, because it is difficult to identify two or more faults simultaneously. This work presents a smart sensor for online detection of simple and multiple-combined faults in induction motors fed through a VSD in a wide frequency range covering low frequencies from 3 Hz and high frequencies up to 60 Hz based on a primary sensor being a commercially available current clamp or a hall-effect sensor. The proposed smart sensor implements a methodology based on the fast Fourier transform (FFT), RMS calculation and artificial neural networks (ANN), which are processed online using digital hardware signal processing based on field programmable gate array (FPGA).

  2. Automatic detection of patient identification and positioning errors in radiation therapy treatment using 3-dimensional setup images.

    Science.gov (United States)

    Jani, Shyam S; Low, Daniel A; Lamb, James M

    2015-01-01

    To develop an automated system that detects patient identification and positioning errors between 3-dimensional computed tomography (CT) and kilovoltage CT planning images. Planning kilovoltage CT images were collected for head and neck (H&N), pelvis, and spine treatments with corresponding 3-dimensional cone beam CT and megavoltage CT setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. For positioning errors, setup and planning images were misaligned by 1 to 5 cm in the 6 anatomical directions for H&N and pelvis patients. Spinal misalignments were simulated by misaligning to adjacent vertebral bodies. Image pairs were assessed using commonly used image similarity metrics as well as custom-designed metrics. Linear discriminant analysis classification models were trained and tested on the imaging datasets, and misclassification error (MCE), sensitivity, and specificity parameters were estimated using 10-fold cross-validation. For patient identification, our workflow produced MCE estimates of 0.66%, 1.67%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivity and specificity ranged from 97.5% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 95.4% and 97.7%. MCEs for 1-cm H&N/pelvis misalignments were 1.3%/5.1% and 9.1%/8.6% for TomoTherapy and TrueBeam images, respectively. Two-centimeter MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. MCEs for vertebral body misalignments were 4.8% and 3.6% for TomoTherapy and TrueBeam images, respectively. Patient identification and gross misalignment errors can be robustly and automatically detected using 3-dimensional setup images of different energies across 3 commonly treated anatomical sites. Copyright © 2015 American Society for Radiation Oncology. Published by

  3. Fast and accurate spectral estimation for online detection of partial broken bar in induction motors

    Science.gov (United States)

    Samanta, Anik Kumar; Naha, Arunava; Routray, Aurobinda; Deb, Alok Kanti

    2018-01-01

    In this paper, an online and real-time system is presented for detecting partial broken rotor bar (BRB) of inverter-fed squirrel cage induction motors under light load condition. This system with minor modifications can detect any fault that affects the stator current. A fast and accurate spectral estimator based on the theory of Rayleigh quotient is proposed for detecting the spectral signature of BRB. The proposed spectral estimator can precisely determine the relative amplitude of fault sidebands and has low complexity compared to available high-resolution subspace-based spectral estimators. Detection of low-amplitude fault components has been improved by removing the high-amplitude fundamental frequency using an extended-Kalman based signal conditioner. Slip is estimated from the stator current spectrum for accurate localization of the fault component. Complexity and cost of sensors are minimal as only a single-phase stator current is required. The hardware implementation has been carried out on an Intel i7 based embedded target ported through the Simulink Real-Time. Evaluation of threshold and detectability of faults with different conditions of load and fault severity are carried out with empirical cumulative distribution function.

  4. The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research-A Behavioral Study.

    Science.gov (United States)

    Furlan, Leonardo; Sterr, Annette

    2018-01-01

    Motor learning studies face the challenge of differentiating between real changes in performance and random measurement error. While the traditional p -value-based analyses of difference (e.g., t -tests, ANOVAs) provide information on the statistical significance of a reported change in performance scores, they do not inform as to the likely cause or origin of that change, that is, the contribution of both real modifications in performance and random measurement error to the reported change. One way of differentiating between real change and random measurement error is through the utilization of the statistics of standard error of measurement (SEM) and minimal detectable change (MDC). SEM is estimated from the standard deviation of a sample of scores at baseline and a test-retest reliability index of the measurement instrument or test employed. MDC, in turn, is estimated from SEM and a degree of confidence, usually 95%. The MDC value might be regarded as the minimum amount of change that needs to be observed for it to be considered a real change, or a change to which the contribution of real modifications in performance is likely to be greater than that of random measurement error. A computer-based motor task was designed to illustrate the applicability of SEM and MDC to motor learning research. Two studies were conducted with healthy participants. Study 1 assessed the test-retest reliability of the task and Study 2 consisted in a typical motor learning study, where participants practiced the task for five consecutive days. In Study 2, the data were analyzed with a traditional p -value-based analysis of difference (ANOVA) and also with SEM and MDC. The findings showed good test-retest reliability for the task and that the p -value-based analysis alone identified statistically significant improvements in performance over time even when the observed changes could in fact have been smaller than the MDC and thereby caused mostly by random measurement error, as opposed

  5. A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

    Science.gov (United States)

    Lyu, Jiang-Tao; Zhou, Chen

    2017-12-01

    Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

  6. Space-borne remote sensing of CO2 by IPDA lidar with heterodyne detection: random error estimation

    Science.gov (United States)

    Matvienko, G. G.; Sukhanov, A. Y.

    2015-11-01

    Possibilities of measuring the CO2 column concentration by spaceborne integrated path differential lidar (IPDA) signals in the near IR absorption bands are investigated. It is shown that coherent detection principles applied in the nearinfrared spectral region promise a high sensitivity for the measurement of the integrated dry air column mixing ratio of the CO2. The simulations indicate that for CO2 the target observational requirements (0.2%) for the relative random error can be met with telescope aperture 0.5 m, detector bandwidth 10 MHz, laser energy per impulse 0.3 mJ and averaging 7500 impulses. It should also be noted that heterodyne technique allows to significantly reduce laser power and receiver overall dimensions compared to direct detection.

  7. High-specificity detection of rare alleles with Paired-End Low Error Sequencing (PELE-Seq).

    Science.gov (United States)

    Preston, Jessica L; Royall, Ariel E; Randel, Melissa A; Sikkink, Kristin L; Phillips, Patrick C; Johnson, Eric A

    2016-06-14

    Polymorphic loci exist throughout the genomes of a population and provide the raw genetic material needed for a species to adapt to changes in the environment. The minor allele frequencies of rare Single Nucleotide Polymorphisms (SNPs) within a population have been difficult to track with Next-Generation Sequencing (NGS), due to the high error rate of standard methods such as Illumina sequencing. We have developed a wet-lab protocol and variant-calling method that identifies both sequencing and PCR errors, called Paired-End Low Error Sequencing (PELE-Seq). To test the specificity and sensitivity of the PELE-Seq method, we sequenced control E. coli DNA libraries containing known rare alleles present at frequencies ranging from 0.2-0.4 % of the total reads. PELE-Seq had higher specificity and sensitivity than standard libraries. We then used PELE-Seq to characterize rare alleles in a Caenorhabditis remanei nematode worm population before and after laboratory adaptation, and found that minor and rare alleles can undergo large changes in frequency during lab-adaptation. We have developed a method of rare allele detection that mitigates both sequencing and PCR errors, called PELE-Seq. PELE-Seq was evaluated using control E. coli populations and was then used to compare a wild C. remanei population to a lab-adapted population. The PELE-Seq method is ideal for investigating the dynamics of rare alleles in a broad range of reduced-representation sequencing methods, including targeted amplicon sequencing, RAD-Seq, ddRAD, and GBS. PELE-Seq is also well-suited for whole genome sequencing of mitochondria and viruses, and for high-throughput rare mutation screens.

  8. Application of ABTS radical cation for selective on-line detection of radical scavengers in HPLC eluates

    NARCIS (Netherlands)

    Koleva, [No Value; Niederlander, HAG; van Beek, TA

    2001-01-01

    The radical cation 2,2 ' -azinobis-(3 -ethylbenzothiazoline-6-sulfonate), (ABTS(.+)) was utilized in an on-line HPLC method for the detection of radical scavengers in complex matrixes. The HPLC-separated analytes react postcolumn with the preformed ABTS(.+), and the induced bleaching is detected as

  9. Detection of anomalies in radio tomography of asteroids: Source count and forward errors

    Science.gov (United States)

    Pursiainen, S.; Kaasalainen, M.

    2014-09-01

    The purpose of this study was to advance numerical methods for radio tomography in which asteroid's internal electric permittivity distribution is to be recovered from radio frequency data gathered by an orbiter. The focus was on signal generation via multiple sources (transponders) providing one potential, or even essential, scenario to be implemented in a challenging in situ measurement environment and within tight payload limits. As a novel feature, the effects of forward errors including noise and a priori uncertainty of the forward (data) simulation were examined through a combination of the iterative alternating sequential (IAS) inverse algorithm and finite-difference time-domain (FDTD) simulation of time evolution data. Single and multiple source scenarios were compared in two-dimensional localization of permittivity anomalies. Three different anomaly strengths and four levels of total noise were tested. Results suggest, among other things, that multiple sources can be necessary to obtain appropriate results, for example, to distinguish three separate anomalies with permittivity less or equal than half of the background value, relevant in recovery of internal cavities.

  10. Selective screening of 650 high risk Iranian patients for detection of inborn error of metabolism

    Directory of Open Access Journals (Sweden)

    Narges Pishva

    2015-02-01

    Full Text Available Objective: Although metabolic diseases individually are rare ,but overall have an incidence of 1/2000 and can cause devastating and irreversible effect if not diagnosed early and treated promptly. selective screening is an acceptable method for detection of these multi presentation diseases.Method: using panel neonatal screening for detection of metabolic diseases in 650 high risk Iranian patients in Fars province. The following clinical features were used as inclusion criteria for investigation of the patients.Lethargy, poor feeding ,persistent vomiting, cholestasis, intractable seizure ,decreased level of consciousness ,persistent hypoglycemia, unexplained acid base disturbance and unexplained neonatal death.Result: Organic acidemia with 40 cases (42% was the most frequent disorder diagnosed in our high risk populations, followed by disorder of galactose metabolism(30%, 15 patient had classic galactosemia(GALT

  11. Selective screening of 650 high risk Iranian patients for detection of inborn error of metabolism

    Directory of Open Access Journals (Sweden)

    Narges Pishva

    2015-02-01

    Full Text Available Objective: Although metabolic diseases individually are rare ,but overall have an incidence of 1/2000 and can cause devastating and irreversible effect if not diagnosed early and treated promptly. selective screening is an acceptable method for detection of these multi presentation diseases. Method: using panel neonatal screening for detection of metabolic diseases in 650 high risk Iranian patients in Fars province. The following clinical features were used as inclusion criteria for investigation of the patients. Lethargy, poor feeding ,persistent vomiting, cholestasis, intractable seizure ,decreased level of consciousness ,persistent hypoglycemia, unexplained acid base disturbance and unexplained neonatal death. Result: Organic acidemia with 40 cases (42% was the most frequent disorder diagnosed in our high risk populations, followed by disorder of galactose metabolism(30%, 15 patient had classic galactosemia(GALT

  12. Comparison of transfer functions. Error detection at transformers; Vergleichen der Uebertragungsfunktionen. Fehlererkennung bei Transformatoren

    Energy Technology Data Exchange (ETDEWEB)

    Rahimpour, Ebrahim [ABB AG, Bad Honnef (Germany). R and D Abt.

    2011-11-14

    The task of modern diagnostics is to provide an optimal use of transformation by means of an exact condition monitoring according to portable power and operating time without an inadmissible impact on the operational safety. Several methods are investigated with respect to this problem: thermal monitoring, oil analysis (DGA, furfural), partial discharge measurements (electric, acoustic), transfer function, relaxation current, RVM (Recovery Voltage Measurement) and various others. Each method has a certain suitability to detect changes.

  13. Reflotron cholesterol measurement in general practice: accuracy and detection of errors.

    Science.gov (United States)

    Ball, M J; Robertson, I K; Woods, M

    1994-11-01

    Comparison of cholesterol determinations by nurses using a Reflotron analyser in a general practice setting showed a good correlation with plasma cholesterol determinations by wet chemistry in a clinical biochemistry laboratory. A limited number of comparisons did, however, give a much lower result on the Reflotron. In an experimental situation, small sample volumes (which could result from poor technique) were shown to produce falsely low readings. A simple method which may immediately detect falsely low Reflotron readings is discussed.

  14. On-line coupled LC-LC-GC for irradiation detection in complex lipid matrices

    International Nuclear Information System (INIS)

    Schulzki, G.; Spiegelberg, A.; Helle, N.; Boegl, K.W.; Schreiber, G.A.

    1993-01-01

    Since sample preparation with HPLC coupled on-line to the GC has been performed for only a few weeks in our laboratory, the results presented give a first look at what can be done by means of this technique. Even difficult samples as the described fish species, where an unequivocal identification regarding an irradiation treatment seemed to become a hopeless enterprise, could be managed. Because of the greater variety of fatty acids in fish ''new'' radiation-induced hydrocarbons were available. According to the theory of Nawar in addition to 16:2 and 17:2 hydrocarbons we have looked for in irradiated meat, further alkadienes appeared in irradiated fish, which were 14:2, 18:2 and 20:2. Analysis of the alkadiene-fraction, transferred to the GC after a two step LC clean up, resulted in an unequivocal identification of all fish samples as well as the fruits and sponge cake. For fruits and sponge cake the detection limit seems to be clearly below 0.5 kGy. It can further be lowered by increasing the amount of lipid whereas the upper limit for a certain LC column has to be determined. In contrast to these samples only qualitative results were obtained for fish. In the case of sponge cake for the first time irradiation of a component of a heat treated food was detected. Further investigations regarding reproducibility, dose dependence and detection limit have to be done. On-line coupled (LC-)LC-GC was proved to be a highly efficient method for analysis of complex samples. In contrast to off-line Florisil column chromatography only a small part of the initial lipid material is needed because the complete hydrocarbon fraction is transferred on-line to the GC. This offers the possibility to analyze even foods with a low fat content like various seafoods. Classification of the hydrocarbon fraction by a two step LC may facilitate the identification of the radiolytic products also if no mass spectrometric detection system is available. (orig./vhe)

  15. Construction of prototype of on-line analyzer detection system for coal on belt conveyor using neutron activation technique

    International Nuclear Information System (INIS)

    Rony Djokorayono; Agus Cahyono; MP Indarzah; SG Usep; Sukandar

    2015-01-01

    The use of on-line neutron activation technique for coal analysis is proposed as an alternative method for analysis based on sampling technique. Compared to this conventional technique, the on-line neutron activation technique has much shorter time of analysis and more accurate results. The construction of detection system prototype for the on-line analyzer is described in this paper. This on-line analyzer consists of detection system, data acquisition system, and computer console. This detection system comprises several modules, i.e. NaI(Tl) scintillation detector completed with a photomultiplier tube (PMT), pre-amplifier, single channel analyzer (SCA), and analog signal transmitter and pulse counter processor. The construction processes of these four modules include the development of configuration block, lay out, and selection of electronic components. The modules have been integrated and tested. This detection system was tested using radioactive element Zn-65 having energy of 1115.5 keV and activity of 1 μCi. The test results show that the prototype of the on-line analyzer detection system has functioned as expected. (author)

  16. Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

    Science.gov (United States)

    Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

    2018-01-01

    Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

  17. Pyrosequencing as a tool for the detection of Phytophthora species: error rate and risk of false Molecular Operational Taxonomic Units.

    Science.gov (United States)

    Vettraino, A M; Bonants, P; Tomassini, A; Bruni, N; Vannini, A

    2012-11-01

    To evaluate the accuracy of pyrosequencing for the description of Phytophthora communities in terms of taxa identification and risk of assignment for false Molecular Operational Taxonomic Units (MOTUs). Pyrosequencing of Internal Transcribed Spacer 1 (ITS1) amplicons was used to describe the structure of a DNA mixture comprising eight Phytophthora spp. and Pythium vexans. Pyrosequencing resulted in 16 965 reads, detecting all species in the template DNA mixture. Reducing the ITS1 sequence identity threshold resulted in a decrease in numbers of unmatched reads but a concomitant increase in the numbers of false MOTUs. The total error rate was 0·63% and comprised mainly mismatches (0·25%) Pyrosequencing of ITS1 region is an efficient and accurate technique for the detection and identification of Phytophthora spp. in environmental samples. However, the risk of allocating false MOTUs, even when demonstrated to be low, may require additional validation with alternative detection methods. Phytophthora spp. are considered among the most destructive groups of invasive plant pathogens, affecting thousands of cultivated and wild plants worldwide. Simultaneous early detection of Phytophthora complexes in environmental samples offers an unique opportunity for the interception of known and unknown species along pathways of introduction, along with the identification of these organisms in invaded environments. © 2012 The Authors Letters in Applied Microbiology © 2012 The Society for Applied Microbiology.

  18. The Scientific Method, Diagnostic Bayes, and How to Detect Epistemic Errors

    Science.gov (United States)

    Vrugt, J. A.

    2015-12-01

    evaluation. This hybrid approach, coined diagnostic Bayes, uses the summary metrics as prior distribution and original data in the likelihood function, or P(x|\\hat {D}) ∝ P(x|S(\\hat {D})) L(x|\\hat {D}). A case study illustrates the ability of the proposed methodology to diagnose epistemic errors and provide guidance on model refinement.

  19. VizieR Online Data Catalog: ROSAT detected quasars. I. (Brinkmann+ 1997)

    Science.gov (United States)

    Brinkmann, W.; Yuan, W.

    1996-09-01

    We have compiled a sample of all quasars with measured radio emission from the Veron-Cetty - Veron catalogue (1993, VV93 ) detected by ROSAT in the ALL-SKY SURVEY (RASS, Voges 1992), as targets of pointed observations, or as serendipitous sources from pointed observations as publicly available from the ROSAT point source catalogue (ROSAT-SRC, Voges et al. 1995). The total number of ROSAT detected radio quasars from the above three sources is 654 objects. 69 of the objects are classified as radio-quiet using the defining line at a radio-loudness of 1.0, and 10 objects have no classification. The 5GHz data are from the 87GB radio survey, the NED database, or from the Veron-Cetty - Veron catalogue. The power law indices and their errors are estimated from the two hardness ratios given by the SASS assuming Galactic absorption. The X-ray flux densities in the ROSAT band (0.1-2.4keV) are calculated from the count rates using the energy to counts conversion factor for power law spectra and Galactic absorption. For the photon index we use the value obtained for a individual source if the estimated 1 sigma error is smaller than 0.5, otherwise we use the mean value 2.14. (1 data file).

  20. Detecting the Online Image of “Average” Restaurants on TripAdvisor

    Directory of Open Access Journals (Sweden)

    Hrvoje Jakopović

    2016-06-01

    Full Text Available Collective intelligence can be interpreted as the actions of individuals that provide collective effects. In online spaces, the more user comments about a matter of discussion, the higher the potential that certain repeated points of view will be used as a story frame. This observation can be a very useful explanation for the value of user comments, reviews and the ratings in the field of public relations. Nowadays, it has become noticeable that many indecisive people who are thinking of buying a product or using a certain service rely on information left by users who already have some kind of experience with the product or service. This information has an effect on decision-making and taking action. In the case of contemporary PR, collective intelligence, facilitated through user comments/reviews, is involved in the image making process. This paper uses the idea of collective intelligence to measure restaurants’ online image, using sentiment analysis to gain insight to users’ attitudes and opinions. Image is interpreted as a short-term outcome of organizational activities that can be identified through individual attitudes and opinions in this study. The author uses sentiment analysis, the use of natural language processing applications, to examine user comments and reviews for restaurants in Dubrovnik rated as “average” on the website TripAdvisor. This paper tests the accuracy of sentiment analysis software, therefore the efficiency of automated sentiment analysis is compared to human sentiment analysis. The results indicate that sentiment analysis tools could be important instruments for the estimation of a positive, negative, or neutral sentiment and detection of organization’s online image.

  1. Automatic analysis of online image data for law enforcement agencies by concept detection and instance search

    Science.gov (United States)

    de Boer, Maaike H. T.; Bouma, Henri; Kruithof, Maarten C.; ter Haar, Frank B.; Fischer, Noëlle M.; Hagendoorn, Laurens K.; Joosten, Bart; Raaijmakers, Stephan

    2017-10-01

    The information available on-line and off-line, from open as well as from private sources, is growing at an exponential rate and places an increasing demand on the limited resources of Law Enforcement Agencies (LEAs). The absence of appropriate tools and techniques to collect, process, and analyze the volumes of complex and heterogeneous data has created a severe information overload. If a solution is not found, the impact on law enforcement will be dramatic, e.g. because important evidence is missed or the investigation time is too long. Furthermore, there is an uneven level of capabilities to deal with the large volumes of complex and heterogeneous data that come from multiple open and private sources at national level across the EU, which hinders cooperation and information sharing. Consequently, there is a pertinent need to develop tools, systems and processes which expedite online investigations. In this paper, we describe a suite of analysis tools to identify and localize generic concepts, instances of objects and logos in images, which constitutes a significant portion of everyday law enforcement data. We describe how incremental learning based on only a few examples and large-scale indexing are addressed in both concept detection and instance search. Our search technology allows querying of the database by visual examples and by keywords. Our tools are packaged in a Docker container to guarantee easy deployment on a system and our tools exploit possibilities provided by open source toolboxes, contributing to the technical autonomy of LEAs.

  2. Improving Fraudster Detection in Online Auctions by Using Neighbor-Driven Attributes

    Directory of Open Access Journals (Sweden)

    Jun-Lin Lin

    2015-12-01

    Full Text Available Online auction websites use a simple reputation system to help their users to evaluate the trustworthiness of sellers and buyers. However, to improve their reputation in the reputation system, fraudulent users can easily deceive the reputation system by creating fake transactions. This inflated-reputation fraud poses a major problem for online auction websites because it can lead legitimate users into scams. Numerous approaches have been proposed in the literature to address this problem, most of which involve using social network analysis (SNA to derive critical features (e.g., k-core, center weight, and neighbor diversity for distinguishing fraudsters from legitimate users. This paper discusses the limitations of these SNA features and proposes a class of SNA features referred to as neighbor-driven attributes (NDAs. The NDAs of users are calculated from the features of their neighbors. Because fraudsters require collusive neighbors to provide them with positive ratings in the reputation system, using NDAs can be helpful for detecting fraudsters. Although the idea of NDAs is not entirely new, experimental results on a real-world dataset showed that using NDAs improves classification accuracy compared with state-of-the-art methods that use the k-core, center weight, and neighbor diversity.

  3. Followers are not enough: a multifaceted approach to community detection in online social networks.

    Science.gov (United States)

    Darmon, David; Omodei, Elisa; Garland, Joshua

    2015-01-01

    In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a 'community' as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of 'community.' In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure.

  4. TH-AB-202-02: Real-Time Verification and Error Detection for MLC Tracking Deliveries Using An Electronic Portal Imaging Device

    International Nuclear Information System (INIS)

    J Zwan, B; Colvill, E; Booth, J; J O’Connor, D; Keall, P; B Greer, P

    2016-01-01

    Purpose: The added complexity of the real-time adaptive multi-leaf collimator (MLC) tracking increases the likelihood of undetected MLC delivery errors. In this work we develop and test a system for real-time delivery verification and error detection for MLC tracking radiotherapy using an electronic portal imaging device (EPID). Methods: The delivery verification system relies on acquisition and real-time analysis of transit EPID image frames acquired at 8.41 fps. In-house software was developed to extract the MLC positions from each image frame. Three comparison metrics were used to verify the MLC positions in real-time: (1) field size, (2) field location and, (3) field shape. The delivery verification system was tested for 8 VMAT MLC tracking deliveries (4 prostate and 4 lung) where real patient target motion was reproduced using a Hexamotion motion stage and a Calypso system. Sensitivity and detection delay was quantified for various types of MLC and system errors. Results: For both the prostate and lung test deliveries the MLC-defined field size was measured with an accuracy of 1.25 cm 2 (1 SD). The field location was measured with an accuracy of 0.6 mm and 0.8 mm (1 SD) for lung and prostate respectively. Field location errors (i.e. tracking in wrong direction) with a magnitude of 3 mm were detected within 0.4 s of occurrence in the X direction and 0.8 s in the Y direction. Systematic MLC gap errors were detected as small as 3 mm. The method was not found to be sensitive to random MLC errors and individual MLC calibration errors up to 5 mm. Conclusion: EPID imaging may be used for independent real-time verification of MLC trajectories during MLC tracking deliveries. Thresholds have been determined for error detection and the system has been shown to be sensitive to a range of delivery errors.

  5. Pilotaje en la detección de errores de prescripción de citostáticos Pilot study in the detection of errors in cytostatics prescription

    Directory of Open Access Journals (Sweden)

    María Antonieta Arbesú Michelena

    2004-12-01

    Institute of Oncology and Radiobiology in 43 medical orders. The errors were divided into errors caused by omission (that make difficult the checking on the part of the pharmacist, and errors caused by incorrectness (that may be potentially severe for the patient. There were 299 errors in all. The lack of the physician's signature in 43 prescriptions, as well as the use of abbreviations, acronyms and commercial names in 88.4 % of them, were among the most common errors. As to the severe errors, it was observed the non-inclusion of the weight and height in any medical order, the erroneous body surface (bs above the real in 15 cases (34.8 %, the subdosing in 41 occasions (47.7 % and the non-correspondance with the Protocol according to the Institutional Norms in 17 mistakes. It was concluded that the occurrence of prescription errors is high at the service, which shows that it is important to protocol the medical orders to reduce the percentage or errors detected in this pilot study and to go deep into this matter.

  6. Online Particle Detection by Neural Networks Based on Topologic Calorimetry Information

    CERN Document Server

    Ciodaro, T; The ATLAS collaboration; Damazio, D; de Seixas, JM

    2011-01-01

    This paper presents the last results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction over the ATLAS calorimetry information (energy measurements). Later, the extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time in 59%. Also, the payload necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount

  7. Liking and hyperlinking: Community detection in online child sexual exploitation networks.

    Science.gov (United States)

    Westlake, Bryce G; Bouchard, Martin

    2016-09-01

    The online sexual exploitation of children is facilitated by websites that form virtual communities, via hyperlinks, to distribute images, videos, and other material. However, how these communities form, are structured, and evolve over time is unknown. Collected using a custom-designed webcrawler, we begin from known child sexual exploitation (CE) seed websites and follow hyperlinks to connected, related, websites. Using a repeated measure design we analyze 10 networks of 300 + websites each - over 4.8 million unique webpages in total, over a period of 60 weeks. Community detection techniques reveal that CE-related networks were dominated by two large communities hosting varied material -not necessarily matching the seed website. Community stability, over 60 weeks, varied across networks. Reciprocity in hyperlinking between community members was substantially higher than within the full network, however, websites were not more likely to connect to homogeneous-content websites. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Parameters Online Detection and Model Predictive Control during the Grain Drying Process

    Directory of Open Access Journals (Sweden)

    Lihui Zhang

    2013-01-01

    Full Text Available In order to improve the grain drying quality and automation level, combined with the structural characteristics of the cross-flow circulation grain dryer designed and developed by us, the temperature, moisture, and other parameters measuring sensors were placed on the dryer, to achieve online automatic detection of process parameters during the grain drying process. A drying model predictive control system was set up. A grain dry predictive control model at constant velocity and variable temperature was established, in which the entire process was dried at constant velocity (i.e., precipitation rate per hour is a constant and variable temperature. Combining PC with PLC, and based on LabVIEW, a system control platform was designed.

  9. Nondestructive Online Detection of Welding Defects in Track Crane Boom Using Acoustic Emission Technique

    Directory of Open Access Journals (Sweden)

    Yong Tao

    2014-04-01

    Full Text Available Nondestructive detection of structural component of track crane is a difficult and costly problem. In the present study, acoustic emission (AE was used to detect two kinds of typical welding defects, that is, welding porosity and incomplete penetration, in the truck crane boom. Firstly, a subsidiary test specimen with special preset welding defect was designed and added on the boom surface with the aid of steel plates to get the synchronous deformation of the main boom. Then, the AE feature information of the welding defect could be got without influencing normal operation of equipment. As a result, the rudimentary location analysis can be attained using the linear location method and the two kinds of welding defects can be distinguished clearly using AE characteristic parameters such as amplitude and centroid frequency. Also, through the comparison of two loading processes, we concluded that the signal produced during the first loading process was mainly caused by plastic deformation damage and during the second loading process the stress release and structure friction between sections in welding area are the main acoustic emission sources. Thus, the AE is an available tool for nondestructive online detection of latent welding defects of structural component of track crane.

  10. Fast Flux Watch: A mechanism for online detection of fast flux networks

    Directory of Open Access Journals (Sweden)

    Basheer N. Al-Duwairi

    2014-07-01

    Full Text Available Fast flux networks represent a special type of botnets that are used to provide highly available web services to a backend server, which usually hosts malicious content. Detection of fast flux networks continues to be a challenging issue because of the similar behavior between these networks and other legitimate infrastructures, such as CDNs and server farms. This paper proposes Fast Flux Watch (FF-Watch, a mechanism for online detection of fast flux agents. FF-Watch is envisioned to exist as a software agent at leaf routers that connect stub networks to the Internet. The core mechanism of FF-Watch is based on the inherent feature of fast flux networks: flux agents within stub networks take the role of relaying client requests to point-of-sale websites of spam campaigns. The main idea of FF-Watch is to correlate incoming TCP connection requests to flux agents within a stub network with outgoing TCP connection requests from the same agents to the point-of-sale website. Theoretical and traffic trace driven analysis shows that the proposed mechanism can be utilized to efficiently detect fast flux agents within a stub network.

  11. Can the Bruckner test be used as a rapid screening test to detect significant refractive errors in children?

    Directory of Open Access Journals (Sweden)

    Kothari Mihir

    2007-01-01

    Full Text Available Purpose: To assess the suitability of Brückner test as a screening test to detect significant refractive errors in children. Materials and Methods: A pediatric ophthalmologist prospectively observed the size and location of pupillary crescent on Brückner test as hyperopic, myopic or astigmatic. This was compared with the cycloplegic refraction. Detailed ophthalmic examination was done for all. Sensitivity, specificity, positive predictive value and negative predictive value of Brückner test were determined for the defined cutoff levels of ametropia. Results: Ninety-six subjects were examined. Mean age was 8.6 years (range 1 to 16 years. Brückner test could be completed for all; the time taken to complete this test was 10 seconds per subject. The ophthalmologist identified 131 eyes as ametropic, 61 as emmetropic. The Brückner test had sensitivity 91%, specificity 72.8%, positive predictive value 85.5% and negative predictive value 83.6%. Of 10 false negatives four had compound hypermetropic astigmatism and three had myopia. Conclusions: Brückner test can be used to rapidly screen the children for significant refractive errors. The potential benefits from such use may be maximized if programs use the test with lower crescent measurement cutoffs, a crescent measurement ruler and a distance fixation target.

  12. SU-E-T-310: Targeting Safety Improvements Through Analysis of Near-Miss Error Detection Points in An Incident Learning Database

    International Nuclear Information System (INIS)

    Novak, A; Nyflot, M; Sponseller, P; Howard, J; Logan, W; Holland, L; Jordan, L; Carlson, J; Ermoian, R; Kane, G; Ford, E; Zeng, J

    2014-01-01

    Purpose: Radiation treatment planning involves a complex workflow that can make safety improvement efforts challenging. This study utilizes an incident reporting system to identify detection points of near-miss errors, in order to guide our departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or their patterns. Methods: 1377 incidents were analyzed from a departmental nearmiss error reporting system from 3/2012–10/2013. All incidents were prospectively reviewed weekly by a multi-disciplinary team, and assigned a near-miss severity score ranging from 0–4 reflecting potential harm (no harm to critical). A 98-step consensus workflow was used to determine origination and detection points of near-miss errors, categorized into 7 major steps (patient assessment/orders, simulation, contouring/treatment planning, pre-treatment plan checks, therapist/on-treatment review, post-treatment checks, and equipment issues). Categories were compared using ANOVA. Results: In the 7-step workflow, 23% of near-miss errors were detected within the same step in the workflow, while an additional 37% were detected by the next step in the workflow, and 23% were detected two steps downstream. Errors detected further from origination were more severe (p<.001; Figure 1). The most common source of near-miss errors was treatment planning/contouring, with 476 near misses (35%). Of those 476, only 72(15%) were found before leaving treatment planning, 213(45%) were found at physics plan checks, and 191(40%) were caught at the therapist pre-treatment chart review or on portal imaging. Errors that passed through physics plan checks and were detected by therapists were more severe than other errors originating in contouring/treatment planning (1.81 vs 1.33, p<0.001). Conclusion: Errors caught by radiation treatment therapists tend to be more severe than errors caught earlier in the workflow, highlighting the importance of safety

  13. Correction for ‘artificial’ electron disequilibrium due to cone-beam CT density errors: implications for on-line adaptive stereotactic body radiation therapy of lung

    International Nuclear Information System (INIS)

    Disher, Brandon; Hajdok, George; Craig, Jeff; Gaede, Stewart; Battista, Jerry J; Wang, An

    2013-01-01

    Cone-beam computed tomography (CBCT) has rapidly become a clinically useful imaging modality for image-guided radiation therapy. Unfortunately, CBCT images of the thorax are susceptible to artefacts due to scattered photons, beam hardening, lag in data acquisition, and respiratory motion during a slow scan. These limitations cause dose errors when CBCT image data are used directly in dose computations for on-line, dose adaptive radiation therapy (DART). The purpose of this work is to assess the magnitude of errors in CBCT numbers (HU), and determine the resultant effects on derived tissue density and computed dose accuracy for stereotactic body radiation therapy (SBRT) of lung cancer. Planning CT (PCT) images of three lung patients were acquired using a Philips multi-slice helical CT simulator, while CBCT images were obtained with a Varian On-Board Imaging system. To account for erroneous CBCT data, three practical correction techniques were tested: (1) conversion of CBCT numbers to electron density using phantoms, (2) replacement of individual CBCT pixel values with bulk CT numbers, averaged from PCT images for tissue regions, and (3) limited replacement of CBCT lung pixels values (LCT) likely to produce artificial lateral electron disequilibrium. For each corrected CBCT data set, lung SBRT dose distributions were computed for a 6 MV volume modulated arc therapy (VMAT) technique within the Philips Pinnacle treatment planning system. The reference prescription dose was set such that 95% of the planning target volume (PTV) received at least 54 Gy (i.e. D95). Further, we used the relative depth dose factor as an a priori index to predict the effects of incorrect low tissue density on computed lung dose in regions of severe electron disequilibrium. CT number profiles from co-registered CBCT and PCT patient lung images revealed many reduced lung pixel values in CBCT data, with some pixels corresponding to vacuum (−1000 HU). Similarly, CBCT data in a plastic lung

  14. Research on the Error Characteristics of a 110 kV Optical Voltage Transformer under Three Conditions: In the Laboratory, Off-Line in the Field and During On-Line Operation

    Science.gov (United States)

    Xiao, Xia; Hu, Haoliang; Xu, Yan; Lei, Min; Xiong, Qianzhu

    2016-01-01

    Optical voltage transformers (OVTs) have been applied in power systems. When performing accuracy performance tests of OVTs large differences exist between the electromagnetic environment and the temperature variation in the laboratory and on-site. Therefore, OVTs may display different error characteristics under different conditions. In this paper, OVT prototypes with typical structures were selected to be tested for the error characteristics with the same testing equipment and testing method. The basic accuracy, the additional error caused by temperature and the adjacent phase in the laboratory, the accuracy in the field off-line, and the real-time monitoring error during on-line operation were tested. The error characteristics under the three conditions—laboratory, in the field off-line and during on-site operation—were compared and analyzed. The results showed that the effect of the transportation process, electromagnetic environment and the adjacent phase on the accuracy of OVTs could be ignored for level 0.2, but the error characteristics of OVTs are dependent on the environmental temperature and are sensitive to the temperature gradient. The temperature characteristics during on-line operation were significantly superior to those observed in the laboratory. PMID:27537895

  15. Online in-tube microextractor coupled with UV-Vis spectrophotometer for bisphenol A detection.

    Science.gov (United States)

    Poorahong, Sujittra; Thammakhet, Chongdee; Thavarungkul, Panote; Kanatharana, Proespichaya

    2013-01-01

    A simple and high extraction efficiency online in-tube microextractor (ITME) was developed for bisphenol A (BPA) detection in water samples. The ITME was fabricated by a stepwise electrodeposition of polyaniline, polyethylene glycol and polydimethylsiloxane composite (CPANI) inside a silico-steel tube. The obtained ITME coupled with UV-Vis detection at 278 nm was investigated. By this method, the extraction and pre-concentration of BPA in water were carried out in a single step. Under optimum conditions, the system provided a linear dynamic range of 0.1 to 100 μM with a limit of detection of 20 nM (S/N ≥3). A single in-tube microextractor had a good stability of more than 60 consecutive injections for 10.0 μM BPA with a relative standard deviation of less than 4%. Moreover, a good tube-to-tube reproducibility and precision were obtained. The system was applied to detect BPA in water samples from six brands of baby bottles and the results showed good agreement with those obtained from the conventional GC-MS method. Acceptable percentage recoveries from the spiked water samples were obtained, ranging from 83-102% for this new method compared with 73-107% for the GC-MS standard method. This new in-tube CPANI microextractor provided an excellent extraction efficiency and a good reproducibility. In addition, it can also be easily applied for the analysis of other polar organic compounds contaminated in water sample.

  16. Design of the scanning mode coated glass color difference online detection system

    Science.gov (United States)

    Bi, Weihong; Zhang, Yu; Wang, Dajiang; Zhang, Baojun; Fu, Guangwei

    2008-03-01

    A design of scanning mode coated glass color difference online detection system was introduced. The system consisted of color difference data acquirement part and orbit control part. The function of the color difference data acquirement part was to acquire glass spectral reflectance and then processed them to get the color difference value. Using fiber for light guiding, the reflected light from surface of glass was transmitted into light division part, and the dispersive light was imaged on linear CCD, and then the output signals from the CCD was sampled pixel by pixel, and the spectral reflectance of coated glass was obtained finally. Then, the acquired spectral reflectance signals was sent to industrial personal computer through USB interface, using standard color space and color difference formula nominated by International Commission on Illumination (CIE) in 1976 to process these signals, and the reflected color parameter and color difference of coated glass was gained in the end. The function of the orbit control part was to move the detection probe by way of transverse scanning mode above the glass strip, and control the measuring start-stop time of the color difference data acquirement part at the same time. The color difference data acquirement part of the system was put on the orbit which is after annealing area in coated glass production line, and the protected fiber probe was placed on slide of the orbit. Using single chip microcomputer to control transmission mechanism of the slide, which made the slide move by way of transverse scanning mode on the glass strip, meanwhile, the color difference data acquirement part of the system was also controlled by the single chip microcomputer, and it made the acquirement part measure color difference data when the probe reached the needed working speed and required place on the glass strip. The scanning mode coated glass color difference online detection system can measure color parameter and color difference of

  17. Powerful conveyer belt real-time online detection system based on x-ray

    Science.gov (United States)

    Rong, Feng; Miao, Chang-yun; Meng, Wei

    2009-07-01

    The powerful conveyer belt is widely used in the mine, dock, and so on. After used for a long time, internal steel rope of the conveyor belt may fracture, rust, joints moving, and so on .This would bring potential safety problems. A kind of detection system based on x-ray is designed in this paper. Linear array detector (LDA) is used. LDA cost is low, response fast; technology mature .Output charge of LDA is transformed into differential voltage signal by amplifier. This kind of signal have great ability of anti-noise, is suitable for long-distance transmission. The processor is FPGA. A IP core control 4-channel A/D convertor, achieve parallel output data collection. Soft-core processor MicroBlaze which process tcp/ip protocol is embedded in FPGA. Sampling data are transferred to a computer via Ethernet. In order to improve the image quality, algorithm of getting rid of noise from the measurement result and taking gain normalization for pixel value is studied and designed. Experiments show that this system work well, can real-time online detect conveyor belt of width of 2.0m and speed of 5 m/s, does not affect the production. Image is clear, visual and can easily judge the situation of conveyor belt.

  18. On-line defect detection of aluminum coating using fiber optic sensor

    Science.gov (United States)

    Patil, Supriya S.; Shaligram, A. D.

    2015-03-01

    Aluminum metallization using the sprayed coating for exhaust mild steel (MS) pipes of tractors is a standard practice for avoiding rusting. Patches of thin metal coats are prone to rusting and are thus considered as defects in the surface coating. This paper reports a novel configuration of the fiber optic sensor for on-line checking the aluminum metallization uniformity and hence for defect detection. An optimally chosen high bright 440 nm BLUE LED (light-emitting diode) launches light into a transmitting fiber inclined at the angle of 60° to the surface under inspection placed adequately. The reflected light is transported by a receiving fiber to a blue enhanced photo detector. The metallization thickness on the coated surface results in visually observable variation in the gray shades. The coated pipe is spirally inspected by a combination of linear and rotary motions. The sensor output is the signal conditioned and monitored with RISHUBH DAS. Experimental results show the good repeatability in the defect detection and coating non-uniformity measurement.

  19. [Modal failure analysis and effects in the detection of errors in the transport of samples to the clinical laboratory].

    Science.gov (United States)

    Parés-Pollán, L; Gonzalez-Quintana, A; Docampo-Cordeiro, J; Vargas-Gallego, C; García-Álvarez, G; Ramos-Rodríguez, V; Diaz Rubio-García, M P

    2014-01-01

    Owing to the decrease in values of biochemical glucose parameter in some samples from external extraction centres, and the risk this implies to patient safety; it was decided to apply an adaptation of the «Health Services Failure Mode and Effects Analysis» (HFMEA) to manage risk during the pre-analytical phase of sample transportation from external centres to clinical laboratories. A retrospective study of glucose parameter was conducted during two consecutive months. The analysis was performed in its different phases: to define the HFMEA topic, assemble the team, graphically describe the process, conduct a hazard analysis, design the intervention and indicators, and identify a person to be responsible for ensuring completion of each action. The results of glucose parameter in one of the transport routes, were significantly lower (P=.006). The errors and potential causes of this problem were analysed, and criteria of criticality and detectability were applied (score≥8) in the decision tree. It was decided to: develop a document management system; reorganise extractions and transport routes in some centres; quality control of the sample container ice-packs, and the time and temperature during transportation. This work proposes quality indicators for controlling time and temperature of transported samples in the pre-analytical phase. Periodic review of certain laboratory parameters can help to detect problems in transporting samples. The HFMEA technique is useful for the clinical laboratory. Copyright © 2013 SECA. Published by Elsevier Espana. All rights reserved.

  20. Evaluation of different types of sensors and their positioning for on-line PD detection and localisation in distribution cables

    NARCIS (Netherlands)

    Wielen, van der P.C.J.M.; Veen, J.; Wouters, P.A.A.F.

    2003-01-01

    Different types of sensors can be used for on-line detection and localisation of PDs in medium voltage cables. These sensors can be placed on different locations in the substa-tions where the cable under test is terminated. Both aspects have a significant influence on the measured signals. In this

  1. Prescription Errors in Psychiatry

    African Journals Online (AJOL)

    Arun Kumar Agnihotri

    clinical pharmacists in detecting errors before they have a (sometimes serious) clinical impact should not be underestimated. Research on medication error in mental health care is limited. .... participation in ward rounds and adverse drug.

  2. The Errors of Our Ways: Understanding Error Representations in Cerebellar-Dependent Motor Learning.

    Science.gov (United States)

    Popa, Laurentiu S; Streng, Martha L; Hewitt, Angela L; Ebner, Timothy J

    2016-04-01

    The cerebellum is essential for error-driven motor learning and is strongly implicated in detecting and correcting for motor errors. Therefore, elucidating how motor errors are represented in the cerebellum is essential in understanding cerebellar function, in general, and its role in motor learning, in particular. This review examines how motor errors are encoded in the cerebellar cortex in the context of a forward internal model that generates predictions about the upcoming movement and drives learning and adaptation. In this framework, sensory prediction errors, defined as the discrepancy between the predicted consequences of motor commands and the sensory feedback, are crucial for both on-line movement control and motor learning. While many studies support the dominant view that motor errors are encoded in the complex spike discharge of Purkinje cells, others have failed to relate complex spike activity with errors. Given these limitations, we review recent findings in the monkey showing that complex spike modulation is not necessarily required for motor learning or for simple spike adaptation. Also, new results demonstrate that the simple spike discharge provides continuous error signals that both lead and lag the actual movements in time, suggesting errors are encoded as both an internal prediction of motor commands and the actual sensory feedback. These dual error representations have opposing effects on simple spike discharge, consistent with the signals needed to generate sensory prediction errors used to update a forward internal model.

  3. A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

    Science.gov (United States)

    Tridandapani, Srini; Ramamurthy, Senthil; Provenzale, James; Obuchowski, Nancy A; Evanoff, Michael G; Bhatti, Pamela

    2014-08-01

    To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors. In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded. Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77). In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  4. Analysis of primary aromatic amines using precolumn derivatization by HPLC fluorescence detection and online MS identification.

    Science.gov (United States)

    Zhao, Xianen; Suo, Yourui

    2008-03-01

    2-(2-phenyl-1H-phenanthro-[9,10-d]imidazole-1-yl)-acetic acid (PPIA) and 2-(9-acridone)-acetic acid (AAA), two novel precolumn fluorescent derivatization reagents, have been developed and compared for analysis of primary aromatic amines by high performance liquid chromatographic fluorescence detection coupled with online mass spectrometric identification. PPIA and AAA react rapidly and smoothly with the aromatic amines on the basis of a condensation reaction using 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) as dehydrating catalyst to form stable derivatives with emission wavelengths at 380 and 440 nm, respectively. Taking six primary aromatic amines (aniline, 2-methylaniline, 2-methoxyaniline, 4-methylaniline, 4-chloroaniline, and 4-bromoaniline) as testing compounds, derivatization conditions such as coupling reagent, basic catalyst, reaction temperature and time, reaction solvent, and fluorescent labeling reagent concentration have also been investigated. With the better PPIA method, chromatographic separation of derivatized aromatic amines exhibited a good baseline resolution on an RP column. At the same time, by online mass spectrometric identification with atmospheric pressure chemical ionization (APCI) source in positive ion mode, the PPIA-labeled derivatives were characterized by easy-to-interpret mass spectra due to the prominent protonated molecular ion m/z [M + H](+) and specific fragment ions (MS/MS) m/z 335 and 295. The linear range is 24.41 fmol-200.0 pmol with correlation coefficients in the range of 0.9996-0.9999, and detection limits of PPIA-labeled aromatic amines are 0.12-0.21 nmol/L (S/N = 3). Method repeatability, precision, and recovery were evaluated and the results were excellent for the efficient HPLC analysis. The most important argument, however, was the high sensitivity and ease-of-handling of the PPIA method. Preliminary experiments with wastewater samples collected from the waterspout of a paper mill and its nearby soil where

  5. VizieR Online Data Catalog: ROSAT detected quasars. II. (Yuan+ 1998)

    Science.gov (United States)

    Yuan, W.; Brinkmann, W.; Siebert, J.; Voges, W.

    1997-11-01

    We have compiled a sample of all radio-quiet quasars or quasars without radio detection from the Veron-Cetty - Veron catalogue (1993, VV93, Cat. ) detected by ROSAT in the ALL-SKY SURVEY (RASS, Voges 1992, in Proc. of the ISY Conference `Space Science', ESA ISY-3, ESA Publications, p.9, See Cat. ), as targets of pointed observations, or as serendipitous sources from pointed observations publicly available from the ROSAT point source catalogue (ROSAT-SRC, Voges et al. 1995, Cat. ). For all sources we used the results of the Standard Analysis Software System (SASS, Voges et al. 1992, in Proc. of the ISY Conference `Space Science', ESA ISY-3, ESA Publications, p.223), employing the most recent processing for the Survey data (RASS-II, Voges et al. 1996, Cat. ). The total number of quasars is 846. 69 of the radio-quiet objects with radio detections have already been presented in a previous paper (Brinkmann, Yuan, & Siebert 1997, Cat. ) using the RASS-I results. 17 objects were found to be radio-loud from recent radio surveys and were marked in the table. When available, the power law photon indices and the corresponding absorption column densities (NH) were estimated from the two hardness ratios given by the SASS, both with free fitted NH and for Galactic absorption. The unabsorbed X-ray flux densities in the ROSAT band (0.1-2.4keV) were calculated from the count rates using the energy to counts conversion factor for power law spectra and Galactic absorption. As the photon index we used the value obtained for the individual source if the estimated 1-σ error is smaller than 0.5, otherwise we used the redshift-dependent mean value (see the paper for details). (1 data file).

  6. ASCS online fault detection and isolation based on an improved MPCA

    Science.gov (United States)

    Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

    2014-09-01

    Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

  7. Twitter-Based Detection of Illegal Online Sale of Prescription Opioid.

    Science.gov (United States)

    Mackey, Tim K; Kalyanam, Janani; Katsuki, Takeo; Lanckriet, Gert

    2017-12-01

    To deploy a methodology accurately identifying tweets marketing the illegal online sale of controlled substances. We first collected tweets from the Twitter public application program interface stream filtered for prescription opioid keywords. We then used unsupervised machine learning (specifically, topic modeling) to identify topics associated with illegal online marketing and sales. Finally, we conducted Web forensic analyses to characterize different types of online vendors. We analyzed 619 937 tweets containing the keywords codeine, Percocet, fentanyl, Vicodin, Oxycontin, oxycodone, and hydrocodone over a 5-month period from June to November 2015. A total of 1778 tweets (marketing the sale of controlled substances online; 90% had imbedded hyperlinks, but only 46 were "live" at the time of the evaluation. Seven distinct URLs linked to Web sites marketing or illegally selling controlled substances online. Our methodology can identify illegal online sale of prescription opioids from large volumes of tweets. Our results indicate that controlled substances are trafficked online via different strategies and vendors. Public Health Implications. Our methodology can be used to identify illegal online sellers in criminal violation of the Ryan Haight Online Pharmacy Consumer Protection Act.

  8. Compensation scheme for online neutron detection using a Gd-covered CdZnTe sensor

    Energy Technology Data Exchange (ETDEWEB)

    Dumazert, Jonathan, E-mail: jonathan.dumazert@cea.fr; Coulon, Romain; Kondrasovs, Vladimir; Boudergui, Karim

    2017-06-11

    The development of portable and personal neutron dosimeters requires compact and efficient radiation sensors. Gd-157, Gd-155 and Cd-113 nuclei present the highest cross-sections for thermal neutron capture among natural isotopes. In order to allow for the exploitation of the low and medium-energy radiative signature of the said captures, the contribution of gamma background radiation, falling into the same energy range, needs to be cancelled out. This paper introduces a thermal neutron detector based on a twin-dense semiconductor scheme. The neutron-sensitive channel takes the form of a Gd-covered CdZnTe crystal, a high density and effective atomic number detection medium. The background compensation will be carried out by means of an identical CdZnTe sensor with a Tb cover. The setting of a hypothesis test aims at discriminating the signal generated by the signature of thermal neutron captures in Gd from statistical fluctuations over the compensation of both independent channels. The measurement campaign conducted with an integrated single-channel chain and two metal Gd and Tb covers, under Cs-137 and Cf-252 irradiations, provides first quantitative results on gamma-rejection and neutron sensitivity. The described study of concept gives grounds for a portable, online-compatible device, operable in conventional to controlled environments.

  9. An online visual loop closure detection method for indoor robotic navigation

    Science.gov (United States)

    Erhan, Can; Sariyanidi, Evangelos; Sencan, Onur; Temeltas, Hakan

    2015-01-01

    In this paper, we present an enhanced loop closure method* based on image-to-image matching relies on quantized local Zernike moments. In contradistinction to the previous methods, our approach uses additional depth information to extract Zernike moments in local manner. These moments are used to represent holistic shape information inside the image. The moments in complex space that are extracted from both grayscale and depth images are coarsely quantized. In order to find out the similarity between two locations, nearest neighbour (NN) classification algorithm is performed. Exemplary results and the practical implementation case of the method are also given with the data gathered on the testbed using a Kinect. The method is evaluated in three different datasets of different lighting conditions. Additional depth information with the actual image increases the detection rate especially in dark environments. The results are referred as a successful, high-fidelity online method for visual place recognition as well as to close navigation loops, which is a crucial information for the well known simultaneously localization and mapping (SLAM) problem. This technique is also practically applicable because of its low computational complexity, and performing capability in real-time with high loop closing accuracy.

  10. Left-hemisphere activation is associated with enhanced vocal pitch error detection in musicians with absolute pitch

    Science.gov (United States)

    Behroozmand, Roozbeh; Ibrahim, Nadine; Korzyukov, Oleg; Robin, Donald A.; Larson, Charles R.

    2014-01-01

    The ability to process auditory feedback for vocal pitch control is crucial during speaking and singing. Previous studies have suggested that musicians with absolute pitch (AP) develop specialized left-hemisphere mechanisms for pitch processing. The present study adopted an auditory feedback pitch perturbation paradigm combined with ERP recordings to test the hypothesis whether the neural mechanisms of the left-hemisphere enhance vocal pitch error detection and control in AP musicians compared with relative pitch (RP) musicians and non-musicians (NM). Results showed a stronger N1 response to pitch-shifted voice feedback in the right-hemisphere for both AP and RP musicians compared with the NM group. However, the left-hemisphere P2 component activation was greater in AP and RP musicians compared with NMs and also for the AP compared with RP musicians. The NM group was slower in generating compensatory vocal reactions to feedback pitch perturbation compared with musicians, and they failed to re-adjust their vocal pitch after the feedback perturbation was removed. These findings suggest that in the earlier stages of cortical neural processing, the right hemisphere is more active in musicians for detecting pitch changes in voice feedback. In the later stages, the left-hemisphere is more active during the processing of auditory feedback for vocal motor control and seems to involve specialized mechanisms that facilitate pitch processing in the AP compared with RP musicians. These findings indicate that the left hemisphere mechanisms of AP ability are associated with improved auditory feedback pitch processing during vocal pitch control in tasks such as speaking or singing. PMID:24355545

  11. Development of online, continuous heavy metals detection and monitoring sensors based on microfluidic plasma reactors

    Science.gov (United States)

    Abdul-Majeed, Wameath Sh

    This research is dedicated to develop a fully integrated system for heavy metals determination in water samples based on micro fluidic plasma atomizers. Several configurations of dielectric barrier discharge (DBD) atomizer are designed, fabricated and tested toward this target. Finally, a combination of annular and rectangular DBD atomizers has been utilized to develop a scheme for heavy metals determination. The present thesis has combined both theoretical and experimental investigations to fulfil the requirements. Several mathematical studies are implemented to explore the optimal design parameters for best system performance. On the other hand, expanded experimental explorations are conducted to assess the proposed operational approaches. The experiments were designed according to a central composite rotatable design; hence, an empirical model has been produced for each studied case. Moreover, several statistical approaches are adopted to analyse the system performance and to deduce the optimal operational parameters.. The introduction of the examined analyte to the plasma atomizer has been achieved by applying chemical schemes, where the element in the sample has been derivitized by using different kinds of reducing agents to produce vapour species (e.g. hydrides) for a group of nine elements examined in this research individually and simultaneously. Moreover, other derivatization schemes based on photochemical vapour generation assisted by ultrasound irradiation are also investigated. Generally speaking, the detection limits achieved in this research for the examined set of elements (by applying hydroborate scheme) are found to be acceptable in accordance with the standard limits in drinking water. The results of copper compared with the data from other technologies in the literature, showed a competitive detection limit obtained from applying the developed scheme, with an advantage of conducting simultaneous, fully automated, insitu, online- real time

  12. Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

    Science.gov (United States)

    Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

    2014-05-27

    It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

  13. Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

    Directory of Open Access Journals (Sweden)

    Zheng-Zhou Li

    2014-05-01

    Full Text Available It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn’t be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

  14. A patient with an inborn error of vitamin B12 metabolism (cblF) detected by newborn screening.

    Science.gov (United States)

    Armour, Christine M; Brebner, Alison; Watkins, David; Geraghty, Michael T; Chan, Alicia; Rosenblatt, David S

    2013-07-01

    A neonate, who was found to have an elevated C3/C2 ratio and minimally elevated propionylcarnitine on newborn screening, was subsequently identified as having the rare cblF inborn error of vitamin B12 (cobalamin) metabolism. This disorder is characterized by the retention of unmetabolized cobalamin in lysosomes such that it is not readily available for cellular metabolism. Although cultured fibroblasts from the patient did not show the expected functional abnormalities of the cobalamin-dependent enzymes, methylmalonyl-CoA mutase and methionine synthase, they did show reduced synthesis of the active cobalamin cofactors adenosylcobalamin and methylcobalamin. Mutation analysis of LMBRD1 established that the patient had the cblF disorder. Treatment was initiated promptly, and the patient showed a robust response to regular injections of cyanocobalamin, and she was later switched to hydroxocobalamin. Currently, at 3 years of age, the child is clinically well, with appropriate development. Adjusted newborn screening cutoffs in Ontario allowed detection of a deficiency that might not have otherwise been identified, allowing early treatment and perhaps preventing the adverse sequelae seen in some untreated patients.

  15. Asymmetrical flow field-flow fractionation with on-line detection for drug transfer studies: a feasibility study

    DEFF Research Database (Denmark)

    Hinna, A.; Steiniger, F.; Hupfeld, S.

    2014-01-01

    Knowledge about drug retention within colloidal carriers is of uppermost importance particularly if drug targeting is anticipated. The aim of the present study was to evaluate asymmetrical flow field-flow fractionation (AF4) with on-line UV/VIS drug quantification for its suitability to determine...... both release and transfer of drug from liposomal carriers to a model acceptor phase consisting of large liposomes. The hydrophobic porphyrin 5,10,15,20-tetrakis(4-hydroxyphenyl)21H,23H-porphine (p-THPP), a fluorescent dye with an absorbance maximum in the visible range and structural similarity...... channel geometries. Drug quantification by on-line absorbance measurements was established by comprehensive evaluation of the size-dependent turbidity contribution in on-line UV/VIS detection and by comparison with off-line results obtained for the respective dye-loaded donor formulations (dissolved...

  16. A New Method to Detect and Correct the Critical Errors and Determine the Software-Reliability in Critical Software-System

    International Nuclear Information System (INIS)

    Krini, Ossmane; Börcsök, Josef

    2012-01-01

    In order to use electronic systems comprising of software and hardware components in safety related and high safety related applications, it is necessary to meet the Marginal risk numbers required by standards and legislative provisions. Existing processes and mathematical models are used to verify the risk numbers. On the hardware side, various accepted mathematical models, processes, and methods exist to provide the required proof. To this day, however, there are no closed models or mathematical procedures known that allow for a dependable prediction of software reliability. This work presents a method that makes a prognosis on the residual critical error number in software. Conventional models lack this ability and right now, there are no methods that forecast critical errors. The new method will show that an estimate of the residual error number of critical errors in software systems is possible by using a combination of prediction models, a ratio of critical errors, and the total error number. Subsequently, the critical expected value-function at any point in time can be derived from the new solution method, provided the detection rate has been calculated using an appropriate estimation method. Also, the presented method makes it possible to make an estimate on the critical failure rate. The approach is modelled on a real process and therefore describes two essential processes - detection and correction process.

  17. Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM in advanced metering infrastructure of smart grid.

    Directory of Open Access Journals (Sweden)

    Yuancheng Li

    Full Text Available Advanced Metering Infrastructure (AMI realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

  18. TU-G-BRD-01: Quantifying the Effectiveness of the Physics Pre-Treatment Plan Review for Detecting Errors in Radiation Therapy

    International Nuclear Information System (INIS)

    Gopan, O; Novak, A; Zeng, J; Ford, E

    2015-01-01

    Purpose: Physics pre-treatment plan review is crucial to safe radiation oncology treatments. Studies show that most errors originate in treatment planning, which underscores the importance of physics plan review. As a QA measure the physics review is of fundamental importance and is central to the profession of medical physics. However, little is known about its effectiveness. More hard data are needed. The purpose of this study was to quantify the effectiveness of physics review with the goal of improving it. Methods: This study analyzed 315 “potentially serious” near-miss incidents within an institutional incident learning system collected over a two-year period. 139 of these originated prior to physics review and were found at the review or after. Incidents were classified as events that: 1)were detected by physics review, 2)could have been detected (but were not), and 3)could not have been detected. Category 1 and 2 events were classified by which specific check (within physics review) detected or could have detected the event. Results: Of the 139 analyzed events, 73/139 (53%) were detected or could have been detected by the physics review; although, 42/73 (58%) were not actually detected. 45/73 (62%) errors originated in treatment planning, making physics review the first step in the workflow that could detect the error. Two specific physics checks were particularly effective (combined effectiveness of >20%): verifying DRRs (8/73) and verifying isocenter (7/73). Software-based plan checking systems were evaluated and found to have potential effectiveness of 40%. Given current data structures, software implementations of some tests such as isocenter verification check would be challenging. Conclusion: Physics plan review is a key safety measure and can detect majority of reported events. However, a majority of events that potentially could have been detected were NOT detected in this study, indicating the need to improve the performance of physics review

  19. Can the error detection mechanism benefit from training the working memory? A comparison between dyslexics and controls--an ERP study.

    Directory of Open Access Journals (Sweden)

    Tzipi Horowitz-Kraus

    Full Text Available BACKGROUND: Based on the relationship between working memory and error detection, we investigated the capacity of adult dyslexic readers' working memory to change as a result of training, and the impact of training on the error detection mechanism. METHODOLOGY: 27 dyslexics and 34 controls, all university students, participated in the study. ERP methodology and behavioral measures were employed prior to, immediately after, and 6 months after training. The CogniFit Personal Coach Program, which consists of 24 sessions of direct training of working memory skills, was used. FINDINGS: Both groups of readers gained from the training program but the dyslexic readers gained significantly more. In the dyslexic group, digit span increased from 9.84+/-3.15 to 10.79+/-3.03. Working memory training significantly increased the number of words per minute read correctly by 14.73%. Adult brain activity changed as a result of training, evidenced by an increase in both working memory capacity and the amplitude of the Error-related Negativity (ERN component (24.71%. When ERN amplitudes increased, the percentage of errors on the Sternberg tests decreased. CONCLUSIONS: We suggest that by expanding the working memory capacity, larger units of information are retained in the system, enabling more effective error detection. The crucial functioning of the central-executive as a sub-component of the working memory is also discussed.

  20. DNA-Inspired Online Behavioral Modeling and Its Application to Spambot Detection

    DEFF Research Database (Denmark)

    Cresci, Stefano; Di Pietro, Roberto; Petrocchi, Marinella

    2016-01-01

    A novel, simple, and effective approach to modeling online user behavior extracts and analyzes digital DNA sequences from user online actions and uses Twitter as a benchmark to test the proposal. Specifically, the model obtains an incisive and compact DNA-inspired characterization of user actions...... methodology is platform and technology agnostic, paving the way for diverse behavioral characterization tasks....

  1. Use of Online Records for Detection of Diseases and Heat in Dairy Cattle Stocks

    DEFF Research Database (Denmark)

    Hansen, Jørgen Vinsløv

    In recent years management of cattle herds has become a much more automated process and machinery for measuring a number of biological entities online has been developed. Analysis of such online data can be helpful to the farmer in the management of the herd. This thesis is a contribution...

  2. On-line detection of key radionuclides for fuel-rod failure in a pressurized water reactor.

    Science.gov (United States)

    Qin, Guoxiu; Chen, Xilin; Guo, Xiaoqing; Ni, Ning

    2016-08-01

    For early on-line detection of fuel rod failure, the key radionuclides useful in monitoring must leak easily from failing rods. Yield, half-life, and mass share of fission products that enter the primary coolant also need to be considered in on-line analyses. From all the nuclides that enter the primary coolant during fuel-rod failure, (135)Xe and (88)Kr were ultimately chosen as crucial for on-line monitoring of fuel-rod failure. A monitoring system for fuel-rod failure detection for pressurized water reactor (PWR) based on the LaBr3(Ce) detector was assembled and tested. The samples of coolant from the PWR were measured using the system as well as a HPGe γ-ray spectrometer. A comparison showed the method was feasible. Finally, the γ-ray spectra of primary coolant were measured under normal operations and during fuel-rod failure. The two peaks of (135)Xe (249.8keV) and (88)Kr (2392.1keV) were visible, confirming that the method is capable of monitoring fuel-rod failure on-line. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

    International Nuclear Information System (INIS)

    Parker, S

    2015-01-01

    Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignment of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic errors

  4. Development of an iterative reconstruction method to overcome 2D detector low resolution limitations in MLC leaf position error detection for 3D dose verification in IMRT

    NARCIS (Netherlands)

    Visser, Ruurd; J., Godart; Wauben, D.J.L.; Langendijk, J.; van 't Veld, A.A.; Korevaar, E.W.

    2016-01-01

    The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a

  5. The influence of random and systematic errors on a general definition of minimum detectable amount (MDA) applicable to all radiobioassay measurements

    International Nuclear Information System (INIS)

    Brodsky, A.

    1985-01-01

    An approach to defining minimum detectable amount (MDA) of radioactivity in a sample will be discussed, with the aim of obtaining comments helpful in developing a formulation of MDA that will be broadly applicable to all kinds of radiobioassay measurements, and acceptable to the scientists who make these measurements. Also, the influence of random and systematic errors on the defined MDA are examined

  6. Bit-error-rate performance analysis of self-heterodyne detected radio-over-fiber links using phase and intensity modulation

    DEFF Research Database (Denmark)

    Yin, Xiaoli; Yu, Xianbin; Tafur Monroy, Idelfonso

    2010-01-01

    We theoretically and experimentally investigate the performance of two self-heterodyne detected radio-over-fiber (RoF) links employing phase modulation (PM) and quadrature biased intensity modulation (IM), in term of bit-error-rate (BER) and optical signal-to-noise-ratio (OSNR). In both links, self...

  7. Action errors, error management, and learning in organizations.

    Science.gov (United States)

    Frese, Michael; Keith, Nina

    2015-01-03

    Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.

  8. An Approach for Implementing State Machines with Online Testability

    Directory of Open Access Journals (Sweden)

    P. K. Lala

    2010-01-01

    Full Text Available During the last two decades, significant amount of research has been performed to simplify the detection of transient or soft errors in VLSI-based digital systems. This paper proposes an approach for implementing state machines that uses 2-hot code for state encoding. State machines designed using this approach allow online detection of soft errors in registers and output logic. The 2-hot code considerably reduces the number of required flip-flops and leads to relatively straightforward implementation of next state and output logic. A new way of designing output logic for online fault detection has also been presented.

  9. Medication errors: prescribing faults and prescription errors.

    Science.gov (United States)

    Velo, Giampaolo P; Minuz, Pietro

    2009-06-01

    1. Medication errors are common in general practice and in hospitals. Both errors in the act of writing (prescription errors) and prescribing faults due to erroneous medical decisions can result in harm to patients. 2. Any step in the prescribing process can generate errors. Slips, lapses, or mistakes are sources of errors, as in unintended omissions in the transcription of drugs. Faults in dose selection, omitted transcription, and poor handwriting are common. 3. Inadequate knowledge or competence and incomplete information about clinical characteristics and previous treatment of individual patients can result in prescribing faults, including the use of potentially inappropriate medications. 4. An unsafe working environment, complex or undefined procedures, and inadequate communication among health-care personnel, particularly between doctors and nurses, have been identified as important underlying factors that contribute to prescription errors and prescribing faults. 5. Active interventions aimed at reducing prescription errors and prescribing faults are strongly recommended. These should be focused on the education and training of prescribers and the use of on-line aids. The complexity of the prescribing procedure should be reduced by introducing automated systems or uniform prescribing charts, in order to avoid transcription and omission errors. Feedback control systems and immediate review of prescriptions, which can be performed with the assistance of a hospital pharmacist, are also helpful. Audits should be performed periodically.

  10. On-line detection of Escherichia coli intrusion in a pilot-scale drinking water distribution system.

    Science.gov (United States)

    Ikonen, Jenni; Pitkänen, Tarja; Kosse, Pascal; Ciszek, Robert; Kolehmainen, Mikko; Miettinen, Ilkka T

    2017-08-01

    Improvements in microbial drinking water quality monitoring are needed for the better control of drinking water distribution systems and for public health protection. Conventional water quality monitoring programmes are not always able to detect a microbial contamination of drinking water. In the drinking water production chain, in addition to the vulnerability of source waters, the distribution networks are prone to contamination. In this study, a pilot-scale drinking-water distribution network with an on-line monitoring system was utilized for detecting bacterial intrusion. During the experimental Escherichia coli intrusions, the contaminant was measured by applying a set of on-line sensors for electric conductivity (EC), pH, temperature (T), turbidity, UV-absorbance at 254 nm (UVAS SC) and with a device for particle counting. Monitored parameters were compared with the measured E. coli counts using the integral calculations of the detected peaks. EC measurement gave the strongest signal compared with the measured baseline during the E. coli intrusion. Integral calculations showed that the peaks in the EC, pH, T, turbidity and UVAS SC data were detected corresponding to the time predicted. However, the pH and temperature peaks detected were barely above the measured baseline and could easily be mixed with the background noise. The results indicate that on-line monitoring can be utilized for the rapid detection of microbial contaminants in the drinking water distribution system although the peak interpretation has to be performed carefully to avoid being mixed up with normal variations in the measurement data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Tracking social contact networks with online respondent-driven detection : who recruits whom?

    NARCIS (Netherlands)

    Stein, Mart L.; van der Heijden, P.G.M.; Buskens, V.W.; van Steenbergen, Jim E.; Bengtsson, Linus; Koppeschaar, Carl E.; Thorson, Anna E.; Kretzschmar, Mirjam E. E.

    2015-01-01

    Background: Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven

  12. Tracking social contact networks with online respondent-driven detection : who recruits whom?

    NARCIS (Netherlands)

    Stein, Mart L; van der Heijden, Peter G M; Buskens, Vincent; van Steenbergen, Jim E; Bengtsson, Linus; Koppeschaar, Carl E; Thorson, Anna; Kretzschmar, MEE

    2015-01-01

    BACKGROUND: Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven

  13. Evaluating IMRT and VMAT dose accuracy: Practical examples of failure to detect systematic errors when applying a commonly used metric and action levels

    Energy Technology Data Exchange (ETDEWEB)

    Nelms, Benjamin E. [Canis Lupus LLC, Merrimac, Wisconsin 53561 (United States); Chan, Maria F. [Memorial Sloan-Kettering Cancer Center, Basking Ridge, New Jersey 07920 (United States); Jarry, Geneviève; Lemire, Matthieu [Hôpital Maisonneuve-Rosemont, Montréal, QC H1T 2M4 (Canada); Lowden, John [Indiana University Health - Goshen Hospital, Goshen, Indiana 46526 (United States); Hampton, Carnell [Levine Cancer Institute/Carolinas Medical Center, Concord, North Carolina 28025 (United States); Feygelman, Vladimir [Moffitt Cancer Center, Tampa, Florida 33612 (United States)

    2013-11-15

    Purpose: This study (1) examines a variety of real-world cases where systematic errors were not detected by widely accepted methods for IMRT/VMAT dosimetric accuracy evaluation, and (2) drills-down to identify failure modes and their corresponding means for detection, diagnosis, and mitigation. The primary goal of detailing these case studies is to explore different, more sensitive methods and metrics that could be used more effectively for evaluating accuracy of dose algorithms, delivery systems, and QA devices.Methods: The authors present seven real-world case studies representing a variety of combinations of the treatment planning system (TPS), linac, delivery modality, and systematic error type. These case studies are typical to what might be used as part of an IMRT or VMAT commissioning test suite, varying in complexity. Each case study is analyzed according to TG-119 instructions for gamma passing rates and action levels for per-beam and/or composite plan dosimetric QA. Then, each case study is analyzed in-depth with advanced diagnostic methods (dose profile examination, EPID-based measurements, dose difference pattern analysis, 3D measurement-guided dose reconstruction, and dose grid inspection) and more sensitive metrics (2% local normalization/2 mm DTA and estimated DVH comparisons).Results: For these case studies, the conventional 3%/3 mm gamma passing rates exceeded 99% for IMRT per-beam analyses and ranged from 93.9% to 100% for composite plan dose analysis, well above the TG-119 action levels of 90% and 88%, respectively. However, all cases had systematic errors that were detected only by using advanced diagnostic techniques and more sensitive metrics. The systematic errors caused variable but noteworthy impact, including estimated target dose coverage loss of up to 5.5% and local dose deviations up to 31.5%. Types of errors included TPS model settings, algorithm limitations, and modeling and alignment of QA phantoms in the TPS. Most of the errors were

  14. Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.

    Science.gov (United States)

    Li, Qi; Melton, Kristin; Lingren, Todd; Kirkendall, Eric S; Hall, Eric; Zhai, Haijun; Ni, Yizhao; Kaiser, Megan; Stoutenborough, Laura; Solti, Imre

    2014-01-01

    Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  15. Using Benford’s Law to detect data error and fraud: An examination of companies listed on the Johannesburg Stock Exchange

    Directory of Open Access Journals (Sweden)

    A Saville

    2014-06-01

    Full Text Available Accounting numbers generally obey a mathematical law called Benford’s Law, and this outcome is so unexpected that manipulators of information generally fail to observe the law. Armed with this knowledge, it becomes possible to detect the occurrence of accounting data that are presented fraudulently. However, the law also allows for the possibility of detecting instances where data are presented containing errors. Given this backdrop, this paper uses data drawn from companies listed on the Johannesburg Stock Exchange to test the hypothesis that Benford’s Law can be used to identify false or fraudulent reporting of accounting data. The results support the argument that Benford’s Law can be used effectively to detect accounting error and fraud. Accordingly, the findings are of particular relevance to auditors, shareholders, financial analysts, investment managers, private investors and other users of publicly reported accounting data, such as the revenue services

  16. A Contrastive Study of Potential and Practical Errors in On-line Translation Due to Linguistic Differences in Chinese, English and Japanese

    OpenAIRE

    Seta, Yukito; Jiang, Fan

    2011-01-01

    Nowadays, some students in China often use on-line translators when they have to write papers, especially the abstract in English or in Japanese. However, the morphological and syntactic differences in Chinese, English and Japanese frequently lead to problems in translation. The present paper aims at exploring the major morphological and syntactic differences among the three languages and demonstrating how these major differences affect translation rendered by on-line translators. Totally, 8 ...

  17. SU-G-BRB-11: On the Sensitivity of An EPID-Based 3D Dose Verification System to Detect Delivery Errors in VMAT Treatments

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez, P; Olaciregui-Ruiz, I; Mijnheer, B; Mans, A; Rozendaal, R [Netherlands Cancer Institute - Antoni van Leeuwenhoek, Amsterdam, Noord-Holland (Netherlands)

    2016-06-15

    Purpose: To investigate the sensitivity of an EPID-based 3D dose verification system to detect delivery errors in VMAT treatments. Methods: For this study 41 EPID-reconstructed 3D in vivo dose distributions of 15 different VMAT plans (H&N, lung, prostate and rectum) were selected. To simulate the effect of delivery errors, their TPS plans were modified by: 1) scaling of the monitor units by ±3% and ±6% and 2) systematic shifting of leaf bank positions by ±1mm, ±2mm and ±5mm. The 3D in vivo dose distributions where then compared to the unmodified and modified treatment plans. To determine the detectability of the various delivery errors, we made use of a receiver operator characteristic (ROC) methodology. True positive and false positive rates were calculated as a function of the γ-parameters γmean, γ1% (near-maximum γ) and the PTV dose parameter ΔD{sub 50} (i.e. D{sub 50}(EPID)-D{sub 50}(TPS)). The ROC curve is constructed by plotting the true positive rate vs. the false positive rate. The area under the ROC curve (AUC) then serves as a measure of the performance of the EPID dosimetry system in detecting a particular error; an ideal system has AUC=1. Results: The AUC ranges for the machine output errors and systematic leaf position errors were [0.64 – 0.93] and [0.48 – 0.92] respectively using γmean, [0.57 – 0.79] and [0.46 – 0.85] using γ1% and [0.61 – 0.77] and [ 0.48 – 0.62] using ΔD{sub 50}. Conclusion: For the verification of VMAT deliveries, the parameter γmean is the best discriminator for the detection of systematic leaf position errors and monitor unit scaling errors. Compared to γmean and γ1%, the parameter ΔD{sub 50} performs worse as a discriminator in all cases.

  18. Impact of habitat-specific GPS positional error on detection of movement scales by first-passage time analysis.

    Directory of Open Access Journals (Sweden)

    David M Williams

    Full Text Available Advances in animal tracking technologies have reduced but not eliminated positional error. While aware of such inherent error, scientists often proceed with analyses that assume exact locations. The results of such analyses then represent one realization in a distribution of possible outcomes. Evaluating results within the context of that distribution can strengthen or weaken our confidence in conclusions drawn from the analysis in question. We evaluated the habitat-specific positional error of stationary GPS collars placed under a range of vegetation conditions that produced a gradient of canopy cover. We explored how variation of positional error in different vegetation cover types affects a researcher's ability to discern scales of movement in analyses of first-passage time for white-tailed deer (Odocoileus virginianus. We placed 11 GPS collars in 4 different vegetative canopy cover types classified as the proportion of cover above the collar (0-25%, 26-50%, 51-75%, and 76-100%. We simulated the effect of positional error on individual movement paths using cover-specific error distributions at each location. The different cover classes did not introduce any directional bias in positional observations (1 m≤mean≤6.51 m, 0.24≤p≤0.47, but the standard deviation of positional error of fixes increased significantly with increasing canopy cover class for the 0-25%, 26-50%, 51-75% classes (SD = 2.18 m, 3.07 m, and 4.61 m, respectively and then leveled off in the 76-100% cover class (SD = 4.43 m. We then added cover-specific positional errors to individual deer movement paths and conducted first-passage time analyses on the noisy and original paths. First-passage time analyses were robust to habitat-specific error in a forest-agriculture landscape. For deer in a fragmented forest-agriculture environment, and species that move across similar geographic extents, we suggest that first-passage time analysis is robust with regard to

  19. Embedded vision equipment of industrial robot for inline detection of product errors by clustering–classification algorithms

    Directory of Open Access Journals (Sweden)

    Kamil Zidek

    2016-10-01

    Full Text Available The article deals with the design of embedded vision equipment of industrial robots for inline diagnosis of product error during manipulation process. The vision equipment can be attached to the end effector of robots or manipulators, and it provides an image snapshot of part surface before grasp, searches for error during manipulation, and separates products with error from the next operation of manufacturing. The new approach is a methodology based on machine teaching for the automated identification, localization, and diagnosis of systematic errors in products of high-volume production. To achieve this, we used two main data mining algorithms: clustering for accumulation of similar errors and classification methods for the prediction of any new error to proposed class. The presented methodology consists of three separate processing levels: image acquisition for fail parameterization, data clustering for categorizing errors to separate classes, and new pattern prediction with a proposed class model. We choose main representatives of clustering algorithms, for example, K-mean from quantization of vectors, fast library for approximate nearest neighbor from hierarchical clustering, and density-based spatial clustering of applications with noise from algorithm based on the density of the data. For machine learning, we selected six major algorithms of classification: support vector machines, normal Bayesian classifier, K-nearest neighbor, gradient boosted trees, random trees, and neural networks. The selected algorithms were compared for speed and reliability and tested on two platforms: desktop-based computer system and embedded system based on System on Chip (SoC with vision equipment.

  20. Determination of organic peroxides by liquid chromatography with on-line post-column ultraviolet irradiation and peroxyoxalate chemiluminescence detection.

    Science.gov (United States)

    Wada, Mitsuhiro; Inoue, Keiyu; Thara, Ayuko; Kishikawa, Naoya; Nakashima, Kenichiro; Kuroda, Naotaka

    2003-02-14

    A HPLC method was developed for the simultaneous determination of organic peroxides and hydrogen peroxide with peroxyoxalate chemiluminescence (PO-CL) detection following on-line UV irradiation. Organic peroxides [i.e., benzoyl peroxide (BP), tert.-butyl hydroperoxide (BHP), tert.-butyl perbenzoate (BPB), cumene hydroperoxide (CHP)] were UV irradiated (254 nm, 15 W) to generate hydrogen peroxide, which was determined by PO-CL detection. The conditions for UV irradiation and PO-CL detection were optimized by a flow injection analysis (FIA) system. Generation of hydrogen peroxide from peroxides with on-line UV irradiation also was confirmed by the FIA system by incorporating an enzyme column reactor immobilized with catalase. The separation of four organic peroxides and hydrogen peroxide by HPLC was accomplished isocratically on an ODS column within 30 min. The detection limits (signal-to-noise ratio=3) were 1.1 microM for hydrogen peroxide, 6.8 microM for BP, 31.3 microM for BHP, 7.5 microM for BPB and 1.3 microM for CHP. The proposed method was applied to the determination of BP in wheat flour.

  1. On-line low and high frequency acoustic leak detection and location for an automated steam generator protection system

    International Nuclear Information System (INIS)

    Gaubatz, D.C.; Gluekler, E.L.

    1990-01-01

    Two on-line acoustic leak detection systems were operated and installed on a 76 MW hockey stick steam generator in the Sodium Components Test Installation (SCTI) at the Energy Technology Engineering Center (ETEC) in Southern California. The low frequency system demonstrated the capability to detect and locate leaks, both intentional and unintentional. No false alarms were issued during the two year test program even with adjacent blasting activities, pneumatic drilling, shuttle rocket engine testing nearby, scrams of the SCTI facility, thermal/hydraulic transient testing, and pump/control valve operations. For the high frequency system the capability to detect water into sodium reactions was established utilizing frequencies as high as 300 kHz. The high frequency system appeared to be sensitive to noise generated by maintenance work and system valve operations. Subsequent development work which is incomplete as of this date showed much more promise for the high frequency system. (author). 13 figs

  2. "Newbies" and "Celebrities": Detecting Social Roles in an Online Network of Teachers via Participation Patterns

    Science.gov (United States)

    Smith Risser, H.; Bottoms, SueAnn

    2014-01-01

    The advent of social networking tools allows teachers to create online networks and share information. While some virtual networks have a formal structure and defined boundaries, many do not. These unstructured virtual networks are difficult to study because they lack defined boundaries and a formal structure governing leadership roles and the…

  3. Automatic analysis of online image data for law enforcement agencies by concept detection and instance search

    NARCIS (Netherlands)

    Boer, M.H.T. de; Bouma, H.; Kruithof, M.C.; Haar, F.B. ter; Fischer, N.M.; Hagendoorn, L.K.; Joosten, B.; Raaijmakers, S.

    2017-01-01

    The information available on-line and off-line, from open as well as from private sources, is growing at an exponential rate and places an increasing demand on the limited resources of Law Enforcement Agencies (LEAs). The absence of appropriate tools and techniques to collect, process, and analyze

  4. Automatic Detection of Online Recruitment Frauds: Characteristics, Methods, and a Public Dataset

    Directory of Open Access Journals (Sweden)

    Sokratis Vidros

    2017-03-01

    Full Text Available The critical process of hiring has relatively recently been ported to the cloud. Specifically, the automated systems responsible for completing the recruitment of new employees in an online fashion, aim to make the hiring process more immediate, accurate and cost-efficient. However, the online exposure of such traditional business procedures has introduced new points of failure that may lead to privacy loss for applicants and harm the reputation of organizations. So far, the most common case of Online Recruitment Frauds (ORF, is employment scam. Unlike relevant online fraud problems, the tackling of ORF has not yet received the proper attention, remaining largely unexplored until now. Responding to this need, the work at hand defines and describes the characteristics of this severe and timely novel cyber security research topic. At the same time, it contributes and evaluates the first to our knowledge publicly available dataset of 17,880 annotated job ads, retrieved from the use of a real-life system.

  5. Online screening of homogeneous catalyst performance using reaction detection mass spectrometry

    NARCIS (Netherlands)

    Martha, C.T.; Elders, N.; Krabbe, J.G.; Kool, J.; Niessen, W.M.A.; Orru, R.V.A.; Irth, H.

    2008-01-01

    An integrated online screening system was developed to rapidly screen homogeneous catalysts for activity toward a selected synthesis. The continuous-flow system comprises standard HPLC pumps for the delivery of substrates, an HPLC autosampler for the injection of homogeneous catalysts, a

  6. An on-line high performance liquid chromatography-crocin bleaching assay for detection of antioxidants

    NARCIS (Netherlands)

    Bountagkidou, O.; Klift, van der E.J.C.; Tsimidou, M.Z.; Ordoudi, S.A.; Beek, van T.A.

    2012-01-01

    An on-line HPLC (high performance liquid chromatography) method for the rapid screening of individual antioxidants in mixtures was developed using crocin as a substrate (i.e. oxidation probe) and 2,2'-azobis(2-amidinopropane dihydrochloride (AAPH)) in phosphate buffer (pH 7.5) as a radical

  7. Use of an online survey to detect reasons for low physical activity in COPD patients

    NARCIS (Netherlands)

    Vorrink, S.N.W.; Kort, H.S.M.; Lammers, J.J.

    2012-01-01

    We developed an online survey for COPD patients to investigate which reasons patients themselves list for being less active. In addition, this survey provides information on whether the internet proves to be a usable platform to administer surveys in COPD patients.

  8. Adaptive algorithm of selecting optimal variant of errors detection system for digital means of automation facility of oil and gas complex

    Science.gov (United States)

    Poluyan, A. Y.; Fugarov, D. D.; Purchina, O. A.; Nesterchuk, V. V.; Smirnova, O. V.; Petrenkova, S. B.

    2018-05-01

    To date, the problems associated with the detection of errors in digital equipment (DE) systems for the automation of explosive objects of the oil and gas complex are extremely actual. Especially this problem is actual for facilities where a violation of the accuracy of the DE will inevitably lead to man-made disasters and essential material damage, at such facilities, the diagnostics of the accuracy of the DE operation is one of the main elements of the industrial safety management system. In the work, the solution of the problem of selecting the optimal variant of the errors detection system of errors detection by a validation criterion. Known methods for solving these problems have an exponential valuation of labor intensity. Thus, with a view to reduce time for solving the problem, a validation criterion is compiled as an adaptive bionic algorithm. Bionic algorithms (BA) have proven effective in solving optimization problems. The advantages of bionic search include adaptability, learning ability, parallelism, the ability to build hybrid systems based on combining. [1].

  9. Very low-energy conversion electron detection (VLECED) system at the isocele on-line isotope separator, Orsay

    International Nuclear Information System (INIS)

    Kilcher, P.; Sauvage, J.; Munsch, J.; Obert, J.; Caruette, A.; Ferro, A.; Boissier, G.; Fournet-Fayas, J.; Ducourtieux, M.; Landois, G.

    1988-01-01

    A system designed and installed at the on-line isotope separator ISOCELE II allows the high resolution detection of low-energy conversion electrons (down to 1 keV) emitted by mass separated radioactive sources: the use of a special tape transport permits both the slowing down of the incoming beam of radioactive ions up to a collection point and the acceleration of the electrons emitted by the collected sources brought to a flat magnetic spectrograph. Typical spectra so obtained are presented

  10. Error Detection-Based Model to Assess Educational Outcomes in Crisis Resource Management Training: A Pilot Study.

    Science.gov (United States)

    Bouhabel, Sarah; Kay-Rivest, Emily; Nhan, Carol; Bank, Ilana; Nugus, Peter; Fisher, Rachel; Nguyen, Lily Hp

    2017-06-01

    Otolaryngology-head and neck surgery (OTL-HNS) residents face a variety of difficult, high-stress situations, which may occur early in their training. Since these events occur infrequently, simulation-based learning has become an important part of residents' training and is already well established in fields such as anesthesia and emergency medicine. In the domain of OTL-HNS, it is gradually gaining in popularity. Crisis Resource Management (CRM), a program adapted from the aviation industry, aims to improve outcomes of crisis situations by attempting to mitigate human errors. Some examples of CRM principles include cultivating situational awareness; promoting proper use of available resources; and improving rapid decision making, particularly in high-acuity, low-frequency clinical situations. Our pilot project sought to integrate CRM principles into an airway simulation course for OTL-HNS residents, but most important, it evaluated whether learning objectives were met, through use of a novel error identification model.

  11. Development of on-line monitoring device to detect the presence/absence of sodium vapor

    International Nuclear Information System (INIS)

    Wolson, R.D.; McPheeters, C.C.; Kremesec, V.J.; Kolba, V.M.

    1983-03-01

    A process is being developed by the Sodium Waste Technology Program at ANL-W to remove metallic sodium from scrap and waste. The final step in the process is the removal of residual metallic sodium by evaporation at temperatures up to 482 0 C (900 0 F) and at pressures of about 10 - 2 torr (1.3 Pa). Efficient operation of this process requires that the operators have a method to indicate the completion of the evaporation. This end point would signify when the chamber and scrap and waste is free of metallic sodium. It was determined that a measure of the vacuum was not sufficiently sensitive, and a research effort was undertaken to select an on-line monitoring device. In this effort, three promising methods were reviewed. The use of quadrupole mass spectrometer was recommended and an on-line device was designed for use in a Sodium Process Demonstration (SPD) Plant

  12. Online Detection of Anomalous Sub-trajectories: A Sliding Window Approach Based on Conformal Anomaly Detection and Local Outlier Factor

    OpenAIRE

    Laxhammar , Rikard; Falkman , Göran

    2012-01-01

    Part 4: First Conformal Prediction and Its Applications Workshop (COPA 2012); International audience; Automated detection of anomalous trajectories is an important problem in the surveillance domain. Various algorithms based on learning of normal trajectory patterns have been proposed for this problem. Yet, these algorithms suffer from one or more of the following limitations: First, they are essentially designed for offline anomaly detection in databases. Second, they are insensitive to loca...

  13. Use of error-detection and diagnosis methods in existing buildings - Final report; Einsatz von Fehlerdetektions- und Diagnosemethoden in realen Gebaeuden (IEA Annex 34) - Schlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Gruber, P.

    2000-10-15

    This report for the Swiss Federal Office of Energy (SFOE) discusses the results of tests made with two expert systems used for error-detection and diagnosis in existing buildings. These expert systems were developed within the framework of the International Energy Agency's (IEA) Annex 25 Project entitled 'Real Time Simulation of Heating, Ventilation and Air-conditioning (HVAC) Systems for Building Optimisation, Fault Detection and Diagnosis'. The aim of using these tools was to help detect planning, installation and commissioning errors. These cannot only affect system performance but also can cause increased energy consumption and a reduction of the working life of the system's components. The tests of the tools took place within the framework of the IEA's Annex 34 'Computer-aided Evaluation of HVAC System Performance: the Practical Application of Fault Detection and Diagnosis Techniques in Real Buildings'. Experience gained with the two tools is presented and discussed. The quality of the results and the use of the systems in practice are discussed and commented on. They strongly differ from one tool to the other.

  14. Exploiting Sequential Injection on-line Solvent Extraction/Back Extraction with Detection by ETAAS or ICPMS

    DEFF Research Database (Denmark)

    Wang, Jianhua; Hansen, Elo Harald

    presents an on-line SI-solvent extraction/back extraction procedure used in connection with detection by either ETAAS or ICPMS. Incorporating two newly designed dual-conical gravitational phase separators, its performance is demonstrated for the determination of various metals in reference materials.......Electrothermal atomic absorption spectrometry (ETAAS) and inductively coupled plasma mass spectrometry (ICPMS) are highly sensitive techniques for trace metal analyses. Nevertheless, separation/preconcentration procedures are often called for in order to overcome their inherent low matrix...... tolerances. With detection by ETAAS, separation/preconcentration by solvent extraction has enjoyed much use. However, this approach is not necessarily the optimal one since introduction of organic eluates directly into the graphite tube might lead to deteriorated reproducibility and lower sensitivity...

  15. Exploiting sequential injection on-line solvent extraction/back extraction with detection by ETAAS and ICPMS

    DEFF Research Database (Denmark)

    Wang, Jianhua; Hansen, Elo Harald

    presents an on-line SI-solvent extraction/back extraction procedure used in connection with detection by either ETAAS or ICPMS. Incorporating two newly designed dual-conical gravitational phase separators, its performance is demonstrated for the determination of various metals in reference materials.......Electrothermal atomic absorption spectrometry (ETAAS) and inductively coupled plasma mass spectrometry (ICPMS) are highly sensitive techniques for trace metal analyses. Nevertheless, separation/preconcentration procedures are often called for in order to overcome their inherent low matrix tolerance....... With detection by ETAAS, separation/preconcentration by solvent extraction has enjoyed much use. However, this approach is not necessarily the optimal one since introduction of organic eluates directly into the graphite tube might lead to deteriorated reproducibility and lower sensitivity. And for ICPMS...

  16. Experimental study to optimize time resolution and detection limit of online 222Rn-in-water measurements

    International Nuclear Information System (INIS)

    Just, G.; Freyer, K.; Treutler, H.C.; Philipsborn, H. von

    2001-01-01

    The possibility to detect short-term variations of the activity concentration of 222 Rn in water by online monitoring with temporal resolutions of a few minutes and a lower limit of detection of about 1 Bq/l enhances the applicability of such measurements. New applications would be possible in the field of hydro-geology in which Rn is used as tracer gas, the monitoring of pumping procedures, for the study of exchange processes during groundwater sampling and for various applications with geophysical effects. A suitable, simple method is the measuring principle proposed by Surbeck (Fribourg) some years ago which is based on the separation of air and water by a diffusion membrane. Process parameters enhancing the time resolution of the method as well as the efficiency of different radon detectors have been studied. (orig.) [de

  17. A New On-Line Detecting Apparatus of the Residual Chlorine in Disinfectant for Fresh-Cut Vegetables

    Science.gov (United States)

    Hu, Chao; Su, Shu-Qiang; Li, Bao-Guo; Liu, Meng-Fang

    With the fast development of modern food and beverage industry, fresh-cut vegetables have wider application than before. During the process of sterilization in fresh-cut vegetables, the concentration of chloric disinfectant is usually so high that the common sensor can't be used directly on the product line. In order to solve this problem, we have invented a new detecting apparatus which could detect high concentration of chloric disinfectant directly. In this paper, the working principle, main monitor indicators, application and technical creations of the on-line apparatus have been discussed, and we also carried on the experimental analysis for its performance. The actual demands in factory could be met when the detecting flux is 2L/min, the dilution ratio is 15 and input amount of the disinfectant is 200ml per time, the max of the detecting deviation achieves ±4.8ppm(mg/L). The main detecting range of residual chlorine is 0~300ppm.

  18. Error Patterns

    NARCIS (Netherlands)

    Hoede, C.; Li, Z.

    2001-01-01

    In coding theory the problem of decoding focuses on error vectors. In the simplest situation code words are $(0,1)$-vectors, as are the received messages and the error vectors. Comparison of a received word with the code words yields a set of error vectors. In deciding on the original code word,

  19. Online production validation in a HEP environment

    Energy Technology Data Exchange (ETDEWEB)

    Harenberg, T.; Lang, N.; Maettig, P.; Sandhoff, M.; Volkmer, F. [Bergische Universitaet, Wuppertal (Germany); Kuhl, T. [DESY Zeuthen, Zeuthen (Germany); Schwanenberger, C. [DESY Hamburg, Hamburg (Germany)

    2017-03-15

    In high energy physics (HEP) event simulations, petabytes of data are processed and stored requiring millions of CPU-years. This enormous demand for computing resources is handled by centers distributed worldwide, which form part of the LHC computing grid. The consumption of such an important amount of resources demands for an efficient production of simulation and for the early detection of potential errors. In this article we present a new monitoring framework for grid environments, which polls a measure of data quality during job execution. This online monitoring facilitates the early detection of configuration errors (specially in simulation parameters), and may thus contribute to significant savings in computing resources. (orig.)

  20. Online ICPMS detection of the thermal release of fission products from nuclear fuel samples

    International Nuclear Information System (INIS)

    Guenther-Leopold, I.; Svedkauskaite-Le Gore, J.; Kivel, N.

    2009-01-01

    Full text: The release of volatile and semi-volatile fission products (like Cs, Tc, Mo etc.) from spent nuclear fuel by thermal and thermochemical treatment (oxidative or reductive conditions) as a head-end step for advanced reprocessing scenarios is studied in the Hot Laboratory of the Paul Scherrer Institut. For this purpose, a heated sampling cell online connected to an ICPMS (Element 2, Thermo Fisher Scientific) was designed and tested on simulated fuel samples up to 650 o C. The results of this study as well as technical perspectives for heating experiments up to 2000 o C will be presented. (author)

  1. New algorithms for motion error detection of numerical control machine tool by laser tracking measurement on the basis of GPS principle

    Science.gov (United States)

    Wang, Jindong; Chen, Peng; Deng, Yufen; Guo, Junjie

    2018-01-01

    As a three-dimensional measuring instrument, the laser tracker is widely used in industrial measurement. To avoid the influence of angle measurement error on the overall measurement accuracy, the multi-station and time-sharing measurement with a laser tracker is introduced on the basis of the global positioning system (GPS) principle in this paper. For the proposed method, how to accurately determine the coordinates of each measuring point by using a large amount of measured data is a critical issue. Taking detecting motion error of a numerical control machine tool, for example, the corresponding measurement algorithms are investigated thoroughly. By establishing the mathematical model of detecting motion error of a machine tool with this method, the analytical algorithm concerning on base station calibration and measuring point determination is deduced without selecting the initial iterative value in calculation. However, when the motion area of the machine tool is in a 2D plane, the coefficient matrix of base station calibration is singular, which generates a distortion result. In order to overcome the limitation of the original algorithm, an improved analytical algorithm is also derived. Meanwhile, the calibration accuracy of the base station with the improved algorithm is compared with that with the original analytical algorithm and some iterative algorithms, such as the Gauss-Newton algorithm and Levenberg-Marquardt algorithm. The experiment further verifies the feasibility and effectiveness of the improved algorithm. In addition, the different motion areas of the machine tool have certain influence on the calibration accuracy of the base station, and the corresponding influence of measurement error on the calibration result of the base station depending on the condition number of coefficient matrix are analyzed.

  2. Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents

    International Nuclear Information System (INIS)

    Zhang, Jing; Ghate, Sujata V.; Yoon, Sora C.; Lo, Joseph Y.; Kuzmiak, Cherie M.; Mazurowski, Maciej A.

    2014-01-01

    Purpose: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach to trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. Methods: The authors’ algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. Results: The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different

  3. Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Jing, E-mail: jing.zhang2@duke.edu; Ghate, Sujata V.; Yoon, Sora C. [Department of Radiology, Duke University School of Medicine, Durham, North Carolina 27705 (United States); Lo, Joseph Y. [Department of Radiology, Duke University School of Medicine, Durham, North Carolina 27705 (United States); Duke Cancer Institute, Durham, North Carolina 27710 (United States); Departments of Biomedical Engineering and Electrical and Computer Engineering, Duke University, Durham, North Carolina 27705 (United States); Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Kuzmiak, Cherie M. [Department of Radiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina 27599 (United States); Mazurowski, Maciej A. [Department of Radiology, Duke University School of Medicine, Durham, North Carolina 27705 (United States); Duke Cancer Institute, Durham, North Carolina 27710 (United States); Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States)

    2014-09-15

    Purpose: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach to trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. Methods: The authors’ algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. Results: The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different

  4. Small Microbial Three-Electrode Cell Based Biosensor for Online Detection of Acute Water Toxicity.

    Science.gov (United States)

    Yu, Dengbin; Zhai, Junfeng; Liu, Changyu; Zhang, Xueping; Bai, Lu; Wang, Yizhe; Dong, Shaojun

    2017-11-22

    The monitoring of toxicity of water is very important to estimate the safety of drinking water and the level of water pollution. Herein, a small microbial three-electrode cell (M3C) biosensor filled with polystyrene particles was proposed for online monitoring of the acute water toxicity. The peak current of the biosensor related with the performance of the bioanode was regarded as the toxicity indicator, and thus the acute water toxicity could be determined in terms of inhibition ratio by comparing the peak current obtained with water sample to that obtained with nontoxic standard water. The incorporation of polystyrene particles in the electrochemical cell not only reduced the volume of the samples used, but also improved the sensitivity of the biosensor. Experimental conditions including washing time with PBS and the concentration of sodium acetate solution were optimized. The stability of the M3C biosensor under optimal conditions was also investigated. The M3C biosensor was further examined by formaldehyde at the concentration of 0.01%, 0.03%, and 0.05% (v/v), and the corresponding inhibition ratios were 14.6%, 21.6%, and 36.4%, respectively. This work provides a new insight into the development of an online toxicity detector based on M3C biosensor.

  5. Effect of background correction on peak detection and quantification in online comprehensive two-dimensional liquid chromatography using diode array detection.

    Science.gov (United States)

    Allen, Robert C; John, Mallory G; Rutan, Sarah C; Filgueira, Marcelo R; Carr, Peter W

    2012-09-07

    A singular value decomposition-based background correction (SVD-BC) technique is proposed for the reduction of background contributions in online comprehensive two-dimensional liquid chromatography (LC×LC) data. The SVD-BC technique was compared to simply subtracting a blank chromatogram from a sample chromatogram and to a previously reported background correction technique for one dimensional chromatography, which uses an asymmetric weighted least squares (AWLS) approach. AWLS was the only background correction technique to completely remove the background artifacts from the samples as evaluated by visual inspection. However, the SVD-BC technique greatly reduced or eliminated the background artifacts as well and preserved the peak intensity better than AWLS. The loss in peak intensity by AWLS resulted in lower peak counts at the detection thresholds established using standards samples. However, the SVD-BC technique was found to introduce noise which led to detection of false peaks at the lower detection thresholds. As a result, the AWLS technique gave more precise peak counts than the SVD-BC technique, particularly at the lower detection thresholds. While the AWLS technique resulted in more consistent percent residual standard deviation values, a statistical improvement in peak quantification after background correction was not found regardless of the background correction technique used. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. On-line runaway detection in batch reactors using chaos theory techniques.

    NARCIS (Netherlands)

    Strozzi, F.; Strozzi, F.; Zaldivar, J.M.; Zaldivar, J.M.; Kronberg, Alexandre E.; Westerterp, K.R.

    1999-01-01

    In this work nonlinear time-series analysis using delay coordinate embedding was applied to simulated temperature data from isoperibolic batch reactors to develop an early-warning detection system of the runaway. In the first part of this study an early-warning detection criterion, that is, when the

  7. Retinopathy online challenge: automatic detection of microaneurysms in digital color fundus photographs.

    NARCIS (Netherlands)

    Niemeijer, M.; Ginneken, B. van; Cree, M.J.; Mizutani, A.; Quellec, G.; Sanchez, C.I.; Zhang, B.; Hornero, R.; Lamard, M.; Muramatsu, C.; Wu, X.; Cazuguel, G.; You, J.; Mayo, A.; Li, Q.; Hatanaka, Y.; Cochener, B.; Roux, C.; Karray, F.; Garcia, M.; Fujita, H.; Abramoff, M.D.

    2010-01-01

    The detection of microaneurysms in digital color fundus photographs is a critical first step in automated screening for diabetic retinopathy (DR), a common complication of diabetes. To accomplish this detection numerous methods have been published in the past but none of these was compared with each

  8. SentiHealth-Cancer: A sentiment analysis tool to help detecting mood of patients in online social networks.

    Science.gov (United States)

    Rodrigues, Ramon Gouveia; das Dores, Rafael Marques; Camilo-Junior, Celso G; Rosa, Thierson Couto

    2016-01-01

    Cancer is a critical disease that affects millions of people and families around the world. In 2012 about 14.1 million new cases of cancer occurred globally. Because of many reasons like the severity of some cases, the side effects of some treatments and death of other patients, cancer patients tend to be affected by serious emotional disorders, like depression, for instance. Thus, monitoring the mood of the patients is an important part of their treatment. Many cancer patients are users of online social networks and many of them take part in cancer virtual communities where they exchange messages commenting about their treatment or giving support to other patients in the community. Most of these communities are of public access and thus are useful sources of information about the mood of patients. Based on that, Sentiment Analysis methods can be useful to automatically detect positive or negative mood of cancer patients by analyzing their messages in these online communities. The objective of this work is to present a Sentiment Analysis tool, named SentiHealth-Cancer (SHC-pt), that improves the detection of emotional state of patients in Brazilian online cancer communities, by inspecting their posts written in Portuguese language. The SHC-pt is a sentiment analysis tool which is tailored specifically to detect positive, negative or neutral messages of patients in online communities of cancer patients. We conducted a comparative study of the proposed method with a set of general-purpose sentiment analysis tools adapted to this context. Different collections of posts were obtained from two cancer communities in Facebook. Additionally, the posts were analyzed by sentiment analysis tools that support the Portuguese language (Semantria and SentiStrength) and by the tool SHC-pt, developed based on the method proposed in this paper called SentiHealth. Moreover, as a second alternative to analyze the texts in Portuguese, the collected texts were automatically translated

  9. Oestrus Detection in Dairy Cows from Activity and Lying Data using on-line Individual Models

    DEFF Research Database (Denmark)

    Jónsson, Ragnar Ingi; Blanke, Mogens; Poulsen, Niels Kjølstad

    2011-01-01

    -line from data to cope with behaviours of individuals. Performance is validated on 18 sequences of data where definite proof of prior oestrus was available in form of subsequent pregnancy. These data were extracted from data sequences from 44 dairy cows over an 8 months period. The results show sensitivity......Automated monitoring and detection of oestrus in dairy cows is attractive for reasons of economy in dairy farming. While high performance detection has been shown possible using high-priced progesterone measurements, detection results were less reliable when only low-cost sensor data were available....... Aiming at improving detection scheme reliability with the use of low-cost sensor data, this study combines information from step count and leg tilt sensors. Introducing a lying balance for the individual animal, a novel change detection scheme is derived from observed distributions of the step count data...

  10. Automated Patient Identification and Localization Error Detection Using 2-Dimensional to 3-Dimensional Registration of Kilovoltage X-Ray Setup Images

    International Nuclear Information System (INIS)

    Lamb, James M.; Agazaryan, Nzhde; Low, Daniel A.

    2013-01-01

    Purpose: To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials: Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results: A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions: An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments

  11. Automated Patient Identification and Localization Error Detection Using 2-Dimensional to 3-Dimensional Registration of Kilovoltage X-Ray Setup Images

    Energy Technology Data Exchange (ETDEWEB)

    Lamb, James M., E-mail: jlamb@mednet.ucla.edu; Agazaryan, Nzhde; Low, Daniel A.

    2013-10-01

    Purpose: To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials: Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results: A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions: An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments.

  12. Automated patient identification and localization error detection using 2-dimensional to 3-dimensional registration of kilovoltage x-ray setup images.

    Science.gov (United States)

    Lamb, James M; Agazaryan, Nzhde; Low, Daniel A

    2013-10-01

    To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. DeAnnIso: a tool for online detection and annotation of isomiRs from small RNA sequencing data.

    Science.gov (United States)

    Zhang, Yuanwei; Zang, Qiguang; Zhang, Huan; Ban, Rongjun; Yang, Yifan; Iqbal, Furhan; Li, Ao; Shi, Qinghua

    2016-07-08

    Small RNA (sRNA) Sequencing technology has revealed that microRNAs (miRNAs) are capable of exhibiting frequent variations from their canonical sequences, generating multiple variants: the isoforms of miRNAs (isomiRs). However, integrated tool to precisely detect and systematically annotate isomiRs from sRNA sequencing data is still in great demand. Here, we present an online tool, DeAnnIso (Detection and Annotation of IsomiRs from sRNA sequencing data). DeAnnIso can detect all the isomiRs in an uploaded sample, and can extract the differentially expressing isomiRs from paired or multiple samples. Once the isomiRs detection is accomplished, detailed annotation information, including isomiRs expression, isomiRs classification, SNPs in miRNAs and tissue specific isomiR expression are provided to users. Furthermore, DeAnnIso provides a comprehensive module of target analysis and enrichment analysis for the selected isomiRs. Taken together, DeAnnIso is convenient for users to screen for isomiRs of their interest and useful for further functional studies. The server is implemented in PHP + Perl + R and available to all users for free at: http://mcg.ustc.edu.cn/bsc/deanniso/ and http://mcg2.ustc.edu.cn/bsc/deanniso/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. A Multiple-Model Particle Filter Fusion Algorithm for GNSS/DR Slide Error Detection and Compensation

    Directory of Open Access Journals (Sweden)

    Rafael Toledo-Moreo

    2018-03-01

    Full Text Available Continuous accurate positioning is a key element for the deployment of many advanced driver assistance systems (ADAS and autonomous vehicle navigation. To achieve the necessary performance, global navigation satellite systems (GNSS must be combined with other technologies. A common onboard sensor-set that allows keeping the cost low, features the GNSS unit, odometry, and inertial sensors, such as a gyro. Odometry and inertial sensors compensate for GNSS flaws in many situations and, in normal conditions, their errors can be easily characterized, thus making the whole solution not only more accurate but also with more integrity. However, odometers do not behave properly when friction conditions make the tires slide. If not properly considered, the positioning perception will not be sound. This article introduces a hybridization approach that takes into consideration the sliding situations by means of a multiple model particle filter (MMPF. Tests with real datasets show the goodness of the proposal.

  15. Online platform for applying space–time scan statistics for prospectively detecting emerging hot spots of dengue fever

    Directory of Open Access Journals (Sweden)

    Chien-Chou Chen

    2016-11-01

    Full Text Available Abstract Background Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level. Methods A total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC. Incorporating demographic information as covariates with cumulative cases (365 days in a discrete Poisson model, we iteratively applied space–time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value <0.05 was identified as a dengue-epidemic area. Assuming an ongoing transmission might continuously spread for two consecutive weeks, we estimated the sensitivity and specificity for detecting outbreaks by comparing the scan-based classification (dengue-epidemic vs. dengue-free village with the true cumulative case numbers from the TCDC’s surveillance statistics. Results Among the 1648 villages in Tainan and Kaohsiung, the overall sensitivity for detecting outbreaks increases as case numbers grow in a total of 92 weekly simulations. The specificity for detecting outbreaks behaves inversely, compared to the sensitivity. On average, the mean sensitivity and specificity of 2-week hot spot detection were 0.615 and 0.891 respectively (p value <0.001 for the covariate adjustment model, as the maximum spatial and temporal windows were specified as 50% of the total population at risk and 28 days. Dengue-epidemic villages were visualized and explored in an interactive map. Conclusions We designed an online analytical tool for

  16. Physical security and cyber security issues and human error prevention for 3D printed objects: detecting the use of an incorrect printing material

    Science.gov (United States)

    Straub, Jeremy

    2017-06-01

    A wide variety of characteristics of 3D printed objects have been linked to impaired structural integrity and use-efficacy. The printing material can also have a significant impact on the quality, utility and safety characteristics of a 3D printed object. Material issues can be created by vendor issues, physical security issues and human error. This paper presents and evaluates a system that can be used to detect incorrect material use in a 3D printer, using visible light imaging. Specifically, it assesses the ability to ascertain the difference between materials of different color and different types of material with similar coloration.

  17. Early fault detection and on-line diagnosis in real-time environments

    Directory of Open Access Journals (Sweden)

    Andreas Bye

    1993-01-01

    Full Text Available This paper describes an approach to fault detection and diagnosis involving the simultaneous employment of quantitative and qualitative reasoning techniques. We show that early identification of process anomalies by means of a separate fault detection module paves the way for a fast and accuratc follow-up diagnosis. The diagnosis task is dramatically simplified because the diagnostic inferences can be performed at the soonest possible time: when the detection module first spots deviations between its calculated reference points and the corresponding measurements from the process.

  18. On-line early fault detection and diagnosis of municipal solid waste incinerators

    International Nuclear Information System (INIS)

    Zhao Jinsong; Huang Jianchao; Sun Wei

    2008-01-01

    A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows that automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI

  19. On-Line Detection of Distributed Attacks from Space-Time Network Flow Patterns

    National Research Council Canada - National Science Library

    Baras, J. S; Cardenas, A. A; Ramezani, V

    2003-01-01

    .... The directionality of the change in a network flow is assumed to have an objective or target. The particular problem of detecting distributed denial of service attacks from distributed observations is presented as a working framework...

  20. A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults

    OpenAIRE

    Rui Sun; Qi Cheng; Guanyu Wang; Washington Yotto Ochieng

    2017-01-01

    The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in ...

  1. Operator errors

    International Nuclear Information System (INIS)

    Knuefer; Lindauer

    1980-01-01

    Besides that at spectacular events a combination of component failure and human error is often found. Especially the Rasmussen-Report and the German Risk Assessment Study show for pressurised water reactors that human error must not be underestimated. Although operator errors as a form of human error can never be eliminated entirely, they can be minimized and their effects kept within acceptable limits if a thorough training of personnel is combined with an adequate design of the plant against accidents. Contrary to the investigation of engineering errors, the investigation of human errors has so far been carried out with relatively small budgets. Intensified investigations in this field appear to be a worthwhile effort. (orig.)

  2. SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Jani, S; Low, D; Lamb, J [UCLA, Los Angeles, CA (United States)

    2015-06-15

    Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and

  3. SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

    International Nuclear Information System (INIS)

    Jani, S; Low, D; Lamb, J

    2015-01-01

    Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and

  4. On-Line Detection of Coil Inter-Turn Short Circuit Faults in Dual-Redundancy Permanent Magnet Synchronous Motors

    Directory of Open Access Journals (Sweden)

    Yiguang Chen

    2018-03-01

    Full Text Available In the aerospace and military fields, with high reliability requirements, the dual-redundancy permanent magnet synchronous motor (DRPMSM with weak thermal coupling and no electromagnetic coupling is needed. A common fault in the DRPMSM is the inter-turn short circuit fault (ISCF. However, research on how to diagnose ISCF and the set of faulty windings in the DRPMSM is lacking. In this paper, the structure of the DRPMSM is analyzed and mathematical models of the motor under normal and faulty conditions are established. Then an on-line ISCF detection scheme, which depends on the running modes of the DRPMSM and the average values for the difference of the d-axis voltages between two sets of windings in the latest 20 sampling periods, is proposed. The main contributions of this paper are to analyze the calculation for the inductance of each part of the stator windings and propose the on-line diagnosis method of the ISCF under various operating conditions. The simulation and experimental results show that the proposed method can quickly and effectively diagnose ISCF and determine the set of faulty windings of the DRPMSM.

  5. Laser-induced breakdown spectroscopy in gases using ungated detection in combination with polarization filtering and online background correction

    International Nuclear Information System (INIS)

    Kiefer, J; Tröger, J W; Seeger, T; Leipertz, A; Li, B; Li, Z S; Aldén, M

    2010-01-01

    Quantitative and fast analysis of gas mixtures is an important task in the field of chemical, security and environmental analysis. In this paper we present a diagnostic approach based on laser-induced breakdown spectroscopy (LIBS). A polarization filter in the signal collection system enables sufficient suppression of elastically scattered light which otherwise reduces the dynamic range of the measurement. Running the detector with a doubled repetition rate as compared to the laser online background correction is obtained. Quantitative measurements of molecular air components in synthetic, ambient and expiration air are performed and demonstrate the potential of the method. The detection limits for elemental oxygen and hydrogen are in the order of 15 ppm and 10 ppm, respectively

  6. Errors detection in viscosity temperature measurements. Pt. B. Results, usefullness. Fehlersuche bei Viskositaet-Temperatur-Messungen. T. B. Resultate, Nuetzlichkeit

    Energy Technology Data Exchange (ETDEWEB)

    Schwen, R. (BASF, Farbenlaboratorium, Ludwigshafen am Rhein (Germany)); Puhl, H. (BASF, Ammoniaklaboratorium, Ludwigshafen am Rhein (Germany))

    1992-06-01

    The temperature dependence of the viscosity spreads often over a large range. It can be measured with less then one per cent error with usual effort, but the result cannot yet be controlled to the same accuracy: Graphic methods are far too incorrect and the numerous approximate equations given in literature do not adequately represent the true shape of the curves of all types of substances at the whole range of interesting temperatures. The different slopes and curvatures of the temperature dependence of the dynamic and kinematic viscosities can now be represented by means of one-term or multi-term exponential-functions with a maximum of eight coefficients. The Antoine equation is included in this investigation and the Ubbelohde-Walter-equation for comparison only. Tests on more than 400 data sets show, that there is no single equation to cope with all existing slopes. The numerical values of the coefficients are determined by the Marquardt statistical search method; the starting values are obtained by fixed rules. Using a non-linear regression of exponential sums, the method exactly describes the viscosity-temperature-behavior of normal liquids and real gases as well as the supercritical region over any desired range starting with four measured values and being complete with nine measured values or more; it allows tabellation, interpolation and, with caution, extrapolation. In the first part published, the problem and the mathematic procedure were discussed. The following publication presents the results and considers the applicability. (orig.).

  7. Determination of vitamin K homologues by high-performance liquid chromatography with on-line photoreactor and peroxyoxalate chemiluminescence detection

    International Nuclear Information System (INIS)

    Ahmed, Sameh; Kishikawa, Naoya; Nakashima, Kenichiro; Kuroda, Naotaka

    2007-01-01

    A sensitive and highly selective high-performance liquid chromatography (HPLC) method was developed for the determination of vitamin K homologues including phylloquinone (PK), menaquinone-4 (MK-4) and menaquinone-7 (MK-7) in human plasma using post-column peroxyoxalate chemiluminescence (PO-CL) detection following on-line ultraviolet (UV) irradiation. The method was based on ultraviolet irradiation (254 nm, 15 W) of vitamin K to produce hydrogen peroxide and a fluorescent product at the same time, which can be determined with PO-CL detection. The separation of vitamin K by HPLC was accomplished isocratically on an ODS column within 35 min. The method involves the use of 2-methyl-3-pentadecyl-1,4-naphthoquinone as an internal standard. The detection limits (signal-to-noise ratio = 3) were 32, 38 and 85 fmol for PK, MK-4 and MK-7, respectively. The recoveries of PK, MK-4 and MK-7 were greater than 82% and the inter- and intra-assay R.S.D. values were 1.9-5.4%. The sensitivity and selectivity of this method were sufficient for clinical and nutritional applications

  8. Detection of trace fluoride in serum and urine by online membrane-based distillation coupled with ion chromatography.

    Science.gov (United States)

    Lou, Chaoyan; Guo, Dandan; Wang, Nani; Wu, Shuchao; Zhang, Peimin; Zhu, Yan

    2017-06-02

    An online membrane-based distillation (MBD) coupled with ion chromatography (IC) method was proposed for automatic detection of trace fluoride (F - ) in serum and urine samples. The system consisted of a sample vessel, a lab-made membrane module and an ion chromatograph. Hydrophobic polytetrafluoroethylene (PTFE) hollow fiber membrane was used in MBD which was directly performed in serum and urine samples to eliminate the matrix interferences and enrich fluoride, while enabling automation. The determination of fluoride in biological samples was carried out by IC with suppressed conductometric detection. The proposed method feasibly determined trace fluoride in serum and urine matrices with the optimized parameters, such as acid concentration, distillation temperature, and distillation time, etc. Fluoride exhibited satisfactory linearity in the range of 0.01-5.0mg/L with a correlation coefficient of 0.9992. The limit of detection (LOD, S/N=3) and limit of quantification (LOQ, S/N=10) were 0.78μg/L and 2.61μg/L, respectively. The relative standard deviations of peak area and peak height were all less than 5.15%. The developed method was validated for the determination of fluoride in serum and urine with good spiked recoveries ranging between 97.1-101.9%. This method also can be proposed as a suitable alternative for the analysis of fluoride in other complex biological samples. Copyright © 2017. Published by Elsevier B.V.

  9. On-line hyperfine structure and isotope shift measurements with diffuse light collection and photon burst detection

    International Nuclear Information System (INIS)

    Lassen, J.; Benck, E.C.; Schuessler, H.A.

    1997-01-01

    An experiment is presently being set up which combines collinear-fast-beam laser spectroscopy with photon burst spectroscopy. Selectivity is provided by the large kinetic isotope shifts together with the practically Doppler free linewidth of the fluorescence from the fast atom beam. The photon burst detection, based on photon correlations in the resonance fluorescence, increases the sensitivity, so that on-line optical isotope shift and hyperfine structure measurements on low intensity radioactive beams become feasible. In order to improve photon burst detection the solid angle of detection and the observation time have to be optimized. To this end a diffuse reflecting cavity has been designed and built, which collects fluorescence over a 45 cm length of the beam and covers the full solid angle. The light collection efficiency of the cavity is calculated to be about 45%. The cavity is being tested with a 11 keV beam of krypton atoms, probing the near infrared transitions in our apparatus at Texas A ampersand M University. copyright 1997 American Institute of Physics

  10. Online model-based fault detection for grid connected PV systems monitoring

    KAUST Repository

    Harrou, Fouzi

    2017-12-14

    This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

  11. On-Line Detection and Segmentation of Sports Motions Using a Wearable Sensor

    Directory of Open Access Journals (Sweden)

    Woosuk Kim

    2018-03-01

    Full Text Available In sports motion analysis, observation is a prerequisite for understanding the quality of motions. This paper introduces a novel approach to detect and segment sports motions using a wearable sensor for supporting systematic observation. The main goal is, for convenient analysis, to automatically provide motion data, which are temporally classified according to the phase definition. For explicit segmentation, a motion model is defined as a sequence of sub-motions with boundary states. A sequence classifier based on deep neural networks is designed to detect sports motions from continuous sensor inputs. The evaluation on two types of motions (soccer kicking and two-handed ball throwing verifies that the proposed method is successful for the accurate detection and segmentation of sports motions. By developing a sports motion analysis system using the motion model and the sequence classifier, we show that the proposed method is useful for observation of sports motions by automatically providing relevant motion data for analysis.

  12. Online model-based fault detection for grid connected PV systems monitoring

    KAUST Repository

    Harrou, Fouzi; Sun, Ying; Saidi, Ahmed

    2017-01-01

    This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

  13. On-Line Detection and Segmentation of Sports Motions Using a Wearable Sensor.

    Science.gov (United States)

    Kim, Woosuk; Kim, Myunggyu

    2018-03-19

    In sports motion analysis, observation is a prerequisite for understanding the quality of motions. This paper introduces a novel approach to detect and segment sports motions using a wearable sensor for supporting systematic observation. The main goal is, for convenient analysis, to automatically provide motion data, which are temporally classified according to the phase definition. For explicit segmentation, a motion model is defined as a sequence of sub-motions with boundary states. A sequence classifier based on deep neural networks is designed to detect sports motions from continuous sensor inputs. The evaluation on two types of motions (soccer kicking and two-handed ball throwing) verifies that the proposed method is successful for the accurate detection and segmentation of sports motions. By developing a sports motion analysis system using the motion model and the sequence classifier, we show that the proposed method is useful for observation of sports motions by automatically providing relevant motion data for analysis.

  14. A scalable architecture for online anomaly detection of WLCG batch jobs

    Science.gov (United States)

    Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.

    2016-10-01

    For data centres it is increasingly important to monitor the network usage, and learn from network usage patterns. Especially configuration issues or misbehaving batch jobs preventing a smooth operation need to be detected as early as possible. At the GridKa data and computing centre we therefore operate a tool BPNetMon for monitoring traffic data and characteristics of WLCG batch jobs and pilots locally on different worker nodes. On the one hand local information itself are not sufficient to detect anomalies for several reasons, e.g. the underlying job distribution on a single worker node might change or there might be a local misconfiguration. On the other hand a centralised anomaly detection approach does not scale regarding network communication as well as computational costs. We therefore propose a scalable architecture based on concepts of a super-peer network.

  15. Online Phase Detection Using Wearable Sensors for Walking with a Robotic Prosthesis

    Directory of Open Access Journals (Sweden)

    Maja Goršič

    2014-02-01

    Full Text Available This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%. A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training.

  16. Investigation on iterative multiuser detection physical layer network coding in two-way relay free-space optical links with turbulences and pointing errors.

    Science.gov (United States)

    Abu-Almaalie, Zina; Ghassemlooy, Zabih; Bhatnagar, Manav R; Le-Minh, Hoa; Aslam, Nauman; Liaw, Shien-Kuei; Lee, It Ee

    2016-11-20

    Physical layer network coding (PNC) improves the throughput in wireless networks by enabling two nodes to exchange information using a minimum number of time slots. The PNC technique is proposed for two-way relay channel free space optical (TWR-FSO) communications with the aim of maximizing the utilization of network resources. The multipair TWR-FSO is considered in this paper, where a single antenna on each pair seeks to communicate via a common receiver aperture at the relay. Therefore, chip interleaving is adopted as a technique to separate the different transmitted signals at the relay node to perform PNC mapping. Accordingly, this scheme relies on the iterative multiuser technique for detection of users at the receiver. The bit error rate (BER) performance of the proposed system is examined under the combined influences of atmospheric loss, turbulence-induced channel fading, and pointing errors (PEs). By adopting the joint PNC mapping with interleaving and multiuser detection techniques, the BER results show that the proposed scheme can achieve a significant performance improvement against the degrading effects of turbulences and PEs. It is also demonstrated that a larger number of simultaneous users can be supported with this new scheme in establishing a communication link between multiple pairs of nodes in two time slots, thereby improving the channel capacity.

  17. Double peak-induced distance error in short-time-Fourier-transform-Brillouin optical time domain reflectometers event detection and the recovery method.

    Science.gov (United States)

    Yu, Yifei; Luo, Linqing; Li, Bo; Guo, Linfeng; Yan, Jize; Soga, Kenichi

    2015-10-01

    The measured distance error caused by double peaks in the BOTDRs (Brillouin optical time domain reflectometers) system is a kind of Brillouin scattering spectrum (BSS) deformation, discussed and simulated for the first time in the paper, to the best of the authors' knowledge. Double peak, as a kind of Brillouin spectrum deformation, is important in the enhancement of spatial resolution, measurement accuracy, and crack detection. Due to the variances of the peak powers of the BSS along the fiber, the measured starting point of a step-shape frequency transition region is shifted and results in distance errors. Zero-padded short-time-Fourier-transform (STFT) can restore the transition-induced double peaks in the asymmetric and deformed BSS, thus offering more accurate and quicker measurements than the conventional Lorentz-fitting method. The recovering method based on the double-peak detection and corresponding BSS deformation can be applied to calculate the real starting point, which can improve the distance accuracy of the STFT-based BOTDR system.

  18. Calibration curves for on-line leakage detection using radiotracer injection method

    Directory of Open Access Journals (Sweden)

    Ayoub Khatooni

    2017-11-01

    Full Text Available One of the most important requirements for industrial pipelines is the leakage detection. In this paper, detection of leak and determination of its amount using radioactive tracer injection method has been simulated by Monte Carlo MCNP code. The detector array included two NaI (Tl detectors which were located before and after the considered position, measure emitted gamma from radioactive tracer. After calibration of radiation detectors, the amount of leakage can be calculated based on the count difference of detectors. Also, the effect of material and thickness and diameter of pipe, crystal dimension, types of fluid, activity of tracer and its type (24Na, 82Br, 131I, 99mTc, 113mIn as well as have been investigated on the detectable amount of leakage. According to the results, for example, leakage more than 0.007% in volume of the inlet fluid for iron pipe with outer diameter 4 inch and thickness of 0.5 cm, Petrol as fluid inside pipe, 3 3 inch detector and 24Na with activity of 100 mCi can be detected by this presented method.

  19. On-line safeguards design: an application of estimation/detection

    International Nuclear Information System (INIS)

    Candy, J.V.; Dunn, D.R.; Rozsa, R.B.

    1979-01-01

    The applicability of madern signal processing techniques to the safeguards problem for a plutonium nitrate storage tank and concentrator is addressed. The techniques involve mathematical modeling, optimal estimation of process variables, and the detection of abnormal changes in these variables due to adversary diversion. The performance of these techniques is preesented for various diversion scenarios

  20. Language and music: differential hemispheric dominance in detecting unexpected errors in the lyrics and melody of memorized songs.

    Science.gov (United States)

    Yasui, Takuya; Kaga, Kimitaka; Sakai, Kuniyoshi L

    2009-02-01

    Using magnetoencephalography (MEG), we report here the hemispheric dominance of the auditory cortex that is selectively modulated by unexpected errors in the lyrics and melody of songs (lyrics and melody deviants), thereby elucidating under which conditions the lateralization of auditory processing changes. In experiment 1 using familiar songs, we found that the dipole strength of responses to the lyrics deviants was left-dominant at 140 ms (M140), whereas that of responses to the melody deviants was right-dominant at 130 ms (M130). In experiment 2 using familiar songs with a constant syllable or pitch, the dipole strength of frequency mismatch negativity elicited by oddballs was left-dominant. There were significant main effects of experiment (1 and 2) for the peak latencies and for the coordinates of the dipoles, indicating that the M140 and M130 were not the frequency mismatch negativity. In experiment 3 using newly memorized songs, the right-dominant M130 was observed only when the presented note was unexpected one, independent of perceiving unnatural pitch transitions (i.e., perceptual saliency) and of selective attention to the melody of songs. The consistent right-dominance of the M130 between experiments 1 and 3 suggests that the M130 in experiment 1 is due to unexpected notes deviating from well-memorized songs. On the other hand, the left-dominant M140 was elicited by lyrics deviants, suggesting the influence of top-down linguistic information and the memory of the familiar songs. We thus conclude that the left- lateralized M140 and right-lateralized M130 reflect the expectation based on top-down information of language and music, respectively.

  1. Optimization of Plastic Scintillator Thicknesses for Online Beta Detection in Mixed Fields

    Energy Technology Data Exchange (ETDEWEB)

    Pourtangestani, K.; Machrafi, R. [University of Ontario Institute of Technology, Oshawa, ON (Canada)

    2013-07-15

    For efficient beta detection in a mixed beta-gamma field, Monte Carlo simulation models have been developed to optimize the thickness of a plastic scintillator used in whole body monitor. The simulation has been performed using MCNP/X code and different thicknesses of plastic scintillators ranging from 150 to 600 {mu}m have been used. The relationship between the thickness of the scintillator and the efficiency of the detector has been analysed. For 150 {mu}m thickness, an experimental investigation has been conducted with different beta sources at different positions on the scintillator and the counting efficiency of the unit has been measured. Evaluated data along with experimental ones have been discussed. A thickness of 300 {mu}m to 500 {mu}m has been found to be an optimum thickness for better beta detection efficiency in the presence of low energy gamma ray. (author)

  2. Optimization of plastic scintillator thicknesses for online beta/gamma detection

    Directory of Open Access Journals (Sweden)

    Pourtangestani K.

    2012-04-01

    Full Text Available For efficient beta detection in a mixed beta gamma field, Monte Carlo simulation models have been built to optimize the thickness of a plastic scintillator, used in a whole body monitor. The simulation has been performed using the MCNP/X code for different thicknesses of plastic scintillator from 150 μm to 600 μm. The relationship between the thickness of the scintillator and the efficiency of the detector has been analyzed. For 150 μm thickness, an experimental investigation has been conducted with different beta sources at different positions on the scintillator and the counting efficiency of the unit has been measured. Evaluated data along with experimental ones have been discussed. A thickness of 300 μm to 500 μm has been found to be the optimum thickness for high efficiency beta detection in the presence of low energy gamma-rays.

  3. On-line leak detection method for OWL-1 loop by ARX modeling using dewpoint signals

    International Nuclear Information System (INIS)

    Oguma, Ritsuo; Hayashi, Koji; Kitajima, Toshio.

    1981-01-01

    Model identification technique based on ARX (autoregressive model with exogenous variable) process was applied to dewpoint data recorded at OWL-1 (Oarai Water Loop No. 1) loop cubicle in JMTR (Japan Materials Testing Reactor) and the dynamical interrelationship between the supply and exhaust dewpoints in the ventilation system of the cubicle was empirically determined. It was shown that the information so derived on the dewpoint dynamics can assist to enhance the sensitivity of leak detection, if it was incorporated into a leak monitoring system for the OWL-1 loop. A simple digital filter incorporating the dewpoint dynamics was designed in an attempt to develop an efficient leak monitor for the OWL-1 loop. This filter was applied to the dewpoint data recordings during an abnormal leak that had occurred at the OWL-1 loop in the 43 rd cycle of JMTR operation, which demonstrated the effectiveness of the present method for leak detection at its early stage. (author)

  4. Detection of microbial contaminations in drinking water using ATP measurements – evaluating potential for online monitoring

    DEFF Research Database (Denmark)

    Vang, Óluva Karin; Corfitzen, Charlotte B.; Albrechtsen, Hans-Jørgen

    2011-01-01

    There is an increasing call for fast and reliable methods for continuous monitoring of microbial drinking water quality in order to protect public health. The potential for Adenosine triphosphate (ATP) measurements as a real-time analysis for continuous monitoring of microbial drinking water...... quality was investigated through simulation of two contamination scenarios, i.e. drinking water contaminated with waste water and surface water at various concentrations. With ATP measurements it was possible to detect waste water diluted 1000-10,000 times in drinking water depending on sensitivity...... of reagent kit. Surface water diluted 100-1000 times was detected in drinking water with ATP measurements. ATP has the potential as an early warning tool, especially in the period when the contamination concentration is high. 2011 © American Water Works Association AWWA WQTC Conference Proceedings All Rights...

  5. Combating Fraud in Online Social Networks: Detecting Stealthy Facebook Like Farms

    OpenAIRE

    Ikram, Muhammad; Onwuzurike, Lucky; Farooqi, Shehroze; De Cristofaro, Emiliano; Friedman, Arik; Jourjon, Guillaume; Kaafar, Mohammad Ali; Shafiq, M. Zubair

    2015-01-01

    As businesses increasingly rely on social networking sites to engage with their customers, it is crucial to understand and counter reputation manipulation activities, including fraudulently boosting the number of Facebook page likes using like farms. To this end, several fraud detection algorithms have been proposed and some deployed by Facebook that use graph co-clustering to distinguish between genuine likes and those generated by farm-controlled profiles. However, as we show in this paper,...

  6. Fault Detection Algorithm based on Null-Space Analysis for On-Line Structural Health Monitoring

    OpenAIRE

    Yan, Ai-Min; Golinval, Jean-Claude; Marin, Frédéric

    2005-01-01

    Early diagnosis of structural damages or machinery malfunctions allows to reduce the maintenance cost of systems and to increase their reliability and safety. This paper addresses the damage detection problem by statistical analysis on output-only measurements of structures. The developed method is based on subspace analysis of the Hankel matrices constructed by vibration measurement data. The column active subspace of the Hankel matrix defined by the first principal components is orthonormal...

  7. Anomaly-based online intrusion detection system as a sensor for cyber security situational awareness system

    OpenAIRE

    Kokkonen, Tero

    2016-01-01

    Almost all the organisations and even individuals rely on complex structures of data networks and networked computer systems. That complex data ensemble, the cyber domain, provides great opportunities, but at the same time it offers many possible attack vectors that can be abused for cyber vandalism, cyber crime, cyber espionage or cyber terrorism. Those threats produce requirements for cyber security situational awareness and intrusion detection capability. This dissertation conc...

  8. Equipment Health Monitoring with Non-Parametric Statistics for Online Early Detection and Scoring of Degradation

    Science.gov (United States)

    2014-10-02

    defined by Eqs. (3)–(4) (Greenwell & Finch , 2004) (Kar & Mohanty, 2006). The p value provides the metric for novelty scoring. p = QKS(z) = 2 ∞∑ j=1 (−1...provides early detection of degradation and ability to score its significance in order to inform maintenance planning and consequently reduce disruption ...actionable information, sig- nals are typically processed from raw measurements into a reduced dimension novelty summary value that may be more easily

  9. VizieR Online Data Catalog: Bayesian method for detecting stellar flares (Pitkin+, 2014)

    Science.gov (United States)

    Pitkin, M.; Williams, D.; Fletcher, L.; Grant, S. D. T.

    2015-05-01

    We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of 'quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N. (1 data file).

  10. Online Vibration Monitoring of a Water Pump Machine to Detect Its Malfunction Components Based on Artificial Neural Network

    Science.gov (United States)

    Rahmawati, P.; Prajitno, P.

    2018-04-01

    Vibration monitoring is a measurement instrument used to identify, predict, and prevent failures in machine instruments[6]. This is very needed in the industrial applications, cause any problem with the equipment or plant translates into economical loss and they are mostly monitored component off-line[2]. In this research, a system has been developed to detect the malfunction of the components of Shimizu PS-128BT water pump machine, such as capacitor, bearing and impeller by online measurements. The malfunction components are detected by taking vibration data using a Micro-Electro-Mechanical System(MEMS)-based accelerometer that are acquired by using Raspberry Pi microcomputer and then the data are converted into the form of Relative Power Ratio(RPR). In this form the signal acquired from different components conditions have different patterns. The collected RPR used as the base of classification process for recognizing the damage components of the water pump that are conducted by Artificial Neural Network(ANN). Finally, the damage test result will be sent via text message using GSM module that are connected to Raspberry Pi microcomputer. The results, with several measurement readings, with each reading in 10 minutes duration for each different component conditions, all cases yield 100% of accuracies while in the case of defective capacitor yields 90% of accuracy.

  11. Using computer-extracted image features for modeling of error-making patterns in detection of mammographic masses among radiology residents.

    Science.gov (United States)

    Zhang, Jing; Lo, Joseph Y; Kuzmiak, Cherie M; Ghate, Sujata V; Yoon, Sora C; Mazurowski, Maciej A

    2014-09-01

    Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach to trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. The authors' algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different from 0.5 (perror

  12. Online Detection and Estimation of Grid Impedance Variation for Distributed Power Generation

    DEFF Research Database (Denmark)

    Jebali-Ben Ghorbal, Manel; Ghzaiel, Walid; Slama-Belkhodja, Ilhem

    2012-01-01

    A better knowledge of the grid impedance is essential in order to improve power quality and control of the Distributed Power Generation Systems (DPGS) and also for a safe connection or reconnection to the utility grid. An LCL-filter associated to a Voltage Source Inverter (VSI) is usually used...... to disconnect the DPG systems of the network. This work presents a rapid and simple technique to detect the grid impedance variation and to determine the grid impedance before and after grid faults accurs. Implementation on FPGA control board, simulations and experimental results are presented to validate...

  13. The preliminary development and testing of a global trigger tool to detect error and patient harm in primary-care records.

    Science.gov (United States)

    de Wet, C; Bowie, P

    2009-04-01

    A multi-method strategy has been proposed to understand and improve the safety of primary care. The trigger tool is a relatively new method that has shown promise in American and secondary healthcare settings. It involves the focused review of a random sample of patient records using a series of "triggers" that alert reviewers to potential errors and previously undetected adverse events. To develop and test a global trigger tool to detect errors and adverse events in primary-care records. Trigger tool development was informed by previous research and content validated by expert opinion. The tool was applied by trained reviewers who worked in pairs to conduct focused audits of 100 randomly selected electronic patient records in each of five urban general practices in central Scotland. Review of 500 records revealed 2251 consultations and 730 triggers. An adverse event was found in 47 records (9.4%), indicating that harm occurred at a rate of one event per 48 consultations. Of these, 27 were judged to be preventable (42%). A further 17 records (3.4%) contained evidence of a potential adverse event. Harm severity was low to moderate for most patients (82.9%). Error and harm rates were higher in those aged > or =60 years, and most were medication-related (59%). The trigger tool was successful in identifying undetected patient harm in primary-care records and may be the most reliable method for achieving this. However, the feasibility of its routine application is open to question. The tool may have greater utility as a research rather than an audit technique. Further testing in larger, representative study samples is required.

  14. Value of dual biometry in the detection and investigation of error in the preoperative prediction of refractive status following cataract surgery.

    LENUS (Irish Health Repository)

    Charalampidou, Sofia

    2012-02-01

    PURPOSE: To report the value of dual biometry in the detection of biometry errors. METHODS: Study 1: retrospective study of 224 consecutive cataract operations. The intraocular lens power calculation was based on immersion biometry. Study 2: immersion biometry was compared with optical coherence biometry (OCB) in terms of axial length, anterior chamber depth, keratometry readings and the recommended lens power to achieve emmetropia. Study 3: prospective study of 61 consecutive cataract operations. Both immersion and OCB were performed, but lens power calculation was based on the latter. RESULTS: Study 1: 115 (86%), 101 (75.4%), 90 (67.2%) and 50 (37.3%) of postoperative spherical equivalents were within +\\/-1.5 dioptres (D), +\\/-1.25 D, +\\/-1 D and +\\/-0.5 D of the target, respectively. Study 2: excellent agreement between axial length readings, anterior chamber depth readings and keratometry readings by immersion biometry and OCB was observed (reflected in a mean bias of -0.065 mm, -0.048 mm and +0.1803 D, respectively, in association with OCB). Agreement between the lens power recommended by each technique to achieve emmetropia was poor (mean bias of +1.16 D in association with OCB), but improved following appropriate modification of lens constants in the Accutome A-scan software (mean bias with OCB = -0.4 D). Study 3: 37 (92.5%) and 23 (57.5%) of operated eyes achieved a postoperative refraction within +\\/-1 D and +\\/-0.5 D of target, respectively. CONCLUSION: Systematic errors in biometry can exist, in the presence of acceptable postoperative refractive results. Dual biometry allows each biometric parameter to be scrutinized in isolation, and identify sources of error that may otherwise go undetected.

  15. Development of an on-line high performance liquid chromatography detection system for human cytochrome P450 1A2 inhibitors in extracts of natural products

    NARCIS (Netherlands)

    Jeurissen, S.M.F.; Claassen, F.W.; Havlik, J.; Bouwmans, E.E.; Cnubben, N.H.P.; Sudhölter, E.J.R.; Rietjens, I.M.C.M.; Beek, T.A. van

    2007-01-01

    An on-line HPLC screening method for detection of inhibitors of human cytochrome P450 1A2 in extracts was developed. HPLC separation of extracts is connected to a continuous methoxyresorufin-O-demethylation (MROD) assay in which recombinant human P450 1A2 converts methoxyresorufin to its fluorescent

  16. The application of HPLC with on-line coupled UV/MS-biochemical detection for isolation of an acetylcholinesterase inhibitor from Narcissus 'Sir Winston Churchill'

    NARCIS (Netherlands)

    Ingkaninan, K.; Hazekamp, A.; de Best, C.M.; Irth, H.; Tjaden, U.R.; van der Heijden, R.; van der Greef, J.; Verpoorte, R.

    2000-01-01

    An HPLC with on-line coupled UV/MS-biochemical detection method for acetylcholinesterase (AChE) inhibitors in natural sources has been developed. The potential of this method is shown by the isolation of a new AChE inhibitor from the alcoholic extract of Narcissus 'Sir Winston Churchill'. Combining

  17. Flow injection on-line dilution for multi-element determination in human urine with detection by inductively coupled plasma mass spectrometry

    DEFF Research Database (Denmark)

    Wang, Jianhua; Hansen, Elo Harald; Gammelgaard, Bente

    2001-01-01

    A simple flow injection on-line dilution procedure with detection by inductively coupled plasma mass spectrometry (ICP-MS) was developed for the determination of copper, zinc, arsenic, lead, selenium, nickel and molybdenum in human urine. Matrix effects were minimized by employing a dilution factor...

  18. Data correlation in on-line solid-phase extraction-gas chromatography-atomic emission/mass spectrometric detection of unknown microcontaminants

    NARCIS (Netherlands)

    Hankemeier, Th.; Rozenbrand, J.; Abhadur, M.; Vreuls, J.J.; Brinkman, U.A.Th.

    1998-01-01

    A procedure is described for the (non-target) screening of hetero-atom-containing compounds in tap and waste water by correlating data obtained by gas chromatography (GC) using atomic emission (AED) and mass selective (MS) detection. Solid-phase extraction (SPE) was coupled on-line to both GC

  19. Selective on-line detection of boronic acids and derivatives in high-performance liquid chromatography eluates by post-column reaction with alizarin

    NARCIS (Netherlands)

    Duval, F.L.; Wardani, P.A.; Zuilhof, H.; Beek, van T.A.

    2015-01-01

    An on-line high-performance liquid chromatography (HPLC) method for the rapid and selective detection of boronic acids in complex mixtures was developed. After optimization experiments at an HPLC flow rate of 0.40 mL/min, the HPLC-separated analytes were mixed post-column with a solution of 75 µM

  20. On-line Speciation of Cr(III) and Cr(VI) by Flow Injection Analysis With Spectrophotometric Detection and Chemometrics

    DEFF Research Database (Denmark)

    Diacu, Elena; Andersen, Jens Enevold Thaulov

    2003-01-01

    A flow injection system has been developed, for on-line speciation. of Cr(III) and Cr(VI) by the Diphenylcarbazide (DPC) method with H2O2 oxidation followed by spectrophotometric detection at the 550 nm wavelength. The data thus obtained were subjected to a chemometric analysis (PLS), which showe...

  1. New oil condition monitoring system, Wearsens® enables continuous, online detection of critical operating conditions and wear damage

    Directory of Open Access Journals (Sweden)

    Manfred Mauntz

    2015-12-01

    Full Text Available A new oil sensor system is presented for the continuous, online measurement of the wear in turbines, industrial gears, generators, hydraulic systems and transformers. Detection of change is much earlier than existing technologies such as particle counting, vibration measurement or recording temperature. Thus targeted, corrective procedures and/or maintenance can be carried out before actual damage occurs. Efficient machine utilization, accurately timed preventive maintenance, increased service life and a reduction of downtime can all be achieved. The presented sensor system effectively controls the proper operation conditions of bearings and cogwheels in gears. The online diagnostics system measures components of the specific complex impedance of oils. For instance, metal abrasion due to wear debris, broken oil molecules, forming acids or oil soaps, result in an increase of the electrical conductivity, which directly correlates with the degree of contamination of the oil. For additivated lubricants, the stage of degradation of the additives can also be derived from changes in the dielectric constant. The determination of impurities or reduction in the quality of the oil and the quasi continuous evaluation of wear and chemical aging follow the holistic approach of a real-time monitoring of an alteration in the condition of the oil-machine system. Once the oil condition monitoring sensors are installed on the wind turbine, industrial gearbox and test stands, the measuring data can be displayed and evaluated elsewhere. The signals are transmitted to a web-based condition monitoring system via LAN, WLAN or serial interfaces of the sensor unit. Monitoring of the damage mechanisms during proper operation below the tolerance limits of the components enables specific preventive maintenance independent of rigid inspection intervals.

  2. Noisy visual feedback training impairs detection of self-generated movement error: implications for anosognosia for hemiplegia

    Directory of Open Access Journals (Sweden)

    Catherine ePreston

    2014-06-01

    Full Text Available Anosognosia for hemiplegia (AHP is characterised as a disorder in which patients are unaware of their contralateral motor deficit. Many current theories for unawareness in AHP are based on comparator model accounts of the normal experience of agency. According to such models, while small mismatches between predicted and actual feedback allow unconscious fine-tuning of normal actions, mismatches that surpass an inherent threshold reach conscious awareness and inform judgements of agency (whether a given movement is produced by the self or another agent. This theory depends on a threshold for consciousness that is greater than the intrinsic noise in the system to reduce the occurrence of incorrect rejections of self-generated movements and maintain a fluid experience of agency. Pathological increases to this threshold could account for reduced motor awareness following brain injury, including AHP. The current experiment tested this hypothesis in healthy controls by exposing them to training in which noise was applied the visual feedback of their normal reaches. Subsequent self/other attribution tasks without noise revealed a decrease in the ability to detect manipulated (other feedback compared to training without noise. This suggests a slackening of awareness thresholds in the comparator model that may help to explain clinical observations of decreased action awareness following stroke.

  3. Einstein's error

    International Nuclear Information System (INIS)

    Winterflood, A.H.

    1980-01-01

    In discussing Einstein's Special Relativity theory it is claimed that it violates the principle of relativity itself and that an anomalous sign in the mathematics is found in the factor which transforms one inertial observer's measurements into those of another inertial observer. The apparent source of this error is discussed. Having corrected the error a new theory, called Observational Kinematics, is introduced to replace Einstein's Special Relativity. (U.K.)

  4. Quantitative evaluation of patient-specific quality assurance using online dosimetry system

    Science.gov (United States)

    Jung, Jae-Yong; Shin, Young-Ju; Sohn, Seung-Chang; Min, Jung-Whan; Kim, Yon-Lae; Kim, Dong-Su; Choe, Bo-Young; Suh, Tae-Suk

    2018-01-01

    In this study, we investigated the clinical performance of an online dosimetry system (Mobius FX system, MFX) by 1) dosimetric plan verification using gamma passing rates and dose volume metrics and 2) error-detection capability evaluation by deliberately introduced machine error. Eighteen volumetric modulated arc therapy (VMAT) plans were studied. To evaluate the clinical performance of the MFX, we used gamma analysis and dose volume histogram (DVH) analysis. In addition, to evaluate the error-detection capability, we used gamma analysis and DVH analysis utilizing three types of deliberately introduced errors (Type 1: gantry angle-independent multi-leaf collimator (MLC) error, Type 2: gantry angle-dependent MLC error, and Type 3: gantry angle error). A dosimetric verification comparison of physical dosimetry system (Delt4PT) and online dosimetry system (MFX), gamma passing rates of the two dosimetry systems showed very good agreement with treatment planning system (TPS) calculation. For the average dose difference between the TPS calculation and the MFX measurement, most of the dose metrics showed good agreement within a tolerance of 3%. For the error-detection comparison of Delta4PT and MFX, the gamma passing rates of the two dosimetry systems did not meet the 90% acceptance criterion with the magnitude of error exceeding 2 mm and 1.5 ◦, respectively, for error plans of Types 1, 2, and 3. For delivery with all error types, the average dose difference of PTV due to error magnitude showed good agreement between calculated TPS and measured MFX within 1%. Overall, the results of the online dosimetry system showed very good agreement with those of the physical dosimetry system. Our results suggest that a log file-based online dosimetry system is a very suitable verification tool for accurate and efficient clinical routines for patient-specific quality assurance (QA).

  5. Zero-Forcing and Minimum Mean-Square Error Multiuser Detection in Generalized Multicarrier DS-CDMA Systems for Cognitive Radio

    Directory of Open Access Journals (Sweden)

    Lie-Liang Yang

    2008-01-01

    Full Text Available In wireless communications, multicarrier direct-sequence code-division multiple access (MC DS-CDMA constitutes one of the highly flexible multiple access schemes. MC DS-CDMA employs a high number of degrees-of-freedom, which are beneficial to design and reconfiguration for communications in dynamic communications environments, such as in the cognitive radios. In this contribution, we consider the multiuser detection (MUD in MC DS-CDMA, which motivates lowcomplexity, high flexibility, and robustness so that the MUD schemes are suitable for deployment in dynamic communications environments. Specifically, a range of low-complexity MUDs are derived based on the zero-forcing (ZF, minimum mean-square error (MMSE, and interference cancellation (IC principles. The bit-error rate (BER performance of the MC DS-CDMA aided by the proposed MUDs is investigated by simulation approaches. Our study shows that, in addition to the advantages provided by a general ZF, MMSE, or IC-assisted MUD, the proposed MUD schemes can be implemented using modular structures, where most modules are independent of each other. Due to the independent modular structure, in the proposed MUDs one module may be reconfigured without yielding impact on the others. Therefore, the MC DS-CDMA, in conjunction with the proposed MUDs, constitutes one of the promising multiple access schemes for communications in the dynamic communications environments such as in the cognitive radios.

  6. Zero-Forcing and Minimum Mean-Square Error Multiuser Detection in Generalized Multicarrier DS-CDMA Systems for Cognitive Radio

    Directory of Open Access Journals (Sweden)

    Wang Li-Chun

    2008-01-01

    Full Text Available Abstract In wireless communications, multicarrier direct-sequence code-division multiple access (MC DS-CDMA constitutes one of the highly flexible multiple access schemes. MC DS-CDMA employs a high number of degrees-of-freedom, which are beneficial to design and reconfiguration for communications in dynamic communications environments, such as in the cognitive radios. In this contribution, we consider the multiuser detection (MUD in MC DS-CDMA, which motivates lowcomplexity, high flexibility, and robustness so that the MUD schemes are suitable for deployment in dynamic communications environments. Specifically, a range of low-complexity MUDs are derived based on the zero-forcing (ZF, minimum mean-square error (MMSE, and interference cancellation (IC principles. The bit-error rate (BER performance of the MC DS-CDMA aided by the proposed MUDs is investigated by simulation approaches. Our study shows that, in addition to the advantages provided by a general ZF, MMSE, or IC-assisted MUD, the proposed MUD schemes can be implemented using modular structures, where most modules are independent of each other. Due to the independent modular structure, in the proposed MUDs one module may be reconfigured without yielding impact on the others. Therefore, the MC DS-CDMA, in conjunction with the proposed MUDs, constitutes one of the promising multiple access schemes for communications in the dynamic communications environments such as in the cognitive radios.

  7. Reliability, standard error, and minimum detectable change of clinical pressure pain threshold testing in people with and without acute neck pain.

    Science.gov (United States)

    Walton, David M; Macdermid, Joy C; Nielson, Warren; Teasell, Robert W; Chiasson, Marco; Brown, Lauren

    2011-09-01

    Clinical measurement. To evaluate the intrarater, interrater, and test-retest reliability of an accessible digital algometer, and to determine the minimum detectable change in normal healthy individuals and a clinical population with neck pain. Pressure pain threshold testing may be a valuable assessment and prognostic indicator for people with neck pain. To date, most of this research has been completed using algometers that are too resource intensive for routine clinical use. Novice raters (physiotherapy students or clinical physiotherapists) were trained to perform algometry testing over 2 clinically relevant sites: the angle of the upper trapezius and the belly of the tibialis anterior. A convenience sample of normal healthy individuals and a clinical sample of people with neck pain were tested by 2 different raters (all participants) and on 2 different days (healthy participants only). Intraclass correlation coefficient (ICC), standard error of measurement, and minimum detectable change were calculated. A total of 60 healthy volunteers and 40 people with neck pain were recruited. Intrarater reliability was almost perfect (ICC = 0.94-0.97), interrater reliability was substantial to near perfect (ICC = 0.79-0.90), and test-retest reliability was substantial (ICC = 0.76-0.79). Smaller change was detectable in the trapezius compared to the tibialis anterior. This study provides evidence that novice raters can perform digital algometry with adequate reliability for research and clinical use in people with and without neck pain.

  8. Automatic detection of potentially illegal online sales of elephant ivory via data mining

    Directory of Open Access Journals (Sweden)

    Julio Hernandez-Castro

    2015-07-01

    Full Text Available In this work, we developed an automated system to detect potentially illegal elephant ivory items for sale on eBay. Two law enforcement experts, with specific knowledge of elephant ivory identification, manually classified items on sale in the Antiques section of eBay UK over an 8 week period. This set the “Gold Standard” that we aim to emulate using data-mining. We achieved close to 93% accuracy with less data than the experts, as we relied entirely on metadata, but did not employ item descriptions or associated images, thus proving the potential and generality of our approach. The reported accuracy may be improved with the addition of text mining techniques for the analysis of the item description, and by applying image classification for the detection of Schreger lines, indicative of elephant ivory. However, any solution relying on images or text description could not be employed on other wildlife illegal markets where pictures can be missing or misleading and text absent (e.g., Instagram. In our setting, we gave human experts all available information while only using minimal information for our analysis. Despite this, we succeeded at achieving a very high accuracy. This work is an important first step in speeding up the laborious, tedious and expensive task of expert discovery of illegal trade over the internet. It will also allow for faster reporting to law enforcement and better accountability. We hope this will also contribute to reducing poaching, by making this illegal trade harder and riskier for those involved.

  9. Use of coliform bacteria for the detection of on-line leakage in drinking water

    International Nuclear Information System (INIS)

    Bibi, S.; Karim, H.M.A.; Mashiatullah, A.; Sajjad, I.

    1996-01-01

    In this method, rupture or leakage in under ground water pipes is detected simply by taking the water samples from the main supply lines of the houses and incubating them at 40 deg. C for sixteen hours, colonies (developed with yellow colour) are counted with colony counter. Thirteen samples (in triplicate) collected from different houses in the congested localities during repair work of the major supply line and all of them after test showed heavy rate of pollution. The experiment was repeated for the same locality and sampling sites after completion of repair work. This time the rate of pollution decreases very much showing drastically low growth of microorganisms except for two points. For two further investigation of the nearly leakages at these points, 13 samples (in triplicate) were again collected in serial wise number of houses. Two points of the leakage were identified where the growth rate of the microorganisms was abruptly high between two consecutive houses or opposite houses depending upon the supply of water pipe lines showing the leakage of houses. Two points of the leakage were identified where the growth rate of the microorganisms was abruptly high between two consecutive houses or opposite houses depending upon the supply of water pipe lines showing the leakage of he pipes. This method is useful and causes no health hazard to the population and gives best results where the water supply is on intermittent basis. The technique is specially useful in the remote areas of the country where research facilities are not available and the Pacqualab is a field instrument. So it is handy and rapid method for the detection of leakage in underground water supplies in the remote areas of the country. (author)

  10. The auditory-evoked N2 and P3 components in the stop-signal task: indices of inhibition, response-conflict or error-detection?

    Science.gov (United States)

    Dimoska, Aneta; Johnstone, Stuart J; Barry, Robert J

    2006-11-01

    The N2 and P3 components have been separately associated with response inhibition in the stop-signal task, and more recently, the N2 has been implicated in the detection of response-conflict. To isolate response inhibition activity from early sensory processing, the present study compared processing of the stop-signal with that of a task-irrelevant tone, which subjects were instructed to ignore. Stop-signals elicited a larger N2 on failed-stop trials and a larger P3 on successful-stop trials, relative to ignore-signal trials, likely reflecting activity related to failed and successful stopping, respectively. ERPs between fast and slow reaction-time (RT) groups were also examined as it was hypothesised that greater inhibitory activation to stop faster responses would manifest in the component reflecting this process. Successful-stop P3 showed the anticipated effect (globally larger amplitude in the fast than slow RT group), supporting its association with the stopping of an ongoing response. In contrast, N2 was larger in the slow than fast RT group, and in contrast to the predictions of the response-conflict hypothesis, successful-stop N2 and the response-locked error-negativity (Ne) differed in scalp distribution. These findings indicate that the successful-stop N2 may be better explained as a deliberate form of response control or selection, which the slow RT group employed as a means of increasing the likelihood of a successful-stop. Finally, a comparison of stimulus and response-locked ERPs revealed that the failed-stop N2 and P3 appeared to reflect error-related activity, best observed in the response-locked Ne and error-positivity (Pe). Together these findings indicate that the successful-stop N2 and P3 reflect functionally distinct aspects of response control that are dependent upon performance strategies, while failed-stop N2 and P3 reflect error-related activity.

  11. Clinical development of a failure detection-based online repositioning strategy for prostate IMRT--Experiments, simulation, and dosimetry study

    International Nuclear Information System (INIS)

    Liu Wu; Qian Jianguo; Hancock, Steven L.; Xing, Lei; Luxton, Gary

    2010-01-01

    Purpose: To implement and evaluate clinic-ready adaptive imaging protocols for online patient repositioning (motion tracking) during prostate IMRT using treatment beam imaging supplemented by minimal, as-needed use of on-board kV. Methods: The authors examine the two-step decision-making strategy: (1) Use cine-MV imaging and online-updated characterization of prostate motion to detect target motion that is potentially beyond a predefined threshold and (2) use paired MV-kV 3D localization to determine overthreshold displacement and, if needed, reposition the patient. Two levels of clinical implementation were evaluated: (1) Field-by-field based motion correction for present-day linacs and (2) instantaneous repositioning for new-generation linacs with capabilities of simultaneous MV-kV imaging and remote automatic couch control during treatment delivery. Experiments were performed on a Varian Trilogy linac in clinical mode using a 4D motion phantom programed with prostate motion trajectories taken from patient data. Dosimetric impact was examined using a 2D ion chamber array. Simulations were done for 536 trajectories from 17 patients. Results: Despite the loss of marker detection efficiency caused by the MLC leaves sometimes obscuring the field at the marker's projected position on the MV imager, the field-by-field correction halved (from 23% to 10%) the mean percentage of time that target displacement exceeded a 3 mm threshold, as compared to no intervention. This was achieved at minimal cost in additional imaging (average of one MV-kV pair per two to three treatment fractions) and with a very small number of repositionings (once every four to five fractions). Also with low kV usage (∼2/fraction), the instantaneous repositioning approach reduced overthreshold time by more than 75% (23% to 5%) even with severe MLC blockage as often encountered in current IMRT and could reduce the overthreshold time tenfold (to <2%) if the MLC blockage problem were relieved. The

  12. Impact of polymeric membrane breakage on drinking water quality and an online detection method of the breakage.

    Science.gov (United States)

    Wu, Qilong; Zhang, Zhenghua; Cao, Guodong; Zhang, Xihui

    2017-10-15

    online detection of particle count can be used to evaluate the bacterial risk. It was also suggested that the online detection of particle count after backwashing within 100 s would be a quick and precise method to identify any fiber breakage in time. These results are very important for the safety issue in the application of polymeric membrane to water treatment plants.

  13. Clinical development of a failure detection-based online repositioning strategy for prostate IMRT--experiments, simulation, and dosimetry study.

    Science.gov (United States)

    Liu, Wu; Qian, Jianguo; Hancock, Steven L; Xing, Lei; Luxton, Gary

    2010-10-01

    To implement and evaluate clinic-ready adaptive imaging protocols for online patient repositioning (motion tracking) during prostate IMRT using treatment beam imaging supplemented by minimal, as-needed use of on-board kV. The authors examine the two-step decision-making strategy: (1) Use cine-MV imaging and online-updated characterization of prostate motion to detect target motion that is potentially beyond a predefined threshold and (2) use paired MV-kV 3D localization to determine overthreshold displacement and, if needed, reposition the patient. Two levels of clinical implementation were evaluated: (1) Field-by-field based motion correction for present-day linacs and (2) instantaneous repositioning for new-generation linacs with capabilities of simultaneous MV-kV imaging and remote automatic couch control during treatment delivery. Experiments were performed on a Varian Trilogy linac in clinical mode using a 4D motion phantom programed with prostate motion trajectories taken from patient data. Dosimetric impact was examined using a 2D ion chamber array. Simulations were done for 536 trajectories from 17 patients. Despite the loss of marker detection efficiency caused by the MLC leaves sometimes obscuring the field at the marker's projected position on the MV imager, the field-by-field correction halved (from 23% to 10%) the mean percentage of time that target displacement exceeded a 3 mm threshold, as compared to no intervention. This was achieved at minimal cost in additional imaging (average of one MV-kV pair per two to three treatment fractions) and with a very small number of repositionings (once every four to five fractions). Also with low kV usage (approximation 2/fraction), the instantaneous repositioning approach reduced overthreshold time by more than 75% (23% to 5%) even with severe MLC blockage as often encountered in current IMRT and could reduce the overthreshold time tenfold (to < 2%) if the MLC blockage problem were relieved. The information

  14. Clinical development of a failure detection-based online repositioning strategy for prostate IMRT--Experiments, simulation, and dosimetry study

    Energy Technology Data Exchange (ETDEWEB)

    Liu Wu; Qian Jianguo; Hancock, Steven L.; Xing, Lei; Luxton, Gary [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305-5847 (United States) and Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, Connecticut 06510 (United States); Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305-5847 (United States)

    2010-10-15

    Purpose: To implement and evaluate clinic-ready adaptive imaging protocols for online patient repositioning (motion tracking) during prostate IMRT using treatment beam imaging supplemented by minimal, as-needed use of on-board kV. Methods: The authors examine the two-step decision-making strategy: (1) Use cine-MV imaging and online-updated characterization of prostate motion to detect target motion that is potentially beyond a predefined threshold and (2) use paired MV-kV 3D localization to determine overthreshold displacement and, if needed, reposition the patient. Two levels of clinical implementation were evaluated: (1) Field-by-field based motion correction for present-day linacs and (2) instantaneous repositioning for new-generation linacs with capabilities of simultaneous MV-kV imaging and remote automatic couch control during treatment delivery. Experiments were performed on a Varian Trilogy linac in clinical mode using a 4D motion phantom programed with prostate motion trajectories taken from patient data. Dosimetric impact was examined using a 2D ion chamber array. Simulations were done for 536 trajectories from 17 patients. Results: Despite the loss of marker detection efficiency caused by the MLC leaves sometimes obscuring the field at the marker's projected position on the MV imager, the field-by-field correction halved (from 23% to 10%) the mean percentage of time that target displacement exceeded a 3 mm threshold, as compared to no intervention. This was achieved at minimal cost in additional imaging (average of one MV-kV pair per two to three treatment fractions) and with a very small number of repositionings (once every four to five fractions). Also with low kV usage ({approx}2/fraction), the instantaneous repositioning approach reduced overthreshold time by more than 75% (23% to 5%) even with severe MLC blockage as often encountered in current IMRT and could reduce the overthreshold time tenfold (to <2%) if the MLC blockage problem were

  15. Determining Type I and Type II Errors when Applying Information Theoretic Change Detection Metrics for Data Association and Space Situational Awareness

    Science.gov (United States)

    Wilkins, M.; Moyer, E. J.; Hussein, Islam I.; Schumacher, P. W., Jr.

    Correlating new detections back to a large catalog of resident space objects (RSOs) requires solving one of three types of data association problems: observation-to-track, track-to-track, or observation-to-observation. The authors previous work has explored the use of various information divergence metrics for solving these problems: Kullback-Leibler (KL) divergence, mutual information, and Bhattacharrya distance. In addition to approaching the data association problem strictly from the metric tracking aspect, we have explored fusing metric and photometric data using Bayesian probabilistic reasoning for RSO identification to aid in our ability to correlate data to specific RS Os. In this work, we will focus our attention on the KL Divergence, which is a measure of the information gained when new evidence causes the observer to revise their beliefs. We can apply the Principle of Minimum Discrimination Information such that new data produces as small an information gain as possible and this information change is bounded by ɛ. Choosing an appropriate value for ɛ for both convergence and change detection is a function of your risk tolerance. Small ɛ for change detection increases alarm rates while larger ɛ for convergence means that new evidence need not be identical in information content. We need to understand what this change detection metric implies for Type I α and Type II β errors when we are forced to make a decision on whether new evidence represents a true change in characterization of an object or is merely within the bounds of our measurement uncertainty. This is unclear for the case of fusing multiple kinds and qualities of characterization evidence that may exist in different metric spaces or are even semantic statements. To this end, we explore the use of Sequential Probability Ratio Testing where we suppose that we may need to collect additional evidence before accepting or rejecting the null hypothesis that a change has occurred. In this work, we

  16. The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation

    Science.gov (United States)

    Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.

    2017-12-01

    In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long

  17. Error-related brain activity and error awareness in an error classification paradigm.

    Science.gov (United States)

    Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

    2016-10-01

    Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Online surveillance of media health event reporting in Nepal: digital disease detection from a One Health perspective.

    Science.gov (United States)

    Schwind, Jessica S; Norman, Stephanie A; Karmacharya, Dibesh; Wolking, David J; Dixit, Sameer M; Rajbhandari, Rajesh M; Mekaru, Sumiko R; Brownstein, John S

    2017-09-21

    Traditional media and the internet are crucial sources of health information. Media can significantly shape public opinion, knowledge and understanding of emerging and endemic health threats. As digital communication rapidly progresses, local access and dissemination of health information contribute significantly to global disease detection and reporting. Health event reports in Nepal (October 2013-December 2014) were used to characterize Nepal's media environment from a One Health perspective using HealthMap - a global online disease surveillance and mapping tool. Event variables (location, media source type, disease or risk factor of interest, and affected species) were extracted from HealthMap. A total of 179 health reports were captured from various sources including newspapers, inter-government agency bulletins, individual reports, and trade websites, yielding 108 (60%) unique articles. Human health events were reported most often (n = 85; 79%), followed by animal health events (n = 23; 21%), with no reports focused solely on environmental health. By expanding event coverage across all of the health sectors, media in developing countries could play a crucial role in national risk communication efforts and could enhance early warning systems for disasters and disease outbreaks.

  19. IVO, a device for In situ Volatilization and On-line detection of products from heavy ion reactions

    CERN Document Server

    Duellmann, C E; Eichler, R; Gäggeler, H W; Jost, D T; Piguet, D; Türler, A

    2002-01-01

    A new gaschromatographic separation system to rapidly isolate heavy ion reaction products in the form of highly volatile species is described. Reaction products recoiling from the target are stopped in a gas volume and converted in situ to volatile species, which are swept by the carrier gas to a chromatography column. Species that are volatile under the given conditions pass through the column. In a cluster chamber, which is directly attached to the exit of the column, the isolated volatile species are chemically adsorbed to the surface of aerosol particles and transported to an on-line detection system. The whole set-up was tested using short-lived osmium (Os) and mercury (Hg) nuclides produced in heavy ion reactions to model future chemical studies with hassium (Hs, Z=108) and element 112. By varying the temperature of the isothermal section of the chromatography column between room temperature and -80 deg. C, yield measurements of given species can be conducted, yielding information about the volatility o...

  20. Size distribution of alkyl amines in continental particulate matter and their online detection in the gas and particle phase

    Directory of Open Access Journals (Sweden)

    T. C. VandenBoer

    2011-05-01

    Full Text Available An ion chromatographic method is described for the quantification of the simple alkyl amines: methylamine (MA, dimethylamine (DMA, trimethylamine (TMA, ethylamine (EA, diethylamine (DEA and triethylamine (TEA, in the ambient atmosphere. Limits of detection (3σ are in the tens of pmol range for all of these amines, and good resolution is achieved for all compounds except for TMA and DEA. The technique was applied to the analysis of time-integrated samples collected using a micro-orifice uniform deposition impactor (MOUDI with ten stages for size resolution of particles with aerodynamic diameters between 56 nm and 18 μm. In eight samples from urban and rural continental airmasses, the mass loading of amines consistently maximized on the stage corresponding to particles with aerodynamic diameters between 320 and 560 nm. The molar ratio of amines to ammonium (R3NH+/NH4+ in fine aerosol ranged between 0.005 and 0.2, and maximized for the smallest particle sizes. The size-dependence of the R3NH+/NH4+ ratio indicates differences in the relative importance of the processes leading to the incorporation of amines and ammonia into secondary particles. The technique was also used to make simultaneous hourly online measurements of amines in the gas phase and in fine particulate matter using an Ambient Ion Monitor Ion Chromatograph (AIM-IC. During a ten day campaign in downtown Toronto, DMA, TMA + DEA, and TEA were observed to range from below detection limit to 2.7 ppt in the gas phase. In the particle phase, MAH+ and TMAH+ + DEAH+ were observed to range from below detection limit up to 15 ng m−3. The presence of detectable levels of amines in the particle phase corresponded to periods with higher relative humidity and higher mass loadings of nitrate. While the hourly measurements made using the AIM-IC provide data that can

  1. Elastic scattering spectroscopy for detection of cancer risk in Barrett's esophagus: experimental and clinical validation of error removal by orthogonal subtraction for increasing accuracy

    Science.gov (United States)

    Zhu, Ying; Fearn, Tom; MacKenzie, Gary; Clark, Ben; Dunn, Jason M.; Bigio, Irving J.; Bown, Stephen G.; Lovat, Laurence B.

    2009-07-01

    Elastic scattering spectroscopy (ESS) may be used to detect high-grade dysplasia (HGD) or cancer in Barrett's esophagus (BE). When spectra are measured in vivo by a hand-held optical probe, variability among replicated spectra from the same site can hinder the development of a diagnostic model for cancer risk. An experiment was carried out on excised tissue to investigate how two potential sources of this variability, pressure and angle, influence spectral variability, and the results were compared with the variations observed in spectra collected in vivo from patients with Barrett's esophagus. A statistical method called error removal by orthogonal subtraction (EROS) was applied to model and remove this measurement variability, which accounted for 96.6% of the variation in the spectra, from the in vivo data. Its removal allowed the construction of a diagnostic model with specificity improved from 67% to 82% (with sensitivity fixed at 90%). The improvement was maintained in predictions on an independent in vivo data set. EROS works well as an effective pretreatment for Barrett's in vivo data by identifying measurement variability and ameliorating its effect. The procedure reduces the complexity and increases the accuracy and interpretability of the model for classification and detection of cancer risk in Barrett's esophagus.

  2. The influence of different error estimates in the detection of postoperative cognitive dysfunction using reliable change indices with correction for practice effects.

    Science.gov (United States)

    Lewis, Matthew S; Maruff, Paul; Silbert, Brendan S; Evered, Lis A; Scott, David A

    2007-02-01

    The reliable change index (RCI) expresses change relative to its associated error, and is useful in the identification of postoperative cognitive dysfunction (POCD). This paper examines four common RCIs that each account for error in different ways. Three rules incorporate a constant correction for practice effects and are contrasted with the standard RCI that had no correction for practice. These rules are applied to 160 patients undergoing coronary artery bypass graft (CABG) surgery who completed neuropsychological assessments preoperatively and 1 week postoperatively using error and reliability data from a comparable healthy nonsurgical control group. The rules all identify POCD in a similar proportion of patients, but the use of the within-subject standard deviation (WSD), expressing the effects of random error, as an error estimate is a theoretically appropriate denominator when a constant error correction, removing the effects of systematic error, is deducted from the numerator in a RCI.

  3. Online Resources

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Genetics; Online Resources. Journal of Genetics. Online Resources. Volume 97. 2018 | Online resources. Volume 96. 2017 | Online resources. Volume 95. 2016 | Online resources. Volume 94. 2015 | Online resources. Volume 93. 2014 | Online resources. Volume 92. 2013 | Online resources ...

  4. Development of on-line sorting system for detection of infected seed potatoes using visible near-infrared transmittance spectral technique

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dae Yong; Cho, Byoung Kwan [Dept. of Biosystems Engineering, Chungnam National University, Daejeon (Korea, Republic of); Mo, Chang Yeun [Rural Development Administration, National Institute of Agricultural Engineering, Jeonju (Korea, Republic of); Kang, Jun Soon [Dept. of Horticultural Bioscience, Pusan National University, Pusan (Korea, Republic of)

    2015-02-15

    In this study, an online seed potato sorting system using a visible and near infrared (40 1100 nm) transmittance spectral technique and statistical model was evaluated for the nondestructive determination of infected and sound seed potatoes. Seed potatoes that had been artificially infected with Pectobacterium atrosepticum, which is known to cause a soil borne disease infection, were prepared for the experiments. After acquiring transmittance spectra from sound and infected seed potatoes, a determination algorithm for detecting infected seed potatoes was developed using the partial least square discriminant analysis method. The coefficient of determination(R{sup 2}{sub p}) of the prediction model was 0.943, and the classification accuracy was above 99% (n = 80) for discriminating diseased seed potatoes from sound ones. This online sorting system has good potential for developing a technique to detect agricultural products that are infected and contaminated by pathogens.

  5. Training-induced improvement of response selection and error detection in aging assessed by task switching: effects of cognitive, physical, and relaxation training.

    Science.gov (United States)

    Gajewski, Patrick D; Falkenstein, Michael

    2012-01-01

    Cognitive control functions decline with increasing age. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in changes of cognitive functions, as measured in electrophysiological brain activity (event-related potentials). One hundred forty-one healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength training), cognitive training (paper-pencil and computer-aided), relaxation and wellness (social control group), and a control group that did not receive any intervention. Training sessions took place twice a week for 90 min for a period of 4 months. The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task sets in working memory, and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials which showed higher amplitudes in a number of potentials associated with response selection (N2), allocation of cognitive resources (P3b), and error detection (Ne). Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

  6. Detección de errores potenciales de prescripción de carboplatino mediante validación farmacéutica Detection of potential prescription errors of carboplatin by pharmaceutical validation

    Directory of Open Access Journals (Sweden)

    María Antonieta Arbesú Michelena

    2011-06-01

    Full Text Available Las fallas en alguno de los procesos de la farmacoterapéutica podrían ser un riesgo potencial para que se cometan errores que puedan provocar daños en el paciente. Por este motivo todo servicio que aplique terapéutica citostática a sus pacientes debe establecer un procedimiento de validación de sus procesos, comenzando por la prescripción. En el presente trabajo se realizó un análisis del comportamiento de este proceso en las prescripciones que incluyeron el carboplatino, citostático cuyos efectos adversos son en general, frecuentes, moderadamente importantes y cuyas dosis deben ser ajustadas individualmente teniendo en cuenta el aclaramiento estimado y el área bajo la curva. Se realizó un estudio descriptivo retrospectivo con el objetivo de identificar las deficiencias en el transcurso de la validación farmacéutica de este fármaco, incluido en los esquemas de tratamientos de quimioterapia en pacientes con cáncer de pulmón. Fueron seleccionadas 45 órdenes médicas de pacientes comprendidos en grupos de edades mayores de 51 años, con comportamiento similar en uno y otro sexo y en los cuales predominó el cáncer de pulmón de células no pequeñas. Prevalecieron los errores sin daño de tipo B (64, seguidos de los errores sin daño tipo C (21. Los errores potenciales de tipo A se presentaron con una frecuencia de 26 oportunidades, en 8 de ellas no se indicó el área bajo la curva y en 18 no hubo cambio de dosis en los diferentes ciclos. Se concluye que el proceso de validación farmacéutica es vital para prevenir que los errores en la prescripción lleguen al paciente.All failures in some of the pharmacotherapy processes could be a potential risk to make mistakes that could to provoke damages in the patient. Thus, all service applying a cytostatic therapy to its patients must to establish a validation procedure of processes, beginning by prescription. In present paper an analysis of behavior of this process in the

  7. Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access

    Science.gov (United States)

    Klugman, Josh; Kuzmenko, Ella; Gupta, Rashmi

    2018-01-01

    Background On December 6 and 7, 2017, the US Department of Health and Human Services (HHS) hosted its first Code-a-Thon event aimed at leveraging technology and data-driven solutions to help combat the opioid epidemic. The authors—an interdisciplinary team from academia, the private sector, and the US Centers for Disease Control and Prevention—participated in the Code-a-Thon as part of the prevention track. Objective The aim of this study was to develop and deploy a methodology using machine learning to accurately detect the marketing and sale of opioids by illicit online sellers via Twitter as part of participation at the HHS Opioid Code-a-Thon event. Methods Tweets were collected from the Twitter public application programming interface stream filtered for common prescription opioid keywords in conjunction with participation in the Code-a-Thon from November 15, 2017 to December 5, 2017. An unsupervised machine learning–based approach was developed and used during the Code-a-Thon competition (24 hours) to obtain a summary of the content of the tweets to isolate those clusters associated with illegal online marketing and sale using a biterm topic model (BTM). After isolating relevant tweets, hyperlinks associated with these tweets were reviewed to assess the characteristics of illegal online sellers. Results We collected and analyzed 213,041 tweets over the course of the Code-a-Thon containing keywords codeine, percocet, vicodin, oxycontin, oxycodone, fentanyl, and hydrocodone. Using BTM, 0.32% (692/213,041) tweets were identified as being associated with illegal online marketing and sale of prescription opioids. After removing duplicates and dead links, we identified 34 unique “live” tweets, with 44% (15/34) directing consumers to illicit online pharmacies, 32% (11/34) linked to individual drug sellers, and 21% (7/34) used by marketing affiliates. In addition to offering the “no prescription” sale of opioids, many of these vendors also sold other

  8. Automatic on-line monitoring of atmospheric volatile organic compounds: Gas chromatography-mass spectrometry and gas chromatography-flame ionization detection as complementary systems

    International Nuclear Information System (INIS)

    Blas, Maite de; Navazo, Marino; Alonso, Lucio; Durana, Nieves; Iza, Jon

    2011-01-01

    Traditionally air quality networks have been carrying out the continuous, on-line measurement of volatile organic compounds (VOC) in ambient air with GC-FID. In this paper some identification and coelution problems observed while using this technique in long-term measurement campaigns are described. In order to solve these problems a GC-MS was set up and operated simultaneously with a GC-FID for C 2 -C 11 VOCs measurement. There are few on-line, unattended, long term measurements of atmospheric VOCs performed with GC-MS. In this work such a system has been optimized for that purpose, achieving good repeatability, linearity, and detection limits of the order of the GC-FID ones, even smaller in some cases. VOC quantification has been made by using response factors, which is not frequent in on-line GC-MS. That way, the identification and coelution problems detected in the GC-FID, which may led to reporting erroneous data, could be corrected. The combination of GC-FID and GC-MS as complementary techniques for the measurement of speciated VOCs in ambient air at sub-ppbv levels is proposed. Some results of the measurements are presented, including concentration values for some compounds not found until now on public ambient air VOC databases, which were identified and quantified combining both techniques. Results may also help to correct previously published VOC data with wrongly identified compounds by reprocessing raw chromatographic data.

  9. Ultrasensitive and accelerated detection of ciguatoxin by capillary electrophoresis via on-line sandwich immunoassay with rotating magnetic field and nanoparticles signal enhancement.

    Science.gov (United States)

    Zhang, Zhaoxiang; Zhang, Chaoying; Luan, Wenxiu; Li, Xiufeng; Liu, Ying; Luo, Xiliang

    2015-08-12

    A sensitive and rapid on-line immunoassay for the determination of ciguatoxin CTX3C was developed based on a capillary mixing system, which was integrated with capillary electrophoresis (CE) separation and electrochemical (EC) detection. In the sandwich immunoassay system, anti-CTX3C-functionalized magnetic nanoparticles were used as immunosensing probes, and horseradish peroxidase (HRP) and anti-CTX3C antibody were bound onto the surface of gold nanoparticles (AuNPs) and used as recognition elements. Online formation of immunocomplex was realized in capillary inlet end with an external rotating magnetic field. Compared with classical HPLC-MS and ELISA, the assay adopting AuNPs as multienzyme carriers and online sandwich immunoassay format with rotating magnetic field exhibited higher sensitivity and shorter assay time. The linear range of the assay for CTX3C was from 0.6 to 150 ng/L with a correlation coefficient of 0.9948 (n = 2), and the detection limit (S/N = 3) was 0.09 ng/L. The developed assay showed satisfying reproducibility and stability, and it was successfully applied for the quantification of CTX3C in fish samples. Copyright © 2015 Elsevier B.V. All rights reserved.

  10. Detection and on-line prediction of leak magnitude in a gas pipeline using an acoustic method and neural network data processing

    Directory of Open Access Journals (Sweden)

    R. B. Santos

    2014-03-01

    Full Text Available Considering the importance of monitoring pipeline systems, this work presents the development of a technique to detect gas leakage in pipelines, based on an acoustic method, and on-line prediction of leak magnitude using artificial neural networks. On-line audible noises generated by leakage were obtained with a microphone installed in a 60 m long pipeline. The sound noises were decomposed into sounds of different frequencies: 1 kHz, 5 kHz and 9 kHz. The dynamics of these noises in time were used as input to the neural model in order to determine the occurrence and the leak magnitude. The results indicated the great potential of the technique and of the developed neural network models. For all on-line tests, the models showed 100% accuracy in leak detection, except for a small orifice (1 mm under 4 kgf/cm² of nominal pressure. Similarly, the neural network models could adequately predict the magnitude of the leakages.

  11. Training-induced improvement of response selection and error detection in aging assessed by task switching: Effects of cognitive, physical and relaxation training

    Directory of Open Access Journals (Sweden)

    Patrick Darius Gajewski

    2012-05-01

    Full Text Available Cognitive control functions decline with increasing age. One of them is response selection that forms the link between the goals and the motor system and is therefore crucial for performance outcomes in cognitive tasks. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in electrophysiological brain activity, as measured in event-related potentials (ERPs. 141 healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength-training, cognitive training (paper-pencil and computer-aided, relaxation and wellness (social control group and a no-contact control group that did not receive any intervention. Training sessions took place twice a week for 90 minutes for a period of 4 months.The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task-sets in working memory and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials (ERP which showed higher amplitudes in a number of potentials associated with response selection (N2, allocation of cognitive resources (P3b and error detection (Ne.Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

  12. Living with an inborn error of metabolism detected by newborn screening-parents' perspectives on child development and impact on family life.

    Science.gov (United States)

    Gramer, Gwendolyn; Haege, Gisela; Glahn, Esther M; Hoffmann, Georg F; Lindner, Martin; Burgard, Peter

    2014-03-01

    Newborn screening for inborn errors of metabolism is regarded as highly successful by health professionals. Little is known about parents' perspectives on child development and social impact on families. Parents of 187 patients with metabolic disorders detected by newborn screening rated child development, perceived burdens on child and family, and future expectations on a questionnaire with standardized answers. Parental ratings were compared with standardized psychometric test results. Regression analysis was performed to identify factors associated with extent of perceived burden. In 26.2% of patients, parents perceived delays in global development and/or specific developmental domains (physical, social, intellectual, language). Parents expected normal future development in 95.7%, and an independent adult life for their child in 94.6%. Comparison with psychometric test results showed that parents of children with cognitive impairments tended to overrate their child's abilities. Mild/medium burden posed on the family (child) by the metabolic disorder was stated by 56.1% (48.9%) of parents, severe/very severe burden by 19.3% (8.6%). One third of families reported financial burden due to the metabolic disorder. Dietary treatment and diagnoses with risk for metabolic decompensation despite treatment were associated with higher perceived burden for the family. Disorders rated as potentially very burdensome by experts were not rated accordingly by parents, demonstrating different perspectives of professionals and parents. Although newborn screening leads to favourable physical and cognitive outcome, living with a metabolic disorder may cause considerable stress on patients and families, emphasizing the need for comprehensive multidisciplinary care including psychological and social support.

  13. Medication Errors - A Review

    OpenAIRE

    Vinay BC; Nikhitha MK; Patel Sunil B

    2015-01-01

    In this present review article, regarding medication errors its definition, medication error problem, types of medication errors, common causes of medication errors, monitoring medication errors, consequences of medication errors, prevention of medication error and managing medication errors have been explained neatly and legibly with proper tables which is easy to understand.

  14. On-line detection of apnea/hypopnea events using SpO2 signal: a rule-based approach employing binary classifier models.

    Science.gov (United States)

    Koley, Bijoy Laxmi; Dey, Debangshu

    2014-01-01

    This paper presents an online method for automatic detection of apnea/hypopnea events, with the help of oxygen saturation (SpO2) signal, measured at fingertip by Bluetooth nocturnal pulse oximeter. Event detection is performed by identifying abnormal data segments from the recorded SpO2 signal, employing a binary classifier model based on a support vector machine (SVM). Thereafter the abnormal segment is further analyzed to detect different states within the segment, i.e., steady, desaturation, and resaturation, with the help of another SVM-based binary ensemble classifier model. Finally, a heuristically obtained rule-based system is used to identify the apnea/hypopnea events from the time-sequenced decisions of these classifier models. In the developmental phase, a set of 34 time domain-based features was extracted from the segmented SpO2 signal using an overlapped windowing technique. Later, an optimal set of features was selected on the basis of recursive feature elimination technique. A total of 34 subjects were included in the study. The results show average event detection accuracies of 96.7% and 93.8% for the offline and the online tests, respectively. The proposed system provides direct estimation of the apnea/hypopnea index with the help of a relatively inexpensive and widely available pulse oximeter. Moreover, the system can be monitored and accessed by physicians through LAN/WAN/Internet and can be extended to deploy in Bluetooth-enabled mobile phones.

  15. Development of On-Line High Performance Liquid Chromatography (HPLC)-Biochemical Detection Methods as Tools in the Identification of Bioactives