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

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

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

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.

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.

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.

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).

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...

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.

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

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

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.

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.

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....

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

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.

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…

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).

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

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.

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 �

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.

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....

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.

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

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)

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.

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.…

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.

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...

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.

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.

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)

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.

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.

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.

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.

WE-D-BRA-04: Online 3D EPID-Based Dose Verification for Optimum Patient Safety

International Nuclear Information System (INIS)

Spreeuw, H; Rozendaal, R; Olaciregui-Ruiz, I; Mans, A; Mijnheer, B; Herk, M van; Gonzalez, P

2015-01-01

Purpose: To develop an online 3D dose verification tool based on EPID transit dosimetry to ensure optimum patient safety in radiotherapy treatments. Methods: A new software package was developed which processes EPID portal images online using a back-projection algorithm for the 3D dose reconstruction. The package processes portal images faster than the acquisition rate of the portal imager (∼ 2.5 fps). After a portal image is acquired, the software seeks for “hot spots” in the reconstructed 3D dose distribution. A hot spot is in this study defined as a 4 cm 3 cube where the average cumulative reconstructed dose exceeds the average total planned dose by at least 20% and 50 cGy. If a hot spot is detected, an alert is generated resulting in a linac halt. The software has been tested by irradiating an Alderson phantom after introducing various types of serious delivery errors. Results: In our first experiment the Alderson phantom was irradiated with two arcs from a 6 MV VMAT H&N treatment having a large leaf position error or a large monitor unit error. For both arcs and both errors the linac was halted before dose delivery was completed. When no error was introduced, the linac was not halted. The complete processing of a single portal frame, including hot spot detection, takes about 220 ms on a dual hexacore Intel Xeon 25 X5650 CPU at 2.66 GHz. Conclusion: A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for various kinds of gross delivery errors. The detection of hot spots was proven to be effective for the timely detection of these errors. Current work is focused on hot spot detection criteria for various treatment sites and the introduction of a clinical pilot program with online verification of hypo-fractionated (lung) treatments

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

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)

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.

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.

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

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

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.

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.

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.

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…

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.

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.

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...

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.

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.

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.

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.

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.

Quality assurance for online adapted treatment plans: Benchmarking and delivery monitoring simulation

International Nuclear Information System (INIS)

Li, Taoran; Wu, Qiuwen; Yang, Yun; Rodrigues, Anna; Yin, Fang-Fang; Jackie Wu, Q.

2015-01-01

. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy

Quality assurance for online adapted treatment plans: Benchmarking and delivery monitoring simulation

Energy Technology Data Exchange (ETDEWEB)

Li, Taoran, E-mail: taoran.li.duke@gmail.com; Wu, Qiuwen; Yang, Yun; Rodrigues, Anna; Yin, Fang-Fang; Jackie Wu, Q. [Department of Radiation Oncology, Duke University Medical Center Durham, North Carolina 27710 (United States)

2015-01-15

. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.

Quality assurance for online adapted treatment plans: benchmarking and delivery monitoring simulation.

Science.gov (United States)

Li, Taoran; Wu, Qiuwen; Yang, Yun; Rodrigues, Anna; Yin, Fang-Fang; Jackie Wu, Q

2015-01-01

found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system's ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.

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.

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

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.

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.

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.

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.

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

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.

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.

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.

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

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.

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

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.

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.

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.)

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...

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

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

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...

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...

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....

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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...

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.

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.

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...

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…

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

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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.

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

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

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).

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.

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.

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.

On-line Monitoring System for Power Transformers

Directory of Open Access Journals (Sweden)

Alexandru HOTEA

2016-12-01

Full Text Available Power transformers are the most important and expensive equipment from the electricity transmission system, so it is very important to know the real state of health of such equipment in every moment. De-energizing the power transformer accidentally due to internal defects can generate high costs. Annual maintenance proved to be ineffective in many cases to determine the internal condition of the equipment degradation due to faults rapidly evolving. An On-line Monitoring System for Power Transformers help real-time condition assessment and to detect errors early enough to take action to eliminate or minimize them. After abnormality detected, it is still important to perform full diagnostic tests to determine the exact condition of the equipment. On-line monitoring systems can help increase the level of availability and reliability of power transformers and lower costs of accidental interruption. This paper presents cases studies on several power transformers equipped with on-line monitoring systems from Transelectrica substation.

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...

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.

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.

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

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

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.

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

Masked and unmasked error-related potentials during continuous control and feedback

Science.gov (United States)

Lopes Dias, Catarina; Sburlea, Andreea I.; Müller-Putz, Gernot R.

2018-06-01

The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in tasks with continuous feedback is still in its early stages. Objective. We developed a task in which subjects have continuous control of a cursor’s position by means of a joystick. The cursor’s position was shown to the participants in two different modalities of continuous feedback: normal and jittered. The jittered feedback was created to mimic the instability that could exist if participants controlled the trajectory directly with brain signals. Approach. This paper studies the electroencephalographic (EEG)—measurable signatures caused by a loss of control over the cursor’s trajectory, causing a target miss. Main results. In both feedback modalities, time-locked potentials revealed the typical frontal-central components of error-related potentials. Errors occurring during the jittered feedback (masked errors) were delayed in comparison to errors occurring during normal feedback (unmasked errors). Masked errors displayed lower peak amplitudes than unmasked errors. Time-locked classification analysis allowed a good distinction between correct and error classes (average Cohen-, average TPR  =  81.8% and average TNR  =  96.4%). Time-locked classification analysis between masked error and unmasked error classes revealed results at chance level (average Cohen-, average TPR  =  60.9% and average TNR  =  58.3%). Afterwards, we performed asynchronous detection of ErrPs, combining both masked and unmasked trials. The asynchronous detection of ErrPs in a simulated online scenario resulted in an average TNR of 84.0% and in an average TPR of 64.9%. Significance. The time-locked classification results suggest that the masked and unmasked errors were indistinguishable in terms of classification. The asynchronous classification results suggest that the

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.

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.

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.

Patients’ online access to their electronic health records and linked online services: a systematic interpretative review

Science.gov (United States)

de Lusignan, Simon; Mold, Freda; Sheikh, Aziz; Majeed, Azeem; Wyatt, Jeremy C; Quinn, Tom; Cavill, Mary; Gronlund, Toto Anne; Franco, Christina; Chauhan, Umesh; Blakey, Hannah; Kataria, Neha; Barker, Fiona; Ellis, Beverley; Koczan, Phil; Arvanitis, Theodoros N; McCarthy, Mary; Jones, Simon; Rafi, Imran

2014-01-01

Objectives To investigate the effect of providing patients online access to their electronic health record (EHR) and linked transactional services on the provision, quality and safety of healthcare. The objectives are also to identify and understand: barriers and facilitators for providing online access to their records and services for primary care workers; and their association with organisational/IT system issues. Setting Primary care. Participants A total of 143 studies were included. 17 were experimental in design and subject to risk of bias assessment, which is reported in a separate paper. Detailed inclusion and exclusion criteria have also been published elsewhere in the protocol. Primary and secondary outcome measures Our primary outcome measure was change in quality or safety as a result of implementation or utilisation of online records/transactional services. Results No studies reported changes in health outcomes; though eight detected medication errors and seven reported improved uptake of preventative care. Professional concerns over privacy were reported in 14 studies. 18 studies reported concern over potential increased workload; with some showing an increase workload in email or online messaging; telephone contact remaining unchanged, and face-to face contact staying the same or falling. Owing to heterogeneity in reporting overall workload change was hard to predict. 10 studies reported how online access offered convenience, primarily for more advantaged patients, who were largely highly satisfied with the process when clinician responses were prompt. Conclusions Patient online access and services offer increased convenience and satisfaction. However, professionals were concerned about impact on workload and risk to privacy. Studies correcting medication errors may improve patient safety. There may need to be a redesign of the business process to engage health professionals in online access and of the EHR to make it friendlier and provide equity of

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

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

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.

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.

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.

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

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.

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.

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

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

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

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)

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.

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.

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.

Error Recovery in the Time-Triggered Paradigm with FTT-CAN.

Science.gov (United States)

Marques, Luis; Vasconcelos, Verónica; Pedreiras, Paulo; Almeida, Luís

2018-01-11

Data networks are naturally prone to interferences that can corrupt messages, leading to performance degradation or even to critical failure of the corresponding distributed system. To improve resilience of critical systems, time-triggered networks are frequently used, based on communication schedules defined at design-time. These networks offer prompt error detection, but slow error recovery that can only be compensated with bandwidth overprovisioning. On the contrary, the Flexible Time-Triggered (FTT) paradigm uses online traffic scheduling, which enables a compromise between error detection and recovery that can achieve timely recovery with a fraction of the needed bandwidth. This article presents a new method to recover transmission errors in a time-triggered Controller Area Network (CAN) network, based on the Flexible Time-Triggered paradigm, namely FTT-CAN. The method is based on using a server (traffic shaper) to regulate the retransmission of corrupted or omitted messages. We show how to design the server to simultaneously: (1) meet a predefined reliability goal, when considering worst case error recovery scenarios bounded probabilistically by a Poisson process that models the fault arrival rate; and, (2) limit the direct and indirect interference in the message set, preserving overall system schedulability. Extensive simulations with multiple scenarios, based on practical and randomly generated systems, show a reduction of two orders of magnitude in the average bandwidth taken by the proposed error recovery mechanism, when compared with traditional approaches available in the literature based on adding extra pre-defined transmission slots.

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

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).

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].

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.

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

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.

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...

Residual-driven online generalized multiscale finite element methods

KAUST Repository

Chung, Eric T.

2015-09-08

The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current residual. Online multiscale basis functions are constructed adaptively in some selected regions based on our error indicators. We derive an error estimator which shows that one needs to have an offline space with certain properties to guarantee that additional online multiscale basis function will decrease the error. This error decrease is independent of physical parameters, such as the contrast and multiple scales in the problem. The offline spaces are constructed using Generalized Multiscale Finite Element Methods (GMsFEM). We show that if one chooses a sufficient number of offline basis functions, one can guarantee that additional online multiscale basis functions will reduce the error independent of contrast. We note that the construction of online basis functions is motivated by the fact that the offline space construction does not take into account distant effects. Using the residual information, we can incorporate the distant information provided the offline approximation satisfies certain properties. In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

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...

Patients' online access to their electronic health records and linked online services: a systematic interpretative review.

Science.gov (United States)

de Lusignan, Simon; Mold, Freda; Sheikh, Aziz; Majeed, Azeem; Wyatt, Jeremy C; Quinn, Tom; Cavill, Mary; Gronlund, Toto Anne; Franco, Christina; Chauhan, Umesh; Blakey, Hannah; Kataria, Neha; Barker, Fiona; Ellis, Beverley; Koczan, Phil; Arvanitis, Theodoros N; McCarthy, Mary; Jones, Simon; Rafi, Imran

2014-09-08

To investigate the effect of providing patients online access to their electronic health record (EHR) and linked transactional services on the provision, quality and safety of healthcare. The objectives are also to identify and understand: barriers and facilitators for providing online access to their records and services for primary care workers; and their association with organisational/IT system issues. Primary care. A total of 143 studies were included. 17 were experimental in design and subject to risk of bias assessment, which is reported in a separate paper. Detailed inclusion and exclusion criteria have also been published elsewhere in the protocol. Our primary outcome measure was change in quality or safety as a result of implementation or utilisation of online records/transactional services. No studies reported changes in health outcomes; though eight detected medication errors and seven reported improved uptake of preventative care. Professional concerns over privacy were reported in 14 studies. 18 studies reported concern over potential increased workload; with some showing an increase workload in email or online messaging; telephone contact remaining unchanged, and face-to face contact staying the same or falling. Owing to heterogeneity in reporting overall workload change was hard to predict. 10 studies reported how online access offered convenience, primarily for more advantaged patients, who were largely highly satisfied with the process when clinician responses were prompt. Patient online access and services offer increased convenience and satisfaction. However, professionals were concerned about impact on workload and risk to privacy. Studies correcting medication errors may improve patient safety. There may need to be a redesign of the business process to engage health professionals in online access and of the EHR to make it friendlier and provide equity of access to a wider group of patients. A1 SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO

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…

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

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...

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

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

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

Three-dimensional glue detection and evaluation based on linear structured light

Science.gov (United States)

Xiao, Zhitao; Yang, Ruipeng; Geng, Lei; Liu, Yanbei

2018-01-01

During the online glue detection of body in white (BIW), the purpose of traditional glue detection based on machine vision is the localization and segmentation of glue, which is dissatisfactory for estimating the uniformity of glue with complex shape. A three-dimensional glue detection method based on the linear structured light and the movement parameters of robot is proposed. Firstly, the linear structured light and epipolar constraint algorithm are used for sign matching of binocular vision. Then, hand-eye relationship between robot and binocular camera is utilized to unified coordinate system. Finally, a structured light stripe extraction method is proposed to extract the sub-pixel coordinates of the light strip center. Experiments results demonstrate that the propose method can estimate the shape of glue accurately. For three kinds of glue with complex shape and uneven illumination, our method can detect the positions of blemishes. The absolute error of measurement is less than 1.04mm and the relative error is less than 10% respectively, which is suitable for online glue detection in BIW.

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

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...

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...

The Error Reporting in the ATLAS TDAQ system

CERN Document Server

Kolos, S; The ATLAS collaboration; Papaevgeniou, L

2014-01-01

The ATLAS Error Reporting feature, which is used in the TDAQ environment, provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service(ERS), gives software applications the opportunity to collect and send comprehensive data about errors, happening at run-time, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the Error Reporting service as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When applications send information to ERS, depending on the actual configuration the information may end up in a local file, in a database, in distributed middle-ware, which can transport it to an expert system or dis...

The Error Reporting in the ATLAS TDAQ System

CERN Document Server

Kolos, S; The ATLAS collaboration; Papaevgeniou, L

2015-01-01

The ATLAS Error Reporting feature, which is used in the TDAQ environment, provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service(ERS), gives software applications the opportunity to collect and send comprehensive data about errors, happening at run-time, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the Error Reporting service as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When applications send information to ERS, depending on the actual configuration the information may end up in a local file, in a database, in distributed middle-ware, which can transport it to an expert system or dis...

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.

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...

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...

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

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.

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...

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...

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.

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.

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.

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.

Electrophysiological Correlates of Error Monitoring and Feedback Processing in Second Language Learning.

Science.gov (United States)

Bultena, Sybrine; Danielmeier, Claudia; Bekkering, Harold; Lemhöfer, Kristin

2017-01-01

Humans monitor their behavior to optimize performance, which presumably relies on stable representations of correct responses. During second language (L2) learning, however, stable representations have yet to be formed while knowledge of the first language (L1) can interfere with learning, which in some cases results in persistent errors. In order to examine how correct L2 representations are stabilized, this study examined performance monitoring in the learning process of second language learners for a feature that conflicts with their first language. Using EEG, we investigated if L2 learners in a feedback-guided word gender assignment task showed signs of error detection in the form of an error-related negativity (ERN) before and after receiving feedback, and how feedback is processed. The results indicated that initially, response-locked negativities for correct (CRN) and incorrect (ERN) responses were of similar size, showing a lack of internal error detection when L2 representations are unstable. As behavioral performance improved following feedback, the ERN became larger than the CRN, pointing to the first signs of successful error detection. Additionally, we observed a second negativity following the ERN/CRN components, the amplitude of which followed a similar pattern as the previous negativities. Feedback-locked data indicated robust FRN and P300 effects in response to negative feedback across different rounds, demonstrating that feedback remained important in order to update memory representations during learning. We thus show that initially, L2 representations may often not be stable enough to warrant successful error monitoring, but can be stabilized through repeated feedback, which means that the brain is able to overcome L1 interference, and can learn to detect errors internally after a short training session. The results contribute a different perspective to the discussion on changes in ERN and FRN components in relation to learning, by extending the

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

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.

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

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.

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.

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.

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

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

The Impact of Error-Management Climate, Error Type and Error Originator on Auditors’ Reporting Errors Discovered on Audit Work Papers

NARCIS (Netherlands)

A.H. Gold-Nöteberg (Anna); U. Gronewold (Ulfert); S. Salterio (Steve)

2010-01-01

textabstractWe examine factors affecting the auditor’s willingness to report their own or their peers’ self-discovered errors in working papers subsequent to detailed working paper review. Prior research has shown that errors in working papers are detected in the review process; however, such

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

[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.

Error-related anterior cingulate cortex activity and the prediction of conscious error awareness

Directory of Open Access Journals (Sweden)

Catherine eOrr

2012-06-01

Full Text Available Research examining the neural mechanisms associated with error awareness has consistently identified dorsal anterior cingulate activity (ACC as necessary but not predictive of conscious error detection. Two recent studies (Steinhauser and Yeung, 2010; Wessel et al. 2011 have found a contrary pattern of greater dorsal ACC activity (in the form of the error-related negativity during detected errors, but suggested that the greater activity may instead reflect task influences (e.g., response conflict, error probability and or individual variability (e.g., statistical power. We re-analyzed fMRI BOLD data from 56 healthy participants who had previously been administered the Error Awareness Task, a motor Go/No-go response inhibition task in which subjects make errors of commission of which they are aware (Aware errors, or unaware (Unaware errors. Consistent with previous data, the activity in a number of cortical regions was predictive of error awareness, including bilateral inferior parietal and insula cortices, however in contrast to previous studies, including our own smaller sample studies using the same task, error-related dorsal ACC activity was significantly greater during aware errors when compared to unaware errors. While the significantly faster RT for aware errors (compared to unaware was consistent with the hypothesis of higher response conflict increasing ACC activity, we could find no relationship between dorsal ACC activity and the error RT difference. The data suggests that individual variability in error awareness is associated with error-related dorsal ACC activity, and therefore this region may be important to conscious error detection, but it remains unclear what task and individual factors influence error awareness.

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.

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)

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

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

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.

The Error Reporting in the ATLAS TDAQ System

Science.gov (United States)

Kolos, Serguei; Kazarov, Andrei; Papaevgeniou, Lykourgos

2015-05-01

The ATLAS Error Reporting provides a service that allows experts and shift crew to track and address errors relating to the data taking components and applications. This service, called the Error Reporting Service (ERS), gives to software applications the opportunity to collect and send comprehensive data about run-time errors, to a place where it can be intercepted in real-time by any other system component. Other ATLAS online control and monitoring tools use the ERS as one of their main inputs to address system problems in a timely manner and to improve the quality of acquired data. The actual destination of the error messages depends solely on the run-time environment, in which the online applications are operating. When an application sends information to ERS, depending on the configuration, it may end up in a local file, a database, distributed middleware which can transport it to an expert system or display it to users. Thanks to the open framework design of ERS, new information destinations can be added at any moment without touching the reporting and receiving applications. The ERS Application Program Interface (API) is provided in three programming languages used in the ATLAS online environment: C++, Java and Python. All APIs use exceptions for error reporting but each of them exploits advanced features of a given language to simplify the end-user program writing. For example, as C++ lacks language support for exceptions, a number of macros have been designed to generate hierarchies of C++ exception classes at compile time. Using this approach a software developer can write a single line of code to generate a boilerplate code for a fully qualified C++ exception class declaration with arbitrary number of parameters and multiple constructors, which encapsulates all relevant static information about the given type of issues. When a corresponding error occurs at run time, the program just need to create an instance of that class passing relevant values to one

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.

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.

Impact of Measurement Error on Synchrophasor Applications

Energy Technology Data Exchange (ETDEWEB)

Liu, Yilu [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gracia, Jose R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ewing, Paul D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Zhao, Jiecheng [Univ. of Tennessee, Knoxville, TN (United States); Tan, Jin [Univ. of Tennessee, Knoxville, TN (United States); Wu, Ling [Univ. of Tennessee, Knoxville, TN (United States); Zhan, Lingwei [Univ. of Tennessee, Knoxville, TN (United States)

2015-07-01

Phasor measurement units (PMUs), a type of synchrophasor, are powerful diagnostic tools that can help avert catastrophic failures in the power grid. Because of this, PMU measurement errors are particularly worrisome. This report examines the internal and external factors contributing to PMU phase angle and frequency measurement errors and gives a reasonable explanation for them. It also analyzes the impact of those measurement errors on several synchrophasor applications: event location detection, oscillation detection, islanding detection, and dynamic line rating. The primary finding is that dynamic line rating is more likely to be influenced by measurement error. Other findings include the possibility of reporting nonoscillatory activity as an oscillation as the result of error, failing to detect oscillations submerged by error, and the unlikely impact of error on event location and islanding detection.

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%.

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.

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.

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.

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.

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.

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

Simulation of 3D-treatment plans in head and neck tumors aided by matching of digitally reconstructed radiographs (DRR) and on-line distortion corrected simulator images

International Nuclear Information System (INIS)

Lohr, Frank; Schramm, Oliver; Schraube, Peter; Sroka-Perez, Gabriele; Seeber, Steffen; Schlepple, Gerd; Schlegel, Wolfgang; Wannenmacher, Michael

1997-01-01

Background and purpose: Simulation of 3D-treatment plans for head and neck malignancy is difficult due to complex anatomy. Therefore, CT-simulation and stereotactic techniques are becoming more common in the treatment preparation, overcoming the need for simulation. However, if simulation is still performed, it is an important step in the treatment preparation/execution chain, since simulation errors, if not detected immediately, can compromise the success of treatment. A recently developed PC-based system for on-line image matching and comparison of digitally reconstructed radiographs (DRR) and distortion corrected simulator monitor images that enables instant correction of field placement errors during the simulation process was evaluated. The range of field placement errors with noncomputer aided simulation is reported. Materials and methods: For 14 patients either a primary 3D-treatment plan or a 3D-boost plan after initial treatment with opposing laterals for head and neck malignancy with a coplanar or non-coplanar two- or three-field technique was simulated. After determining the robustness of the matching process and the accuracy of field placement error detection with phantom measurements, DRRs were generated from the treatment planning CT-dataset of each patient and were interactively matched with on-line simulator images that had undergone correction for geometrical distortion, using a landmark algorithm. Translational field placement errors in all three planes as well as in-plane rotational errors were studied and were corrected immediately. Results: The interactive matching process is very robust with a tolerance of <2 mm when suitable anatomical landmarks are chosen. The accuracy for detection of translational errors in phantom measurements was <1 mm and for in-plane rotational errors the accuracy had a maximum of only 1.5 deg.. For patient simulation, the mean absolute distance of the planned versus simulated isocenter was 6.4 ± 3.9 mm. The in

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.

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)

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.

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

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.

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.

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

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.

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...

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.

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.

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.

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.

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.

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.

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.

Bibliographic Instruction and the Development of Online Catalogs.

Science.gov (United States)

McDonald, David R.; Searing, Susan E.

1983-01-01

Discusses the definition of an online library catalog; five factors to be considered by the online catalog designer; user-computer communication (error messages, help screens, prompts, unnatural language); online tutorials and offline instruction offered by bibliographic instruction librarians; and the current situation. Nine references are…

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

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.

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.

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.

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

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

Online 3D EPID-based dose verification: Proof of concept

Energy Technology Data Exchange (ETDEWEB)

Spreeuw, Hanno; Rozendaal, Roel, E-mail: r.rozendaal@nki.nl; Olaciregui-Ruiz, Igor; González, Patrick; Mans, Anton; Mijnheer, Ben [Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam 1066 CX (Netherlands); Herk, Marcel van [University of Manchester, Manchester Academic Health Science Centre, The Christie NHS Foundation Trust, Manchester M20 4BX (United Kingdom)

2016-07-15

, including dose verification, took 266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5–10 s irradiation time. Conclusions: A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

Online 3D EPID-based dose verification: Proof of concept

International Nuclear Information System (INIS)

Spreeuw, Hanno; Rozendaal, Roel; Olaciregui-Ruiz, Igor; González, Patrick; Mans, Anton; Mijnheer, Ben; Herk, Marcel van

2016-01-01

, including dose verification, took 266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5–10 s irradiation time. Conclusions: A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

Online 3D EPID-based dose verification: Proof of concept.

Science.gov (United States)

Spreeuw, Hanno; Rozendaal, Roel; Olaciregui-Ruiz, Igor; González, Patrick; Mans, Anton; Mijnheer, Ben; van Herk, Marcel

2016-07-01

266 ± 11 ms on a dual octocore Intel Xeon E5-2630 CPU running at 2.40 GHz. The introduced delivery errors were detected after 5-10 s irradiation time. A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

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 ...

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

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

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.

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

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.

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)

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.

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.

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.

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.

Online dynamic equalization adjustment of high-power lithium-ion battery packs based on the state of balance estimation

International Nuclear Information System (INIS)

Wang, Shunli; Shang, Liping; Li, Zhanfeng; Deng, Hu; Li, Jianchao

2016-01-01

Highlights: • A novel concept (SOB, State of Balance) is proposed for the LIB pack equalization. • Core parameter detection and filtering is analyzed to identify the LIB pack behavior. • The electrical UKF model is adopted for the online dynamic estimation. • The equalization target model is built based on the optimum preference. • Comprehensive imbalance state calculation is implemented for the adjustment. - Abstract: A novel concept named as state of balance (SOB) is proposed and its online dynamic estimation method is presented for the high-power lithium-ion battery (LIB) packs, based on which the online dynamic equalization adjustment is realized aiming to protect the operation safety of its power supply application. The core parameter detection method based on the specific moving average algorithm is studied because of their identical varying characteristics on the individual cells due to the manufacturing variability and other factors, affecting the performance of the high-power LIB pack. The SOB estimation method is realized with the detailed deduction, in which a dual filter consisting of the Unscented Kalman filter (UKF), equivalent circuit model (ECM) and open circuit voltage (OCV) is used in order to predict the SOB state. It is beneficial for the energy operation and the energy performance state can be evaluated online prior to the adjustment method based on the terminal voltage consistency. The energy equalization is realized that is based on the credibility reasoning together with the equalization model building process. The experiments including the core parameter detection, SOB estimation and equalization adjustment are done and the experimental results are analyzed. The experiment results show that the numerical Coulomb efficiency is bigger than 95%. The cell voltage measurement error is less than 5 mV and the terminal voltage measurement error of the LIB pack is less than 1% FS. The measurement error of the battery discharge and charge

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.

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.

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.

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.

Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of offline modeling errors

Science.gov (United States)

Marti, Alejandro; Folch, Arnau

2018-03-01

Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated with the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems in which meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated with the offline modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the offline coupling strategy are compared against those from an online forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors due to the offline modeling are of the same order of magnitude as those associated with the source term uncertainties. In particular, traditional offline forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45-70 % of the ash cloud of an online forecast. These inconsistencies are anticipated to be even more relevant in scenarios in which the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real-time advisories for aviation to consider employing computationally

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.

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.

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.

The Neural-fuzzy Thermal Error Compensation Controller on CNC Machining Center

Science.gov (United States)

Tseng, Pai-Chung; Chen, Shen-Len

The geometric errors and structural thermal deformation are factors that influence the machining accuracy of Computer Numerical Control (CNC) machining center. Therefore, researchers pay attention to thermal error compensation technologies on CNC machine tools. Some real-time error compensation techniques have been successfully demonstrated in both laboratories and industrial sites. The compensation results still need to be enhanced. In this research, the neural-fuzzy theory has been conducted to derive a thermal prediction model. An IC-type thermometer has been used to detect the heat sources temperature variation. The thermal drifts are online measured by a touch-triggered probe with a standard bar. A thermal prediction model is then derived by neural-fuzzy theory based on the temperature variation and the thermal drifts. A Graphic User Interface (GUI) system is also built to conduct the user friendly operation interface with Insprise C++ Builder. The experimental results show that the thermal prediction model developed by neural-fuzzy theory methodology can improve machining accuracy from 80µm to 3µm. Comparison with the multi-variable linear regression analysis the compensation accuracy is increased from ±10µm to ±3µm.

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...

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

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

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

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).

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...

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

Positioning errors assessed with kV cone-beam CT for image-guided prostate radiotherapy

International Nuclear Information System (INIS)

Li Jiongyan; Guo Xiaomao; Yao Weiqiang; Wang Yanyang; Ma Jinli; Chen Jiayi; Zhang Zhen; Feng Yan

2010-01-01

Objective: To assess set-up errors measured with kilovoltage cone-beam CT (KV-CBCT), and the impact of online corrections on margins required to account for set-up variability during IMRT for patients with prostate cancer. Methods: Seven patients with prostate cancer undergoing IMRT were enrolled onto the study. The KV-CBCT scans were acquired at least twice weekly. After initial set-up using the skin marks, a CBCT scan was acquired and registered with the planning CT to determine the setup errors using an auto grey-scale registration software. Corrections would be made by moving the table if the setup errors were considered clinically significant (i. e. , > 2 mm). A second CBCT scan was acquired immediately after the corrections to evaluate the residual error. PTV margins were derived to account for the measured set-up errors and residual errors determined for this group of patients. Results: 197 KV-CBCT images in total were acquired. The random and systematic positioning errors and calculated PTV margins without correction in mm were : a) Lateral 3.1, 2.1, 9.3; b) Longitudinal 1.5, 1.8, 5.1;c) Vertical 4.2, 3.7, 13.0. The random and systematic positioning errors and calculated PTV margin with correction in mm were : a) Lateral 1.1, 0.9, 3.4; b) Longitudinal 0.7, 1.1, 2.5; c) Vertical 1.1, 1.3, 3.7. Conclusions: With the guidance of online KV-CBCT, set-up errors could be reduced significantly for patients with prostate cancer receiving IMRT. The margin required after online CBCT correction for the patients enrolled in the study would be appoximatively 3-4 mm. (authors)

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

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

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.

Online versus offline corrections: opposition or evolution? A comparison of two electronic portal imaging approaches for locally advanced prostate cancer

International Nuclear Information System (INIS)

Middleton, Mark; Medwell, Steve; Wong, Jacky; Lynton-Moll, Mary; Rolfo, Aldo; See Andrew; Joon, Michael Lim

2006-01-01

Given the onset of dose escalation and increased planning target volume (PTV) conformity, the requirement of accurate field placement has also increased. This study compares and contrasts a combination offline/online electronic portal imaging (EPI) device correction with a complete online correction protocol and assesses their relative effectiveness in managing set-up error. Field placement data was collected on patients receiving radical radiotherapy to the prostate. Ten patients were on an initial combination offline/online correction protocol, followed by another 10 patients on a complete online correction protocol. Analysis of 1480 portal images from 20 patients was carried out, illustrating that a combination offline/online approach can be very effective in dealing with the systematic component of set-up error, but it is only when a complete online correction protocol is employed that both systematic and random set-up errors can be managed. Now, EPI protocols have evolved considerably and online corrections are a highly effective tool in the quest for more accurate field placement. This study discusses the clinical workload impact issues that need to be addressed in order for an online correction protocol to be employed, and addresses many of the practical issues that need to be resolved. Management of set-up error is paramount when seeking to dose escalate and only an online correction protocol can manage both components of set-up error. Both systematic and random errors are important and can be effectively and efficiently managed

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

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

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.

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.

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.

Analysis of error patterns in clinical radiotherapy

International Nuclear Information System (INIS)

Macklis, Roger; Meier, Tim; Barrett, Patricia; Weinhous, Martin

1996-01-01

Purpose: Until very recently, prescription errors and adverse treatment events have rarely been studied or reported systematically in oncology. We wished to understand the spectrum and severity of radiotherapy errors that take place on a day-to-day basis in a high-volume academic practice and to understand the resource needs and quality assurance challenges placed on a department by rapid upswings in contract-based clinical volumes requiring additional operating hours, procedures, and personnel. The goal was to define clinical benchmarks for operating safety and to detect error-prone treatment processes that might function as 'early warning' signs. Methods: A multi-tiered prospective and retrospective system for clinical error detection and classification was developed, with formal analysis of the antecedents and consequences of all deviations from prescribed treatment delivery, no matter how trivial. A department-wide record-and-verify system was operational during this period and was used as one method of treatment verification and error detection. Brachytherapy discrepancies were analyzed separately. Results: During the analysis year, over 2000 patients were treated with over 93,000 individual fields. A total of 59 errors affecting a total of 170 individual treated fields were reported or detected during this period. After review, all of these errors were classified as Level 1 (minor discrepancy with essentially no potential for negative clinical implications). This total treatment delivery error rate (170/93, 332 or 0.18%) is significantly better than corresponding error rates reported for other hospital and oncology treatment services, perhaps reflecting the relatively sophisticated error avoidance and detection procedures used in modern clinical radiation oncology. Error rates were independent of linac model and manufacturer, time of day (normal operating hours versus late evening or early morning) or clinical machine volumes. There was some relationship to

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.

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].

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.

Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

Science.gov (United States)

McIntosh, Dawn

2006-01-01

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

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.

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.

High cortisol awakening response is associated with impaired error monitoring and decreased post-error adjustment.

Science.gov (United States)

Zhang, Liang; Duan, Hongxia; Qin, Shaozheng; Yuan, Yiran; Buchanan, Tony W; Zhang, Kan; Wu, Jianhui

2015-01-01

The cortisol awakening response (CAR), a rapid increase in cortisol levels following morning awakening, is an important aspect of hypothalamic-pituitary-adrenocortical axis activity. Alterations in the CAR have been linked to a variety of mental disorders and cognitive function. However, little is known regarding the relationship between the CAR and error processing, a phenomenon that is vital for cognitive control and behavioral adaptation. Using high-temporal resolution measures of event-related potentials (ERPs) combined with behavioral assessment of error processing, we investigated whether and how the CAR is associated with two key components of error processing: error detection and subsequent behavioral adjustment. Sixty university students performed a Go/No-go task while their ERPs were recorded. Saliva samples were collected at 0, 15, 30 and 60 min after awakening on the two consecutive days following ERP data collection. The results showed that a higher CAR was associated with slowed latency of the error-related negativity (ERN) and a higher post-error miss rate. The CAR was not associated with other behavioral measures such as the false alarm rate and the post-correct miss rate. These findings suggest that high CAR is a biological factor linked to impairments of multiple steps of error processing in healthy populations, specifically, the automatic detection of error and post-error behavioral adjustment. A common underlying neural mechanism of physiological and cognitive control may be crucial for engaging in both CAR and error processing.

Impact of the frequency of online verifications on the patient set-up accuracy and set-up margins

International Nuclear Information System (INIS)

Rudat, Volker; Hammoud, Mohamed; Pillay, Yogin; Alaradi, Abdul Aziz; Mohamed, Adel; Altuwaijri, Saleh

2011-01-01

The purpose of the study was to evaluate the patient set-up error of different anatomical sites, to estimate the effect of different frequencies of online verifications on the patient set-up accuracy, and to calculate margins to accommodate for the patient set-up error (ICRU set-up margin, SM). Alignment data of 148 patients treated with inversed planned intensity modulated radiotherapy (IMRT) or three-dimensional conformal radiotherapy (3D-CRT) of the head and neck (n = 31), chest (n = 72), abdomen (n = 15), and pelvis (n = 30) were evaluated. The patient set-up accuracy was assessed using orthogonal megavoltage electronic portal images of 2328 fractions of 173 planning target volumes (PTV). In 25 patients, two PTVs were analyzed where the PTVs were located in different anatomical sites and treated in two different radiotherapy courses. The patient set-up error and the corresponding SM were retrospectively determined assuming no online verification, online verification once a week and online verification every other day. The SM could be effectively reduced with increasing frequency of online verifications. However, a significant frequency of relevant set-up errors remained even after online verification every other day. For example, residual set-up errors larger than 5 mm were observed on average in 18% to 27% of all fractions of patients treated in the chest, abdomen and pelvis, and in 10% of fractions of patients treated in the head and neck after online verification every other day. In patients where high set-up accuracy is desired, daily online verification is highly recommended

Climbing fibers predict movement kinematics and performance errors.

Science.gov (United States)

Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

2017-09-01

Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each

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...

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).

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.

Probability of undetected error after decoding for a concatenated coding scheme

Science.gov (United States)

Costello, D. J., Jr.; Lin, S.

1984-01-01

A concatenated coding scheme for error control in data communications is analyzed. In this scheme, the inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. Probability of undetected error is derived and bounded. A particular example, proposed for NASA telecommand system is analyzed.

Passive quantum error correction of linear optics networks through error averaging

Science.gov (United States)

Marshman, Ryan J.; Lund, Austin P.; Rohde, Peter P.; Ralph, Timothy C.

2018-02-01

We propose and investigate a method of error detection and noise correction for bosonic linear networks using a method of unitary averaging. The proposed error averaging does not rely on ancillary photons or control and feedforward correction circuits, remaining entirely passive in its operation. We construct a general mathematical framework for this technique and then give a series of proof of principle examples including numerical analysis. Two methods for the construction of averaging are then compared to determine the most effective manner of implementation and probe the related error thresholds. Finally we discuss some of the potential uses of this scheme.

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)

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)

Repeat-aware modeling and correction of short read errors.

Science.gov (United States)

Yang, Xiao; Aluru, Srinivas; Dorman, Karin S

2011-02-15

High-throughput short read sequencing is revolutionizing genomics and systems biology research by enabling cost-effective deep coverage sequencing of genomes and transcriptomes. Error detection and correction are crucial to many short read sequencing applications including de novo genome sequencing, genome resequencing, and digital gene expression analysis. Short read error detection is typically carried out by counting the observed frequencies of kmers in reads and validating those with frequencies exceeding a threshold. In case of genomes with high repeat content, an erroneous kmer may be frequently observed if it has few nucleotide differences with valid kmers with multiple occurrences in the genome. Error detection and correction were mostly applied to genomes with low repeat content and this remains a challenging problem for genomes with high repeat content. We develop a statistical model and a computational method for error detection and correction in the presence of genomic repeats. We propose a method to infer genomic frequencies of kmers from their observed frequencies by analyzing the misread relationships among observed kmers. We also propose a method to estimate the threshold useful for validating kmers whose estimated genomic frequency exceeds the threshold. We demonstrate that superior error detection is achieved using these methods. Furthermore, we break away from the common assumption of uniformly distributed errors within a read, and provide a framework to model position-dependent error occurrence frequencies common to many short read platforms. Lastly, we achieve better error correction in genomes with high repeat content. The software is implemented in C++ and is freely available under GNU GPL3 license and Boost Software V1.0 license at "http://aluru-sun.ece.iastate.edu/doku.php?id = redeem". We introduce a statistical framework to model sequencing errors in next-generation reads, which led to promising results in detecting and correcting errors

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.

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...

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

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.

Impact of the frequency of online verifications on the patient set-up accuracy and set-up margins

Directory of Open Access Journals (Sweden)

Mohamed Adel

2011-08-01

Full Text Available Abstract Purpose The purpose of the study was to evaluate the patient set-up error of different anatomical sites, to estimate the effect of different frequencies of online verifications on the patient set-up accuracy, and to calculate margins to accommodate for the patient set-up error (ICRU set-up margin, SM. Methods and materials Alignment data of 148 patients treated with inversed planned intensity modulated radiotherapy (IMRT or three-dimensional conformal radiotherapy (3D-CRT of the head and neck (n = 31, chest (n = 72, abdomen (n = 15, and pelvis (n = 30 were evaluated. The patient set-up accuracy was assessed using orthogonal megavoltage electronic portal images of 2328 fractions of 173 planning target volumes (PTV. In 25 patients, two PTVs were analyzed where the PTVs were located in different anatomical sites and treated in two different radiotherapy courses. The patient set-up error and the corresponding SM were retrospectively determined assuming no online verification, online verification once a week and online verification every other day. Results The SM could be effectively reduced with increasing frequency of online verifications. However, a significant frequency of relevant set-up errors remained even after online verification every other day. For example, residual set-up errors larger than 5 mm were observed on average in 18% to 27% of all fractions of patients treated in the chest, abdomen and pelvis, and in 10% of fractions of patients treated in the head and neck after online verification every other day. Conclusion In patients where high set-up accuracy is desired, daily online verification is highly recommended.

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

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.

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…

A hybrid strategy of offline adaptive planning and online image guidance for prostate cancer radiotherapy

International Nuclear Information System (INIS)

Lei Yu; Wu Qiuwen

2010-01-01

Offline adaptive radiotherapy (ART) has been used to effectively correct and compensate for prostate motion and reduce the required margin. The efficacy depends on the characteristics of the patient setup error and interfraction motion through the whole treatment; specifically, systematic errors are corrected and random errors are compensated for through the margins. In online image-guided radiation therapy (IGRT) of prostate cancer, the translational setup error and inter-fractional prostate motion are corrected through pre-treatment imaging and couch correction at each fraction. However, the rotation and deformation of the target are not corrected and only accounted for with margins in treatment planning. The purpose of this study was to investigate whether the offline ART strategy is necessary for an online IGRT protocol and to evaluate the benefit of the hybrid strategy. First, to investigate the rationale of the hybrid strategy, 592 cone-beam-computed tomography (CBCT) images taken before and after each fraction for an online IGRT protocol from 16 patients were analyzed. Specifically, the characteristics of prostate rotation were analyzed. It was found that there exist systematic inter-fractional prostate rotations, and they are patient specific. These rotations, if not corrected, are persistent through the treatment fraction, and rotations detected in early fractions are representative of those in later fractions. These findings suggest that the offline adaptive replanning strategy is beneficial to the online IGRT protocol with further margin reductions. Second, to quantitatively evaluate the benefit of the hybrid strategy, 412 repeated helical CT scans from 25 patients during the course of treatment were included in the replanning study. Both low-risk patients (LRP, clinical target volume, CTV = prostate) and intermediate-risk patients (IRP, CTV = prostate + seminal vesicles) were included in the simulation. The contours of prostate and seminal vesicles were

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.

A Compound Detection System Based on Ultrasonic Flow Rate and Concentration

OpenAIRE

Qing-Hui WANG; Fang MU; Li-Feng WEI

2014-01-01

This paper proposes a new detection system for monitoring gas concentration and flow rate. Velocity difference of ultrasonic wave in bi-directional propagation in measured gas is recorded and utilized for computing the online gas concentration and flow rate. Meanwhile, the temperature compensation, return signal processing and error analysis algorithms are applied to improve the accuracy. The experimental results show that, compared with the single sensor measurement of gas flow rate or conce...

Error rate performance of narrowband multilevel CPFSK signals

Science.gov (United States)

Ekanayake, N.; Fonseka, K. J. P.

1987-04-01

The paper presents a relatively simple method for analyzing the effect of IF filtering on the performance of multilevel FM signals. Using this method, the error rate performance of narrowband FM signals is analyzed for three different detection techniques, namely limiter-discriminator detection, differential detection and coherent detection followed by differential decoding. The symbol error probabilities are computed for a Gaussian IF filter and a second-order Butterworth IF filter. It is shown that coherent detection and differential decoding yields better performance than limiter-discriminator detection and differential detection, whereas two noncoherent detectors yield approximately identical performance.

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...

A Compound Detection System Based on Ultrasonic Flow Rate and Concentration

Directory of Open Access Journals (Sweden)

Qing-Hui WANG

2014-02-01

Full Text Available This paper proposes a new detection system for monitoring gas concentration and flow rate. Velocity difference of ultrasonic wave in bi-directional propagation in measured gas is recorded and utilized for computing the online gas concentration and flow rate. Meanwhile, the temperature compensation, return signal processing and error analysis algorithms are applied to improve the accuracy. The experimental results show that, compared with the single sensor measurement of gas flow rate or concentration, the proposed detection system with lower cost and higher accuracy can be applied in the occasion which needs simultaneous monitoring of gas concentration and flow rate.

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.

Corpus-Based Websites to Promote Learner Autonomy in Correcting Writing Collocation Errors

Directory of Open Access Journals (Sweden)

Pham Thuy Dung

2016-12-01

Full Text Available The recent yet powerful emergence of E-learning and using online resources in learning EFL (English as a Foreign Language has helped promote learner autonomy in language acquisition including self-correcting their mistakes. This pilot study despite conducted on a modest sample of 25 second year students majoring in Business English at Hanoi Foreign Trade University is an initial attempt to investigate the feasibility of using corpus-based websites to promote learner autonomy in correcting collocation errors in EFL writing. The data is collected using a pre-questionnaire and a post-interview aiming to find out the participants’ change in belief and attitude toward learner autonomy in collocation errors in writing, the extent of their success in using the corpus-based websites to self-correct the errors and the change in their confidence in self-correcting the errors using the websites. The findings show that a significant majority of students have shifted their belief and attitude toward a more autonomous mode of learning, enjoyed a fair success of using the websites to self-correct the errors and become more confident. The study also yields an implication that a face-to-face training of how to use these online tools is vital to the later confidence and success of the learners

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.

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,

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,

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.

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.

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.

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

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.

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.

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.

CDF run II run control and online monitor

International Nuclear Information System (INIS)

Arisawa, T.; Ikado, K.; Badgett, W.; Chlebana, F.; Maeshima, K.; McCrory, E.; Meyer, A.; Patrick, J.; Wenzel, H.; Stadie, H.; Wagner, W.; Veramendi, G.

2001-01-01

The authors discuss the CDF Run II Run Control and online event monitoring system. Run Control is the top level application that controls the data acquisition activities across 150 front end VME crates and related service processes. Run Control is a real-time multi-threaded application implemented in Java with flexible state machines, using JDBC database connections to configure clients, and including a user friendly and powerful graphical user interface. The CDF online event monitoring system consists of several parts: the event monitoring programs, the display to browse their results, the server program which communicates with the display via socket connections, the error receiver which displays error messages and communicates with Run Control, and the state manager which monitors the state of the monitor programs

Redundant measurements for controlling errors

International Nuclear Information System (INIS)

Ehinger, M.H.; Crawford, J.M.; Madeen, M.L.

1979-07-01

Current federal regulations for nuclear materials control require consideration of operating data as part of the quality control program and limits of error propagation. Recent work at the BNFP has revealed that operating data are subject to a number of measurement problems which are very difficult to detect and even more difficult to correct in a timely manner. Thus error estimates based on operational data reflect those problems. During the FY 1978 and FY 1979 R and D demonstration runs at the BNFP, redundant measurement techniques were shown to be effective in detecting these problems to allow corrective action. The net effect is a reduction in measurement errors and a significant increase in measurement sensitivity. Results show that normal operation process control measurements, in conjunction with routine accountability measurements, are sensitive problem indicators when incorporated in a redundant measurement program

Online measurement of bead geometry in GMAW-based additive manufacturing using passive vision

International Nuclear Information System (INIS)

Xiong, Jun; Zhang, Guangjun

2013-01-01

Additive manufacturing based on gas metal arc welding is an advanced technique for depositing fully dense components with low cost. Despite this fact, techniques to achieve accurate control and automation of the process have not yet been perfectly developed. The online measurement of the deposited bead geometry is a key problem for reliable control. In this work a passive vision-sensing system, comprising two cameras and composite filtering techniques, was proposed for real-time detection of the bead height and width through deposition of thin walls. The nozzle to the top surface distance was monitored for eliminating accumulated height errors during the multi-layer deposition process. Various image processing algorithms were applied and discussed for extracting feature parameters. A calibration procedure was presented for the monitoring system. Validation experiments confirmed the effectiveness of the online measurement system for bead geometry in layered additive manufacturing. (paper)

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.

Acoustic Evidence for Phonologically Mismatched Speech Errors

Science.gov (United States)

Gormley, Andrea

2015-01-01

Speech errors are generally said to accommodate to their new phonological context. This accommodation has been validated by several transcription studies. The transcription methodology is not the best choice for detecting errors at this level, however, as this type of error can be difficult to perceive. This paper presents an acoustic analysis of…

Characteristics of medication errors with parenteral cytotoxic drugs

OpenAIRE

Fyhr, A; Akselsson, R

2012-01-01

Errors involving cytotoxic drugs have the potential of being fatal and should therefore be prevented. The objective of this article is to identify the characteristics of medication errors involving parenteral cytotoxic drugs in Sweden. A total of 60 cases reported to the national error reporting systems from 1996 to 2008 were reviewed. Classification was made to identify cytotoxic drugs involved, type of error, where the error occurred, error detection mechanism, and consequences for the pati...

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.

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

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

Fast online generalized multiscale finite element method using constraint energy minimization

Science.gov (United States)

Chung, Eric T.; Efendiev, Yalchin; Leung, Wing Tat

2018-02-01

Local multiscale methods often construct multiscale basis functions in the offline stage without taking into account input parameters, such as source terms, boundary conditions, and so on. These basis functions are then used in the online stage with a specific input parameter to solve the global problem at a reduced computational cost. Recently, online approaches have been introduced, where multiscale basis functions are adaptively constructed in some regions to reduce the error significantly. In multiscale methods, it is desired to have only 1-2 iterations to reduce the error to a desired threshold. Using Generalized Multiscale Finite Element Framework [10], it was shown that by choosing sufficient number of offline basis functions, the error reduction can be made independent of physical parameters, such as scales and contrast. In this paper, our goal is to improve this. Using our recently proposed approach [4] and special online basis construction in oversampled regions, we show that the error reduction can be made sufficiently large by appropriately selecting oversampling regions. Our numerical results show that one can achieve a three order of magnitude error reduction, which is better than our previous methods. We also develop an adaptive algorithm and enrich in selected regions with large residuals. In our adaptive method, we show that the convergence rate can be determined by a user-defined parameter and we confirm this by numerical simulations. The analysis of the method is presented.

Communication Error Management in Law Enforcement Interactions : a receiver's perspective

NARCIS (Netherlands)

Oostinga, Miriam; Giebels, Ellen; Taylor, Paul Jonathon

2018-01-01

Two experiments explore the effect of law enforcement officers’ communication errors and their response strategies on a suspect’s trust in the officer; established rapport and hostility; and, the amount and quality of information shared. Students were questioned online by an exam board member about

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.

Assessment of a daily online implanted fiducial marker-guided prostate radiotherapy process.

Science.gov (United States)

Greer, P B; Dahl, K; Ebert, M A; White, M; Wratten, C; Ostwald, P; Pichler, P; Denham, J W

2008-10-01

The aims of this study were to investigate whether intrafraction prostate motion can affect the accuracy of online prostate positioning using implanted fiducial markers and to determine the effect of prostate rotations on the accuracy of the software-predicted set-up correction shifts. Eleven patients were treated with implanted prostate fiducial markers and online set-up corrections. Orthogonal electronic portal images were acquired to determine couch shifts before treatment. Verification images were also acquired during treatment to assess whether intrafraction motion had occurred. A limitation of the online image registration software is that it does not allow for in-plane prostate rotations (evident on lateral portal images) when aligning marker positions. The accuracy of couch shifts was assessed by repeating the registration measurements with separate software that incorporates full in-plane prostate rotations. Additional treatment time required for online positioning was also measured. For the patient group, the overall postalignment systematic prostate errors were less than 1.5 mm (1 standard deviation) in all directions (range 0.2-3.9 mm). The random prostate errors ranged from 0.8 to 3.3 mm (1 standard deviation). One patient exhibited intrafraction prostate motion, resulting in a postalignment prostate set-up error of more than 10 mm for one fraction. In 14 of 35 fractions, the postalignment prostate set-up error was greater than 5 mm in the anterior-posterior direction for this patient. Maximum prostate rotations measured from the lateral images varied from 2 degrees to 20 degrees for the patients. The differences between set-up shifts determined by the online software without in-plane rotations to align markers, and with rotations applied, was less than 1 mm (root mean square), with a maximum difference of 4.1 mm. Intrafraction prostate motion was found to reduce the effectiveness of the online set-up for one of the patients. A larger study is required

Daily online bony correction is required for prostate patients without fiducial markers or soft-tissue imaging.

Science.gov (United States)

Johnston, M L; Vial, P; Wiltshire, K L; Bell, L J; Blome, S; Kerestes, Z; Morgan, G W; O'Driscoll, D; Shakespeare, T P; Eade, T N

2011-09-01

To compare online position verification strategies with offline correction protocols for patients undergoing definitive prostate radiotherapy. We analysed 50 patients with implanted fiducial markers undergoing curative prostate radiation treatment, all of whom underwent daily kilovoltage imaging using an on-board imager. For each treatment, patients were set-up initially with skin tattoos and in-room lasers. Orthogonal on-board imager images were acquired and the couch shift to match both bony anatomy and the fiducial markers recorded. The set-up error using skin tattoos and offline bone correction was compared with online bone correction. The fiducial markers were used as the reference. Data from 1923 fractions were analysed. The systematic error was ≤1 mm for all protocols. The average random error was 2-3mm for online bony correction and 3-5mm for skin tattoos or offline-bone. Online-bone showed a significant improvement compared with offline-bone in the number of patients with >5mm set-up errors for >10% (P20% (Pmarkers or daily soft-tissue imaging. Copyright © 2011 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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.

Effect of video decoder errors on video interpretability

Science.gov (United States)

Young, Darrell L.

2014-06-01

The advancement in video compression technology can result in more sensitivity to bit errors. Bit errors can propagate causing sustained loss of interpretability. In the worst case, the decoder "freezes" until it can re-synchronize with the stream. Detection of artifacts enables downstream processes to avoid corrupted frames. A simple template approach to detect block stripes and a more advanced cascade approach to detect compression artifacts was shown to correlate to the presence of artifacts and decoder messages.

Fractional Order Differentiation by Integration and Error Analysis in Noisy Environment

KAUST Repository

Liu, Dayan; Gibaru, Olivier; Perruquetti, Wilfrid; Laleg-Kirati, Taous-Meriem

2015-01-01

respectively. Exact and simple formulae for these differentiators are given by integral expressions. Hence, they can be used for both continuous-time and discrete-time models in on-line or off-line applications. Secondly, some error bounds are provided

Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

Science.gov (United States)

Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

2017-12-01

In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

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.

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

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

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

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.

Comparison of prostate set-up accuracy and margins with off-line bony anatomy corrections and online implanted fiducial-based corrections.

Science.gov (United States)

Greer, P B; Dahl, K; Ebert, M A; Wratten, C; White, M; Denham, J W

2008-10-01

The aim of the study was to determine prostate set-up accuracy and set-up margins with off-line bony anatomy-based imaging protocols, compared with online implanted fiducial marker-based imaging with daily corrections. Eleven patients were treated with implanted prostate fiducial markers and online set-up corrections. Pretreatment orthogonal electronic portal images were acquired to determine couch shifts and verification images were acquired during treatment to measure residual set-up error. The prostate set-up errors that would result from skin marker set-up, off-line bony anatomy-based protocols and online fiducial marker-based corrections were determined. Set-up margins were calculated for each set-up technique using the percentage of encompassed isocentres and a margin recipe. The prostate systematic set-up errors in the medial-lateral, superior-inferior and anterior-posterior directions for skin marker set-up were 2.2, 3.6 and 4.5 mm (1 standard deviation). For our bony anatomy-based off-line protocol the prostate systematic set-up errors were 1.6, 2.5 and 4.4 mm. For the online fiducial based set-up the results were 0.5, 1.4 and 1.4 mm. A prostate systematic error of 10.2 mm was uncorrected by the off-line bone protocol in one patient. Set-up margins calculated to encompass 98% of prostate set-up shifts were 11-14 mm with bone off-line set-up and 4-7 mm with online fiducial markers. Margins from the van Herk margin recipe were generally 1-2 mm smaller. Bony anatomy-based set-up protocols improve the group prostate set-up error compared with skin marks; however, large prostate systematic errors can remain undetected or systematic errors increased for individual patients. The margin required for set-up errors was found to be 10-15 mm unless implanted fiducial markers are available for treatment guidance.

Residual-driven online generalized multiscale finite element methods

KAUST Repository

Chung, Eric T.; Efendiev, Yalchin R.; Leung, Wing Tat

2015-01-01

In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.

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...

Human errors related to maintenance and modifications

International Nuclear Information System (INIS)

Laakso, K.; Pyy, P.; Reiman, L.

1998-01-01

The focus in human reliability analysis (HRA) relating to nuclear power plants has traditionally been on human performance in disturbance conditions. On the other hand, some studies and incidents have shown that also maintenance errors, which have taken place earlier in plant history, may have an impact on the severity of a disturbance, e.g. if they disable safety related equipment. Especially common cause and other dependent failures of safety systems may significantly contribute to the core damage risk. The first aim of the study was to identify and give examples of multiple human errors which have penetrated the various error detection and inspection processes of plant safety barriers. Another objective was to generate numerical safety indicators to describe and forecast the effectiveness of maintenance. A more general objective was to identify needs for further development of maintenance quality and planning. In the first phase of this operational experience feedback analysis, human errors recognisable in connection with maintenance were looked for by reviewing about 4400 failure and repair reports and some special reports which cover two nuclear power plant units on the same site during 1992-94. A special effort was made to study dependent human errors since they are generally the most serious ones. An in-depth root cause analysis was made for 14 dependent errors by interviewing plant maintenance foremen and by thoroughly analysing the errors. A more simple treatment was given to maintenance-related single errors. The results were shown as a distribution of errors among operating states i.a. as regards the following matters: in what operational state the errors were committed and detected; in what operational and working condition the errors were detected, and what component and error type they were related to. These results were presented separately for single and dependent maintenance-related errors. As regards dependent errors, observations were also made

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.

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.

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.

Comprehensive Use of Curvature for Robust and Accurate Online Surface Reconstruction.

Science.gov (United States)

Lefloch, Damien; Kluge, Markus; Sarbolandi, Hamed; Weyrich, Tim; Kolb, Andreas

2017-12-01

Interactive real-time scene acquisition from hand-held depth cameras has recently developed much momentum, enabling applications in ad-hoc object acquisition, augmented reality and other fields. A key challenge to online reconstruction remains error accumulation in the reconstructed camera trajectory, due to drift-inducing instabilities in the range scan alignments of the underlying iterative-closest-point (ICP) algorithm. Various strategies have been proposed to mitigate that drift, including SIFT-based pre-alignment, color-based weighting of ICP pairs, stronger weighting of edge features, and so on. In our work, we focus on surface curvature as a feature that is detectable on range scans alone and hence does not depend on accurate multi-sensor alignment. In contrast to previous work that took curvature into consideration, however, we treat curvature as an independent quantity that we consistently incorporate into every stage of the real-time reconstruction pipeline, including densely curvature-weighted ICP, range image fusion, local surface reconstruction, and rendering. Using multiple benchmark sequences, and in direct comparison to other state-of-the-art online acquisition systems, we show that our approach significantly reduces drift, both when analyzing individual pipeline stages in isolation, as well as seen across the online reconstruction pipeline as a whole.

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.

Technology and medication errors: impact in nursing homes.

Science.gov (United States)

Baril, Chantal; Gascon, Viviane; St-Pierre, Liette; Lagacé, Denis

2014-01-01

The purpose of this paper is to study a medication distribution technology's (MDT) impact on medication errors reported in public nursing homes in Québec Province. The work was carried out in six nursing homes (800 patients). Medication error data were collected from nursing staff through a voluntary reporting process before and after MDT was implemented. The errors were analysed using: totals errors; medication error type; severity and patient consequences. A statistical analysis verified whether there was a significant difference between the variables before and after introducing MDT. The results show that the MDT detected medication errors. The authors' analysis also indicates that errors are detected more rapidly resulting in less severe consequences for patients. MDT is a step towards safer and more efficient medication processes. Our findings should convince healthcare administrators to implement technology such as electronic prescriber or bar code medication administration systems to improve medication processes and to provide better healthcare to patients. Few studies have been carried out in long-term healthcare facilities such as nursing homes. The authors' study extends what is known about MDT's impact on medication errors in nursing homes.

The clinical feasibility and effect of online cone beam computer tomography-guided intensity-modulated radiotherapy for nasopharyngeal cancer

International Nuclear Information System (INIS)

Wang Jin; Bai Sen; Chen Nianyong; Xu Feng; Jiang Xiaoqin; Li Yan; Xu Qingfeng; Shen Yali; Zhang Hong; Gong Youling; Zhong Renming; Jiang Qingfeng

2009-01-01

Background and purpose: Online adaptive correction in image-guided intensity-modulated radiotherapy appeared to be a promising approach for precision radiation treatment in head and neck tumors. This protocol was designed to evaluate the clinical feasibility and effect of online cone beam computed tomography (CBCT) guidance in IMRT of nasopharyngeal cancer (NPC). Methods and materials: The Elekta Synergy system, which integrates an X-ray volumetric imager (XVI), was used to deliver radiation treatment for 22 cases of NPC. The acquired CBCT was registered to the planning CT for online and offline analysis. The systematic and random setup errors, as well as planning target volume (PTV) margin, were calculated at different correction threshold levels. The impact of online setup correction on dosimetry was evaluated by simulation of pre-correction errors. Results: The correction-of-setup-errors frequencies for 1, 2 and 3 mm thresholds were 41.3-53.9%, 12.7-21.2% and 6.3-10.3%, respectively. Online correction was effective at the 2 mm threshold level for all three axes. The pre-correction systematic errors for the whole group ranged 1.1-1.3 mm, and the random errors were also 1.1-1.3 mm. After online correction, the systematic and random errors ranged 0.4-0.5 mm and 0.7-0.8 mm, respectively, in the three directions. The PTV margins for the pre-correction, pretreatment and post-treatment positions were 3.5-4.2 mm, 1.6-1.8 mm and 2.5-3.2 mm, respectively, in three directions. Analysis of hypothetical dosimetric change due to a translational isocenter shift of 3 mm showed that if no correction was applied, the mean maximum dose to both the brain stem and spinal cord would be increased by 10 Gy, the mean dose to the left and right parotids would be increased by 7.8 and 8.5 Gy, respectively, and the dose to target volumes would be decreased: 4 Gy for 95% GTV and 5.6 Gy for 95% CTV 60. Conclusions: CBCT-based online correction increased the accuracy of IMRT for NPC and

Feasibility study of image guided radiotherapy for lung tumor using online and offline cone-beam CT setup verification

International Nuclear Information System (INIS)

Li Hongsheng; Li Baosheng; Lu Jie; Yin Yong; Yu Ningsha; Chen Yiru

2009-01-01

Objective: To investigate the feasibility of online and offline cone-beam CT(CBCT) guided radiotherapy for lung cancer. Methods: Fourteen patients with lung tumor treated by three-dimensional conformal radiotherapy were investigated. Online kV CBCT scan, image registration and setup correction were performed before and immediately after radiotherapy. CBCT online-guided correction data were used to calculate the population-based CTV-PTV margins under the condition of non-correction and correction in every fraction respectively. The numbers of initial images and the population-based CTV-PTV margins after the offline compensation of the system setup error were evaluated with the permission of 0.5 mm and 1.5 mm maximal residue error, respectively. Results: Under the condition of non-correction, the required margins for total error were 5.7 mm, 8.0 mm and 7.8 mm in the left-right (x axis), cranio-caudal (y axis) and anterior-posterior(z axis) directions, respectively. When the tumor was corrected in every fraction, the required margins for intra-fraction error were 2.4 mm, 2.4 mm and 2.3 mm in x,y and z axes, respectively. To correct the systematic setup error, 9 sets of CBCT images for 3.3 mm, 3.7 mm and 3.6 mm PTV margins, and 7 sets of CBCT images for 3.9 mm, 4.3 mm and 4.3 mm PTV margins in x,y and z axes were necessary when 0.5 mm and 1.5 mm maximal residue error were permitted respectively. Conclusions: Both of the online CBCT correction and the offline adaptive correction can markedly reduce the impact of setup error and reduce the required PTV margins accordingly. It is feasible to deliver the online and offline image guided radiation for patients with lung tumor. (authors)

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.

Evaluation of rotational set-up errors in patients with thoracic neoplasms

International Nuclear Information System (INIS)

Wang Yanyang; Fu Xiaolong; Xia Bing; Fan Min; Yang Huanjun; Ren Jun; Xu Zhiyong; Jiang Guoliang

2010-01-01

Objective: To assess the rotational set-up errors in patients with thoracic neoplasms. Methods: 224 kilovoltage cone-beam computed tomography (KVCBCT) scans from 20 thoracic tumor patients were evaluated retrospectively. All these patients were involved in the research of 'Evaluation of the residual set-up error for online kilovoltage cone-beam CT guided thoracic tumor radiation'. Rotational set-up errors, including pitch, roll and yaw, were calculated by 'aligning the KVCBCT with the planning CT, using the semi-automatic alignment method. Results: The average rotational set-up errors were -0.28 degree ±1.52 degree, 0.21 degree ± 0.91 degree and 0.27 degree ± 0.78 degree in the left-fight, superior-inferior and anterior-posterior axis, respectively. The maximal rotational errors of pitch, roll and yaw were 3.5 degree, 2.7 degree and 2.2 degree, respectively. After correction for translational set-up errors, no statistically significant changes in rotational error were observed. Conclusions: The rotational set-up errors in patients with thoracic neoplasms were all small in magnitude. Rotational errors may not change after the correction for translational set-up errors alone, which should be evaluated in a larger sample future. (authors)

SU-C-BRA-03: An Automated and Quick Contour Errordetection for Auto Segmentation in Online Adaptive Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Zhang, J; Ates, O; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

2016-06-15

Purpose: To develop a tool that can quickly and automatically assess contour quality generated from auto segmentation during online adaptive replanning. Methods: Due to the strict time requirement of online replanning and lack of ‘ground truth’ contours in daily images, our method starts with assessing image registration accuracy focusing on the surface of the organ in question. Several metrics tightly related to registration accuracy including Jacobian maps, contours shell deformation, and voxel-based root mean square (RMS) analysis were computed. To identify correct contours, additional metrics and an adaptive decision tree are introduced. To approve in principle, tests were performed with CT sets, planned and daily CTs acquired using a CT-on-rails during routine CT-guided RT delivery for 20 prostate cancer patients. The contours generated on daily CTs using an auto-segmentation tool (ADMIRE, Elekta, MIM) based on deformable image registration of the planning CT and daily CT were tested. Results: The deformed contours of 20 patients with total of 60 structures were manually checked as baselines. The incorrect rate of total contours is 49%. To evaluate the quality of local deformation, the Jacobian determinant (1.047±0.045) on contours has been analyzed. In an analysis of rectum contour shell deformed, the higher rate (0.41) of error contours detection was obtained compared to 0.32 with manual check. All automated detections took less than 5 seconds. Conclusion: The proposed method can effectively detect contour errors in micro and macro scope by evaluating multiple deformable registration metrics in a parallel computing process. Future work will focus on improving practicability and optimizing calculation algorithms and metric selection.

SU-C-BRA-03: An Automated and Quick Contour Errordetection for Auto Segmentation in Online Adaptive Radiotherapy

International Nuclear Information System (INIS)

Zhang, J; Ates, O; Li, X

2016-01-01

Purpose: To develop a tool that can quickly and automatically assess contour quality generated from auto segmentation during online adaptive replanning. Methods: Due to the strict time requirement of online replanning and lack of ‘ground truth’ contours in daily images, our method starts with assessing image registration accuracy focusing on the surface of the organ in question. Several metrics tightly related to registration accuracy including Jacobian maps, contours shell deformation, and voxel-based root mean square (RMS) analysis were computed. To identify correct contours, additional metrics and an adaptive decision tree are introduced. To approve in principle, tests were performed with CT sets, planned and daily CTs acquired using a CT-on-rails during routine CT-guided RT delivery for 20 prostate cancer patients. The contours generated on daily CTs using an auto-segmentation tool (ADMIRE, Elekta, MIM) based on deformable image registration of the planning CT and daily CT were tested. Results: The deformed contours of 20 patients with total of 60 structures were manually checked as baselines. The incorrect rate of total contours is 49%. To evaluate the quality of local deformation, the Jacobian determinant (1.047±0.045) on contours has been analyzed. In an analysis of rectum contour shell deformed, the higher rate (0.41) of error contours detection was obtained compared to 0.32 with manual check. All automated detections took less than 5 seconds. Conclusion: The proposed method can effectively detect contour errors in micro and macro scope by evaluating multiple deformable registration metrics in a parallel computing process. Future work will focus on improving practicability and optimizing calculation algorithms and metric selection.

Distributed error and alarm processing in the CMS data acquisition system

Energy Technology Data Exchange (ETDEWEB)

Bauer, G.; et al.

2012-01-01

The error and alarm system for the data acquisition of the Compact Muon Solenoid (CMS) at CERN was successfully used for the physics runs at Large Hadron Collider (LHC) during first three years of activities. Error and alarm processing entails the notification, collection, storing and visualization of all exceptional conditions occurring in the highly distributed CMS online system using a uniform scheme. Alerts and reports are shown on-line by web application facilities that map them to graphical models of the system as defined by the user. A persistency service keeps a history of all exceptions occurred, allowing subsequent retrieval of user defined time windows of events for later playback or analysis. This paper describes the architecture and the technologies used and deals with operational aspects during the first years of LHC operation. In particular we focus on performance, stability, and integration with the CMS sub-detectors.

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.

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...

On-line learning in radial basis functions networks

OpenAIRE

Freeman, Jason; Saad, David

1997-01-01

An analytic investigation of the average case learning and generalization properties of Radial Basis Function Networks (RBFs) is presented, utilising on-line gradient descent as the learning rule. The analytic method employed allows both the calculation of generalization error and the examination of the internal dynamics of the network. The generalization error and internal dynamics are then used to examine the role of the learning rate and the specialization of the hidden units, which gives ...

SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes.

Science.gov (United States)

Antaki, Danny; Brandler, William M; Sebat, Jonathan

2018-05-15

Structural variation (SV) detection from short-read whole genome sequencing is error prone, presenting significant challenges for population or family-based studies of disease. Here, we describe SV2, a machine-learning algorithm for genotyping deletions and duplications from paired-end sequencing data. SV2 can rapidly integrate variant calls from multiple structural variant discovery algorithms into a unified call set with high genotyping accuracy and capability to detect de novo mutations. SV2 is freely available on GitHub (https://github.com/dantaki/SV2). jsebat@ucsd.edu. Supplementary data are available at Bioinformatics online.

Robot learning and error correction

Science.gov (United States)

Friedman, L.

1977-01-01

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Understanding human management of automation errors

Science.gov (United States)

McBride, Sara E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance. PMID:25383042

Online Classes See Cheating Go High-Tech

Science.gov (United States)

Young, Jeffrey R.

2012-01-01

Easy A's may be even easier to score these days, with the growing popularity of online courses. Tech-savvy students are finding ways to cheat that let them ace online courses with minimal effort, in ways that are difficult to detect. The issue of online cheating may rise in prominence, as more and more institutions embrace online courses, and as…

A method for online verification of adapted fields using an independent dose monitor

International Nuclear Information System (INIS)

Chang Jina; Norrlinger, Bernhard D.; Heaton, Robert K.; Jaffray, David A.; Cho, Young-Bin; Islam, Mohammad K.; Mahon, Robert

2013-01-01

Purpose: Clinical implementation of online adaptive radiotherapy requires generation of modified fields and a method of dosimetric verification in a short time. We present a method of treatment field modification to account for patient setup error, and an online method of verification using an independent monitoring system.Methods: The fields are modified by translating each multileaf collimator (MLC) defined aperture in the direction of the patient setup error, and magnifying to account for distance variation to the marked isocentre. A modified version of a previously reported online beam monitoring system, the integral quality monitoring (IQM) system, was investigated for validation of adapted fields. The system consists of a large area ion-chamber with a spatial gradient in electrode separation to provide a spatially sensitive signal for each beam segment, mounted below the MLC, and a calculation algorithm to predict the signal. IMRT plans of ten prostate patients have been modified in response to six randomly chosen setup errors in three orthogonal directions.Results: A total of approximately 49 beams for the modified fields were verified by the IQM system, of which 97% of measured IQM signal agree with the predicted value to within 2%.Conclusions: The modified IQM system was found to be suitable for online verification of adapted treatment fields

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.

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...

The generalization ability of online SVM classification based on Markov sampling.

Science.gov (United States)

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

Bit error rate analysis of free-space optical communication over general Malaga turbulence channels with pointing error

KAUST Repository

Alheadary, Wael Ghazy

2016-12-24

In this work, we present a bit error rate (BER) and achievable spectral efficiency (ASE) performance of a freespace optical (FSO) link with pointing errors based on intensity modulation/direct detection (IM/DD) and heterodyne detection over general Malaga turbulence channel. More specifically, we present exact closed-form expressions for adaptive and non-adaptive transmission. The closed form expressions are presented in terms of generalized power series of the Meijer\\'s G-function. Moreover, asymptotic closed form expressions are provided to validate our work. In addition, all the presented analytical results are illustrated using a selected set of numerical results.

[Diagnostic and organizational error in head injuries].

Science.gov (United States)

Zaba, Czesław; Zaba, Zbigniew; Swiderski, Paweł; Lorkiewicz-Muszyíska, Dorota

2009-01-01

The study aimed at presenting a case of a diagnostic and organizational error involving lack of detection of foreign body presence in the soft tissues of the head. Head radiograms in two projections clearly demonstrated foreign bodies that resembled in shape flattened bullets, which could not have been missed upon evaluation of the X-rays. On the other hand, description of the radiograms entered by the attending physicians to the patient's medical record indicated an absence of traumatic injuries or foreign bodies. In the opinion of the authors, the case in question involved a diagnostic error: the doctors failed to detect the presence of foreign bodies in the head. The organizational error involved the failure of radiogram evaluation performed by a radiologist.

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.

Understanding reliance on automation: effects of error type, error distribution, age and experience

Science.gov (United States)

Sanchez, Julian; Rogers, Wendy A.; Fisk, Arthur D.; Rovira, Ericka

2015-01-01

An obstacle detection task supported by “imperfect” automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation. PMID:25642142

VOLUMETRIC ERROR COMPENSATION IN FIVE-AXIS CNC MACHINING CENTER THROUGH KINEMATICS MODELING OF GEOMETRIC ERROR

Directory of Open Access Journals (Sweden)

Pooyan Vahidi Pashsaki

2016-06-01

Full Text Available Accuracy of a five-axis CNC machine tool is affected by a vast number of error sources. This paper investigates volumetric error modeling and its compensation to the basis for creation of new tool path for improvement of work pieces accuracy. The volumetric error model of a five-axis machine tool with the configuration RTTTR (tilting head B-axis and rotary table in work piece side A΄ was set up taking into consideration rigid body kinematics and homogeneous transformation matrix, in which 43 error components are included. Volumetric error comprises 43 error components that can separately reduce geometrical and dimensional accuracy of work pieces. The machining accuracy of work piece is guaranteed due to the position of the cutting tool center point (TCP relative to the work piece. The cutting tool is deviated from its ideal position relative to the work piece and machining error is experienced. For compensation process detection of the present tool path and analysis of the RTTTR five-axis CNC machine tools geometrical error, translating current position of component to compensated positions using the Kinematics error model, converting newly created component to new tool paths using the compensation algorithms and finally editing old G-codes using G-code generator algorithm have been employed.

Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

Energy Technology Data Exchange (ETDEWEB)

Valdetaro, Eduardo Damianik, E-mail: valdtar@eletronuclear.gov.br [ELETRONUCLEAR - ELETROBRAS, Angra dos Reis, RJ (Brazil). Angra 2 Operating Dept.; Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear; Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

2011-07-01

an on-line process to solve Data Reconciliation and Gross Error Detection problem. (author)

Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

International Nuclear Information System (INIS)

Valdetaro, Eduardo Damianik; Coordenacao dos Programas de Pos-Graduacao de Engenharia; Schirru, Roberto

2011-01-01

an on-line process to solve Data Reconciliation and Gross Error Detection problem. (author)

Comparison of prostate set-up accuracy and margins with off-line bony anatomy corrections and online implanted fiducial-based corrections

International Nuclear Information System (INIS)

Greer, P. B.; Dahl, K.; Ebert, M. A.; Wratten, C.; White, M.; Denham, K. W.

2008-01-01

Full text: The aim of the study was to determine prostate set-up accuracy and set-up margins with off-line bony anatomy-based imaging protocols, compared with online implanted fiducial marker-based imaging with daily corrections. Eleven patients were treated with implanted prostate fiducial markers and online set-up corrections. Pretreatment orthogonal electronic portal images were acquired to determine couch shifts and verification images were acquired during treatment to measure residual set-up error. The prostate set-up errors that would result from skin marker set-up, off-line bony anatomy-based protocols and online fiducial marker-based corrections were determined. Set-up margins were calculated for each set-up technique using the percentage of encompassed isocentres land a margin recipe. The prostate systematic set-up errors in the medial-lateral, superior-inferior and anterior-I posterior directions for skin marker set-up were 2.2, 3.6 and 4.5 mm (1 standard deviation). For our bony anatomy-I based off-line protocol the prostate systematic set-up errors were 1.6, 2.5 and 4.4 mm. For the online fiducial based set-up the results were 0.5, 1.4 and 1.4 mm. A prostate systematic error of 10.2 mm was uncorrected by the off-line bone protocol in one patient. Set-up margins calculated to encompass 98% of prostate set-up shifts were 111-14 mm with bone off-line set-up and 4-7 mm with online fiducial markers. Margins from the van Herk margin I recipe were generally 1-2 mm smaller. Bony anatomy-based set-up protocols improve the group prostate set-up error compared with skin marks; however, large prostate systematic errors can remain undetected or systematic (errors increased for individual patients. The margin required for set-up errors was found to be 10-15 mm unless I implanted fiducial markers are available for treatment guidance.

Analysis of measured data of human body based on error correcting frequency

Science.gov (United States)

Jin, Aiyan; Peipei, Gao; Shang, Xiaomei

2014-04-01

Anthropometry is to measure all parts of human body surface, and the measured data is the basis of analysis and study of the human body, establishment and modification of garment size and formulation and implementation of online clothing store. In this paper, several groups of the measured data are gained, and analysis of data error is gotten by analyzing the error frequency and using analysis of variance method in mathematical statistics method. Determination of the measured data accuracy and the difficulty of measured parts of human body, further studies of the causes of data errors, and summarization of the key points to minimize errors possibly are also mentioned in the paper. This paper analyses the measured data based on error frequency, and in a way , it provides certain reference elements to promote the garment industry development.

INVESTIGATION OF INFLUENCE OF ENCODING FUNCTION COMPLEXITY ON DISTRIBUTION OF ERROR MASKING PROBABILITY

Directory of Open Access Journals (Sweden)

A. B. Levina

2016-03-01

Full Text Available Error detection codes are mechanisms that enable robust delivery of data in unreliable communication channels and devices. Unreliable channels and devices are error-prone objects. Respectively, error detection codes allow detecting such errors. There are two classes of error detecting codes - classical codes and security-oriented codes. The classical codes have high percentage of detected errors; however, they have a high probability to miss an error in algebraic manipulation. In order, security-oriented codes are codes with a small Hamming distance and high protection to algebraic manipulation. The probability of error masking is a fundamental parameter of security-oriented codes. A detailed study of this parameter allows analyzing the behavior of the error-correcting code in the case of error injection in the encoding device. In order, the complexity of the encoding function plays an important role in the security-oriented codes. Encoding functions with less computational complexity and a low probability of masking are the best protection of encoding device against malicious acts. This paper investigates the influence of encoding function complexity on the error masking probability distribution. It will be shownthat the more complex encoding function reduces the maximum of error masking probability. It is also shown in the paper that increasing of the function complexity changes the error masking probability distribution. In particular, increasing of computational complexity decreases the difference between the maximum and average value of the error masking probability. Our resultshave shown that functions with greater complexity have smoothed maximums of error masking probability, which significantly complicates the analysis of error-correcting code by attacker. As a result, in case of complex encoding function the probability of the algebraic manipulation is reduced. The paper discusses an approach how to measure the error masking

A prospective study on an innovative online forum for peer reviewing of surgical science.

Directory of Open Access Journals (Sweden)

Martin Almquist

Full Text Available Peer review is important to the scientific process. However, the present system has been criticised and accused of bias, lack of transparency, failure to detect significant breakthrough and error. At the British Journal of Surgery (BJS, after surveying authors' and reviewers' opinions on peer review, we piloted an open online forum with the aim of improving the peer review process.In December 2014, a web-based survey assessing attitudes towards open online review was sent to reviewers with a BJS account in Scholar One. From April to June 2015, authors were invited to allow their manuscripts to undergo online peer review in addition to the standard peer review process. The quality of each review was evaluated by editors and editorial assistants using a validated instrument based on a Likert scale.The survey was sent to 6635 reviewers. In all, 1454 (21.9% responded. Support for online peer review was strong, with only 10% stating that they would not subject their manuscripts to online peer review. The most prevalent concern was about intellectual property, being highlighted in 118 of 284 comments (41.5%. Out of 265 eligible manuscripts, 110 were included in the online peer review trial. Around 7000 potential reviewers were invited to review each manuscript. In all, 44 of 110 manuscripts (40% received 100 reviews from 59 reviewers, alongside 115 conventional reviews. The quality of the open forum reviews was lower than for conventional reviews (2.13 (± 0.75 versus 2.84 (± 0.71, P<0.001.Open online peer review is feasible in this setting, but it attracts few reviews, of lower quality than conventional peer reviews.

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.

Adaptive and accelerated tracking-learning-detection

Science.gov (United States)

Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

2013-08-01

An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

On-line learning of non-monotonic rules by simple perceptron

OpenAIRE

Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki

1997-01-01

We study the generalization ability of a simple perceptron which learns unlearnable rules. The rules are presented by a teacher perceptron with a non-monotonic transfer function. The student is trained in the on-line mode. The asymptotic behaviour of the generalization error is estimated under various conditions. Several learning strategies are proposed and improved to obtain the theoretical lower bound of the generalization error.

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...

Online beam energy measurement of Beijing electron positron collider II linear accelerator

Science.gov (United States)

Wang, S.; Iqbal, M.; Liu, R.; Chi, Y.

2016-02-01

This paper describes online beam energy measurement of Beijing Electron Positron Collider upgraded version II linear accelerator (linac) adequately. It presents the calculation formula, gives the error analysis in detail, discusses the realization in practice, and makes some verification. The method mentioned here measures the beam energy by acquiring the horizontal beam position with three beam position monitors (BPMs), which eliminates the effect of orbit fluctuation, and is much better than the one using the single BPM. The error analysis indicates that this online measurement has further potential usage such as a part of beam energy feedback system. The reliability of this method is also discussed and demonstrated in this paper.

TH-B-BRC-01: How to Identify and Resolve Potential Clinical Errors

Energy Technology Data Exchange (ETDEWEB)

Das, I. [NYU Langone Medical Center, New York, NY (United States)

2016-06-15

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.

TH-B-BRC-01: How to Identify and Resolve Potential Clinical Errors

International Nuclear Information System (INIS)

Das, I.

2016-01-01

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews of some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803

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

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.

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.

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...

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

Barriers to medication error reporting among hospital nurses.

Science.gov (United States)

Rutledge, Dana N; Retrosi, Tina; Ostrowski, Gary

2018-03-01

The study purpose was to report medication error reporting barriers among hospital nurses, and to determine validity and reliability of an existing medication error reporting barriers questionnaire. Hospital medication errors typically occur between ordering of a medication to its receipt by the patient with subsequent staff monitoring. To decrease medication errors, factors surrounding medication errors must be understood; this requires reporting by employees. Under-reporting can compromise patient safety by disabling improvement efforts. This 2017 descriptive study was part of a larger workforce engagement study at a faith-based Magnet ® -accredited community hospital in California (United States). Registered nurses (~1,000) were invited to participate in the online survey via email. Reported here are sample demographics (n = 357) and responses to the 20-item medication error reporting barriers questionnaire. Using factor analysis, four factors that accounted for 67.5% of the variance were extracted. These factors (subscales) were labelled Fear, Cultural Barriers, Lack of Knowledge/Feedback and Practical/Utility Barriers; each demonstrated excellent internal consistency. The medication error reporting barriers questionnaire, originally developed in long-term care, demonstrated good validity and excellent reliability among hospital nurses. Substantial proportions of American hospital nurses (11%-48%) considered specific factors as likely reporting barriers. Average scores on most barrier items were categorised "somewhat unlikely." The highest six included two barriers concerning the time-consuming nature of medication error reporting and four related to nurses' fear of repercussions. Hospitals need to determine the presence of perceived barriers among nurses using questionnaires such as the medication error reporting barriers and work to encourage better reporting. Barriers to medication error reporting make it less likely that nurses will report medication

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

Online updating procedures for a real-time hydrological forecasting system

International Nuclear Information System (INIS)