Automatic limb identification and sleeping parameters assessment for pressure ulcer prevention.

Science.gov (United States)

Baran Pouyan, Maziyar; Birjandtalab, Javad; Nourani, Mehrdad; Matthew Pompeo, M D

2016-08-01

Pressure ulcers (PUs) are common among vulnerable patients such as elderly, bedridden and diabetic. PUs are very painful for patients and costly for hospitals and nursing homes. Assessment of sleeping parameters on at-risk limbs is critical for ulcer prevention. An effective assessment depends on automatic identification and tracking of at-risk limbs. An accurate limb identification can be used to analyze the pressure distribution and assess risk for each limb. In this paper, we propose a graph-based clustering approach to extract the body limbs from the pressure data collected by a commercial pressure map system. A robust signature-based technique is employed to automatically label each limb. Finally, an assessment technique is applied to evaluate the experienced stress by each limb over time. The experimental results indicate high performance and more than 94% average accuracy of the proposed approach. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automatic topic identification of health-related messages in online health community using text classification.

Science.gov (United States)

Lu, Yingjie

2013-01-01

To facilitate patient involvement in online health community and obtain informative support and emotional support they need, a topic identification approach was proposed in this paper for identifying automatically topics of the health-related messages in online health community, thus assisting patients in reaching the most relevant messages for their queries efficiently. Feature-based classification framework was presented for automatic topic identification in our study. We first collected the messages related to some predefined topics in a online health community. Then we combined three different types of features, n-gram-based features, domain-specific features and sentiment features to build four feature sets for health-related text representation. Finally, three different text classification techniques, C4.5, Naïve Bayes and SVM were adopted to evaluate our topic classification model. By comparing different feature sets and different classification techniques, we found that n-gram-based features, domain-specific features and sentiment features were all considered to be effective in distinguishing different types of health-related topics. In addition, feature reduction technique based on information gain was also effective to improve the topic classification performance. In terms of classification techniques, SVM outperformed C4.5 and Naïve Bayes significantly. The experimental results demonstrated that the proposed approach could identify the topics of online health-related messages efficiently.

Roadway system assessment using bluetooth-based automatic vehicle identification travel time data.

Science.gov (United States)

2012-12-01

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection : systems. This includes considerations in the physical setup of the collection system as well as the interpretation of...

Identification with video game characters as automatic shift of self-perceptions

NARCIS (Netherlands)

Klimmt, C.; Hefner, D.; Vorderer, P.A.; Roth, C.; Blake, C.

2010-01-01

Two experiments tested the prediction that video game players identify with the character or role they are assigned, which leads to automatic shifts in implicit self-perceptions. Video game identification, thus, is considered as a kind of altered self-experience. In Study 1 (N = 61), participants

Performance Modelling of Automatic Identification System with Extended Field of View

DEFF Research Database (Denmark)

Lauersen, Troels; Mortensen, Hans Peter; Pedersen, Nikolaj Bisgaard

2010-01-01

This paper deals with AIS (Automatic Identification System) behavior, to investigate the severity of packet collisions in an extended field of view (FOV). This is an important issue for satellite-based AIS, and the main goal is a feasibility study to find out to what extent an increased FOV...

Automatic Priming Effects for New Associations in Lexical Decision and Perceptual Identification

NARCIS (Netherlands)

D. Pecher (Diane); J.G.W. Raaijmakers (Jeroen)

1999-01-01

textabstractInformation storage in semantic memory was investigated by looking at automatic priming effects for new associations in two experiments. In the study phase word pairs were presented in a paired-associate learning task. Lexical decision and perceptual identification were used to examine

Semi-automatic long-term acoustic surveying

DEFF Research Database (Denmark)

Andreassen, Tórur; Surlykke, Annemarie; Hallam, John

2014-01-01

Increasing concern about decline in biodiversity has created a demand for population surveys. Acoustic monitoring is an efficient non-invasive method, which may be deployed for surveys of animals as diverse as insects, birds, and bats. Long-term unmanned automatic monitoring may provide unique...... to determine bat behavior and correct for the bias toward loud bats inherent in acoustic surveying....

MAC, A System for Automatically IPR Identification, Collection and Distribution

Science.gov (United States)

Serrão, Carlos

Controlling Intellectual Property Rights (IPR) in the Digital World is a very hard challenge. The facility to create multiple bit-by-bit identical copies from original IPR works creates the opportunities for digital piracy. One of the most affected industries by this fact is the Music Industry. The Music Industry has supported huge losses during the last few years due to this fact. Moreover, this fact is also affecting the way that music rights collecting and distributing societies are operating to assure a correct music IPR identification, collection and distribution. In this article a system for automating this IPR identification, collection and distribution is presented and described. This system makes usage of advanced automatic audio identification system based on audio fingerprinting technology. This paper will present the details of the system and present a use-case scenario where this system is being used.

Automatic Identification and Reconstruction of the Right Phrenic Nerve on Computed Tomography

OpenAIRE

Bamps, Kobe; Cuypers, Céline; Polmans, Pieter; Claesen, Luc; Koopman, Pieter

2016-01-01

An automatic computer algorithm was successfully constructed, enabling identification and reconstruction of the right phrenic nerve on high resolution coronary computed tomography scans. This could lead to a substantial reduction in the incidence of phrenic nerve paralysis during pulmonary vein isolation using ballon techniques.

Automatic identification of inertial sensor placement on human body segments during walking

NARCIS (Netherlands)

Weenk, D.; van Beijnum, Bernhard J.F.; Baten, Christian T.M.; Hermens, Hermanus J.; Veltink, Petrus H.

2013-01-01

We present a novel method for the automatic identification of inertial sensors on human body segments during walking. This method allows the user to place (wireless) inertial sensors on arbitrary body segments. Next, the user walks for just a few seconds and the segment to which each sensor is

Automatic Knowledge Extraction and Knowledge Structuring for a National Term Bank

DEFF Research Database (Denmark)

Lassen, Tine; Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

2011-01-01

This paper gives an introduction to the plans and ongoing work in a project, the aim of which is to develop methods for automatic knowledge extraction and automatic construction and updating of ontologies. The project also aims at developing methods for automatic merging of terminological data fr...... various existing sources, as well as methods for target group oriented knowledge dissemination. In this paper, we mainly focus on the plans for automatic knowledge extraction and knowledge structuring that will result in ontologies for a national term bank.......This paper gives an introduction to the plans and ongoing work in a project, the aim of which is to develop methods for automatic knowledge extraction and automatic construction and updating of ontologies. The project also aims at developing methods for automatic merging of terminological data from...

A pattern recognition approach based on DTW for automatic transient identification in nuclear power plants

International Nuclear Information System (INIS)

Galbally, Javier; Galbally, David

2015-01-01

Highlights: • Novel transient identification method for NPPs. • Low-complexity. • Low training data requirements. • High accuracy. • Fully reproducible protocol carried out on a real benchmark. - Abstract: Automatic identification of transients in nuclear power plants (NPPs) allows monitoring the fatigue damage accumulated by critical components during plant operation, and is therefore of great importance for ensuring that usage factors remain within the original design bases postulated by the plant designer. Although several schemes to address this important issue have been explored in the literature, there is still no definitive solution available. In the present work, a new method for automatic transient identification is proposed, based on the Dynamic Time Warping (DTW) algorithm, largely used in other related areas such as signature or speech recognition. The novel transient identification system is evaluated on real operational data following a rigorous pattern recognition protocol. Results show the high accuracy of the proposed approach, which is combined with other interesting features such as its low complexity and its very limited requirements of training data

Automatic Identification System (AIS) Transmit Testing in Louisville Phase 2

Science.gov (United States)

2014-08-01

Firewall Louisville QM 65.206.28.x NAIS Site Controller PC RS232 Serial cable TV32 Computer Cmd Center Serial splitter SAAB R40 AIS Base Station...172.17.14.6 Rack mount computer AIS Radio Interface Ethernet Switch 192.168.0.x Firewall Cable Modem 192.168.0.1 VTS Accred. Boundary serial connection...Automatic Identification System ( AIS ) Transmit Testing in Louisville Phase 2 Distribution Statement A: Approved for public release

Rewriting and suppressing UMLS terms for improved biomedical term identification

NARCIS (Netherlands)

K.M. Hettne (Kristina); E.M. van Mulligen (Erik); M.J. Schuemie (Martijn); R.J.A. Schijvenaars (Bob); J.A. Kors (Jan)

2010-01-01

textabstractBackground: Identification of terms is essential for biomedical text mining. We concentrate here on the use of vocabularies for term identification, specifically the Unified Medical Language System (UMLS). To make the UMLS more suitable for biomedical text mining we implemented and

Automatic slice identification in 3D medical images with a ConvNet regressor

NARCIS (Netherlands)

de Vos, Bob D.; Viergever, Max A.; de Jong, Pim A.; Išgum, Ivana

2016-01-01

Identification of anatomical regions of interest is a prerequisite in many medical image analysis tasks. We propose a method that automatically identifies a slice of interest (SOI) in 3D images with a convolutional neural network (ConvNet) regressor. In 150 chest CT scans two reference slices were

Identification of mycobacterium tuberculosis in sputum smear slide using automatic scanning microscope

Science.gov (United States)

Rulaningtyas, Riries; Suksmono, Andriyan B.; Mengko, Tati L. R.; Saptawati, Putri

2015-04-01

Sputum smear observation has an important role in tuberculosis (TB) disease diagnosis, because it needs accurate identification to avoid high errors diagnosis. In development countries, sputum smear slide observation is commonly done with conventional light microscope from Ziehl-Neelsen stained tissue and it doesn't need high cost to maintain the microscope. The clinicians do manual screening process for sputum smear slide which is time consuming and needs highly training to detect the presence of TB bacilli (mycobacterium tuberculosis) accurately, especially for negative slide and slide with less number of TB bacilli. For helping the clinicians, we propose automatic scanning microscope with automatic identification of TB bacilli. The designed system modified the field movement of light microscope with stepper motor which was controlled by microcontroller. Every sputum smear field was captured by camera. After that some image processing techniques were done for the sputum smear images. The color threshold was used for background subtraction with hue canal in HSV color space. Sobel edge detection algorithm was used for TB bacilli image segmentation. We used feature extraction based on shape for bacilli analyzing and then neural network classified TB bacilli or not. The results indicated identification of TB bacilli that we have done worked well and detected TB bacilli accurately in sputum smear slide with normal staining, but not worked well in over staining and less staining tissue slide. However, overall the designed system can help the clinicians in sputum smear observation becomes more easily.

Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria.

Science.gov (United States)

Chu, Wei; Thompson, Robert M; Song, John; Vorburger, Theodore V

2013-09-10

The consecutive matching striae (CMS) numeric criteria for firearm and toolmark identifications have been widely accepted by forensic examiners, although there have been questions concerning its observer subjectivity and limited statistical support. In this paper, based on signal processing and extraction, a model for the automatic and objective counting of CMS is proposed. The position and shape information of the striae on the bullet land is represented by a feature profile, which is used for determining the CMS number automatically. Rapid counting of CMS number provides a basis for ballistics correlations with large databases and further statistical and probability analysis. Experimental results in this report using bullets fired from ten consecutively manufactured barrels support this developed model. Published by Elsevier Ireland Ltd.

Automatic Adviser on Mobile Objects Status Identification and Classification

Science.gov (United States)

Shabelnikov, A. N.; Liabakh, N. N.; Gibner, Ya M.; Saryan, A. S.

2018-05-01

A mobile object status identification task is defined within the image discrimination theory. It is proposed to classify objects into three classes: object operation status; its maintenance is required and object should be removed from the production process. Two methods were developed to construct the separating boundaries between the designated classes: a) using statistical information on the research objects executed movement, b) basing on regulatory documents and expert commentary. Automatic Adviser operation simulation and the operation results analysis complex were synthesized. Research results are commented using a specific example of cuts rolling from the hump yard. The work was supported by Russian Fundamental Research Fund, project No. 17-20-01040.

Managing Returnable Containers Logistics - A Case Study Part II - Improving Visibility through Using Automatic Identification Technologies

Directory of Open Access Journals (Sweden)

Gretchen Meiser

2011-05-01

Full Text Available This case study is the result of a project conducted on behalf of a company that uses its own returnable containers to transport purchased parts from suppliers. The objective of this project was to develop a proposal to enable the company to more effectively track and manage its returnable containers. The research activities in support of this project included (1 the analysis and documentation of the physical flow and the information flow associated with the containers and (2 the investigation of new technologies to improve the automatic identification and tracking of containers. This paper explains the automatic identification technologies and important criteria for selection. A companion paper details the flow of information and containers within the logistics chain, and it identifies areas for improving the management of the containers.

Channel Access Algorithm Design for Automatic Identification System

Institute of Scientific and Technical Information of China (English)

Oh Sang-heon; Kim Seung-pum; Hwang Dong-hwan; Park Chan-sik; Lee Sang-jeong

2003-01-01

The Automatic Identification System (AIS) is a maritime equipment to allow an efficient exchange of the navigational data between ships and between ships and shore stations. It utilizes a channel access algorithm which can quickly resolve conflicts without any intervention from control stations. In this paper, a design of channel access algorithm for the AIS is presented. The input/output relationship of each access algorithm module is defined by drawing the state transition diagram, dataflow diagram and flowchart based on the technical standard, ITU-R M.1371. In order to verify the designed channel access algorithm, the simulator was developed using the C/C++ programming language. The results show that the proposed channel access algorithm can properly allocate transmission slots and meet the operational performance requirements specified by the technical standard.

A hybrid approach to automatic de-identification of psychiatric notes.

Science.gov (United States)

Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

2017-11-01

De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

Roadway System Assessment Using Bluetooth-Based Automatic Vehicle Identification Travel Time Data

OpenAIRE

Day, Christopher M.; Brennan, Thomas M.; Hainen, Alexander M.; Remias, Stephen M.; Bullock, Darcy M.

2012-01-01

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection systems. This includes considerations in the physical setup of the collection system as well as the interpretation of the data. An extended discussion is provided, with examples, demonstrating data techniques for converting the raw data into more concise metrics and views. Examples of statistical before-after tests are also provided. A series of case studies were ...

AROMA-AIRWICK: a CHLOE/CDC-3600 system for the automatic identification of spark images and their association into tracks

International Nuclear Information System (INIS)

Clark, R.K.

The AROMA-AIRWICK System for CHLOE, an automatic film scanning equipment built at Argonne by Donald Hodges, and the CDC-3600 computer is a system for the automatic identification of spark images and their association into tracks. AROMA-AIRWICK has been an outgrowth of the generally recognized need for the automatic processing of high energy physics data and the fact that the Argonne National Laboratory has been a center of serious spark chamber development in recent years

Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric MR images

Science.gov (United States)

Suzani, Amin; Rasoulian, Abtin; Seitel, Alexander; Fels, Sidney; Rohling, Robert N.; Abolmaesumi, Purang

2015-03-01

This paper proposes an automatic method for vertebra localization, labeling, and segmentation in multi-slice Magnetic Resonance (MR) images. Prior work in this area on MR images mostly requires user interaction while our method is fully automatic. Cubic intensity-based features are extracted from image voxels. A deep learning approach is used for simultaneous localization and identification of vertebrae. The localized points are refined by local thresholding in the region of the detected vertebral column. Thereafter, a statistical multi-vertebrae model is initialized on the localized vertebrae. An iterative Expectation Maximization technique is used to register the vertebral body of the model to the image edges and obtain a segmentation of the lumbar vertebral bodies. The method is evaluated by applying to nine volumetric MR images of the spine. The results demonstrate 100% vertebra identification and a mean surface error of below 2.8 mm for 3D segmentation. Computation time is less than three minutes per high-resolution volumetric image.

Evaluating current automatic de-identification methods with Veteran’s health administration clinical documents

Directory of Open Access Journals (Sweden)

Ferrández Oscar

2012-07-01

Full Text Available Abstract Background The increased use and adoption of Electronic Health Records (EHR causes a tremendous growth in digital information useful for clinicians, researchers and many other operational purposes. However, this information is rich in Protected Health Information (PHI, which severely restricts its access and possible uses. A number of investigators have developed methods for automatically de-identifying EHR documents by removing PHI, as specified in the Health Insurance Portability and Accountability Act “Safe Harbor” method. This study focuses on the evaluation of existing automated text de-identification methods and tools, as applied to Veterans Health Administration (VHA clinical documents, to assess which methods perform better with each category of PHI found in our clinical notes; and when new methods are needed to improve performance. Methods We installed and evaluated five text de-identification systems “out-of-the-box” using a corpus of VHA clinical documents. The systems based on machine learning methods were trained with the 2006 i2b2 de-identification corpora and evaluated with our VHA corpus, and also evaluated with a ten-fold cross-validation experiment using our VHA corpus. We counted exact, partial, and fully contained matches with reference annotations, considering each PHI type separately, or only one unique ‘PHI’ category. Performance of the systems was assessed using recall (equivalent to sensitivity and precision (equivalent to positive predictive value metrics, as well as the F2-measure. Results Overall, systems based on rules and pattern matching achieved better recall, and precision was always better with systems based on machine learning approaches. The highest “out-of-the-box” F2-measure was 67% for partial matches; the best precision and recall were 95% and 78%, respectively. Finally, the ten-fold cross validation experiment allowed for an increase of the F2-measure to 79% with partial matches

An automatic microseismic or acoustic emission arrival identification scheme with deep recurrent neural networks

Science.gov (United States)

Zheng, Jing; Lu, Jiren; Peng, Suping; Jiang, Tianqi

2018-02-01

The conventional arrival pick-up algorithms cannot avoid the manual modification of the parameters for the simultaneous identification of multiple events under different signal-to-noise ratios (SNRs). Therefore, in order to automatically obtain the arrivals of multiple events with high precision under different SNRs, in this study an algorithm was proposed which had the ability to pick up the arrival of microseismic or acoustic emission events based on deep recurrent neural networks. The arrival identification was performed using two important steps, which included a training phase and a testing phase. The training process was mathematically modelled by deep recurrent neural networks using Long Short-Term Memory architecture. During the testing phase, the learned weights were utilized to identify the arrivals through the microseismic/acoustic emission data sets. The data sets were obtained by rock physics experiments of the acoustic emission. In order to obtain the data sets under different SNRs, this study added random noise to the raw experiments' data sets. The results showed that the outcome of the proposed method was able to attain an above 80 per cent hit-rate at SNR 0 dB, and an approximately 70 per cent hit-rate at SNR -5 dB, with an absolute error in 10 sampling points. These results indicated that the proposed method had high selection precision and robustness.

CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal-neutron-activated samples

International Nuclear Information System (INIS)

Giannini, M.; Oliva, P.R.; Ramorino, M.C.

1979-01-01

A computer code that automatically analyzes gamma-ray spectra obtained with Ge(Li) detectors is described. The program contains such features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification, and calculation of masses and errors. Finally, the results obtained with this computer code for a lunar sample are reported and briefly discussed

Operator overloading as an enabling technology for automatic differentiation

International Nuclear Information System (INIS)

Corliss, G.F.; Griewank, A.

1993-01-01

We present an example of the science that is enabled by object-oriented programming techniques. Scientific computation often needs derivatives for solving nonlinear systems such as those arising in many PDE algorithms, optimization, parameter identification, stiff ordinary differential equations, or sensitivity analysis. Automatic differentiation computes derivatives accurately and efficiently by applying the chain rule to each arithmetic operation or elementary function. Operator overloading enables the techniques of either the forward or the reverse mode of automatic differentiation to be applied to real-world scientific problems. We illustrate automatic differentiation with an example drawn from a model of unsaturated flow in a porous medium. The problem arises from planning for the long-term storage of radioactive waste

CERPI and CEREL, two computer codes for the automatic identification and determination of gamma emitters in thermal neutron activated samples

International Nuclear Information System (INIS)

Giannini, M.; Oliva, P.R.; Ramorino, C.

1978-01-01

A description is given of a computer code which automatically analyses gamma-ray spectra obtained with Ge(Li) detectors. The program contains features as automatic peak location and fitting, determination of peak energies and intensities, nuclide identification and calculation of masses and errors. Finally the results obtained with our computer code for a lunar sample are reported and briefly discussed

Rewriting and suppressing UMLS terms for improved biomedical term identification

Directory of Open Access Journals (Sweden)

Hettne Kristina M

2010-03-01

Full Text Available Abstract Background Identification of terms is essential for biomedical text mining.. We concentrate here on the use of vocabularies for term identification, specifically the Unified Medical Language System (UMLS. To make the UMLS more suitable for biomedical text mining we implemented and evaluated nine term rewrite and eight term suppression rules. The rules rely on UMLS properties that have been identified in previous work by others, together with an additional set of new properties discovered by our group during our work with the UMLS. Our work complements the earlier work in that we measure the impact on the number of terms identified by the different rules on a MEDLINE corpus. The number of uniquely identified terms and their frequency in MEDLINE were computed before and after applying the rules. The 50 most frequently found terms together with a sample of 100 randomly selected terms were evaluated for every rule. Results Five of the nine rewrite rules were found to generate additional synonyms and spelling variants that correctly corresponded to the meaning of the original terms and seven out of the eight suppression rules were found to suppress only undesired terms. Using the five rewrite rules that passed our evaluation, we were able to identify 1,117,772 new occurrences of 14,784 rewritten terms in MEDLINE. Without the rewriting, we recognized 651,268 terms belonging to 397,414 concepts; with rewriting, we recognized 666,053 terms belonging to 410,823 concepts, which is an increase of 2.8% in the number of terms and an increase of 3.4% in the number of concepts recognized. Using the seven suppression rules, a total of 257,118 undesired terms were suppressed in the UMLS, notably decreasing its size. 7,397 terms were suppressed in the corpus. Conclusions We recommend applying the five rewrite rules and seven suppression rules that passed our evaluation when the UMLS is to be used for biomedical term identification in MEDLINE. A software

Integration and segregation of large-scale brain networks during short-term task automatization.

Science.gov (United States)

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-11-03

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Automatic Identification System modular receiver for academic purposes

Science.gov (United States)

Cabrera, F.; Molina, N.; Tichavska, M.; Araña, V.

2016-07-01

The Automatic Identification System (AIS) standard is encompassed within the Global Maritime Distress and Safety System (GMDSS), in force since 1999. The GMDSS is a set of procedures, equipment, and communication protocols designed with the aim of increasing the safety of sea crossings, facilitating navigation, and the rescue of vessels in danger. The use of this system not only is increasingly attractive to security issues but also potentially creates intelligence products throughout the added-value information that this network can transmit from ships on real time (identification, position, course, speed, dimensions, flag, among others). Within the marine electronics market, commercial receivers implement this standard and allow users to access vessel-broadcasted information if in the range of coverage. In addition to satellite services, users may request actionable information from private or public AIS terrestrial networks where real-time feed or historical data can be accessed from its nodes. This paper describes the configuration of an AIS receiver based on a modular design. This modular design facilitates the evaluation of specific modules and also a better understanding of the standard and the possibility of changing hardware modules to improve the performance of the prototype. Thus, the aim of this paper is to describe the system's specifications, its main hardware components, and to present educational didactics on the setup and use of a modular and terrestrial AIS receiver. The latter is for academic purposes and in undergraduate studies such as electrical engineering, telecommunications, and maritime studies.

Automatic Identification of Subtechniques in Skating-Style Roller Skiing Using Inertial Sensors

Science.gov (United States)

Sakurai, Yoshihisa; Fujita, Zenya; Ishige, Yusuke

2016-01-01

This study aims to develop and validate an automated system for identifying skating-style cross-country subtechniques using inertial sensors. In the first experiment, the performance of a male cross-country skier was used to develop an automated identification system. In the second, eight male and seven female college cross-country skiers participated to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, and a small video camera on a backpack. All subjects skied through a 3450 m roller ski course using a skating style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, as well as by visual observations from a video recording of the same ski run. The system correctly identified 6418 subtechniques from a total of 6768 cycles, which indicates an accuracy of 94.8%. The precisions of the automatic system for identifying the V1R, V1L, V2R, V2L, V2AR, and V2AL subtechniques were 87.6%, 87.0%, 97.5%, 97.8%, 92.1%, and 92.0%, respectively. Most incorrect identification cases occurred during a subtechnique identification that included a transition and turn event. Identification accuracy can be improved by separately identifying transition and turn events. This system could be used to evaluate each skier’s subtechniques in course conditions. PMID:27049388

Automatic Identification of Subtechniques in Skating-Style Roller Skiing Using Inertial Sensors

Directory of Open Access Journals (Sweden)

Yoshihisa Sakurai

2016-04-01

Full Text Available This study aims to develop and validate an automated system for identifying skating-style cross-country subtechniques using inertial sensors. In the first experiment, the performance of a male cross-country skier was used to develop an automated identification system. In the second, eight male and seven female college cross-country skiers participated to validate the developed identification system. Each subject wore inertial sensors on both wrists and both roller skis, and a small video camera on a backpack. All subjects skied through a 3450 m roller ski course using a skating style at their maximum speed. The adopted subtechniques were identified by the automated method based on the data obtained from the sensors, as well as by visual observations from a video recording of the same ski run. The system correctly identified 6418 subtechniques from a total of 6768 cycles, which indicates an accuracy of 94.8%. The precisions of the automatic system for identifying the V1R, V1L, V2R, V2L, V2AR, and V2AL subtechniques were 87.6%, 87.0%, 97.5%, 97.8%, 92.1%, and 92.0%, respectively. Most incorrect identification cases occurred during a subtechnique identification that included a transition and turn event. Identification accuracy can be improved by separately identifying transition and turn events. This system could be used to evaluate each skier’s subtechniques in course conditions.

Automatic identification of otologic drilling faults: a preliminary report.

Science.gov (United States)

Shen, Peng; Feng, Guodong; Cao, Tianyang; Gao, Zhiqiang; Li, Xisheng

2009-09-01

A preliminary study was carried out to identify parameters to characterize drilling faults when using an otologic drill under various operating conditions. An otologic drill was modified by the addition of four sensors. Under consistent conditions, the drill was used to simulate three important types of drilling faults and the captured data were analysed to extract characteristic signals. A multisensor information fusion system was designed to fuse the signals and automatically identify the faults. When identifying drilling faults, there was a high degree of repeatability and regularity, with an average recognition rate of >70%. This study shows that the variables measured change in a fashion that allows the identification of particular drilling faults, and that it is feasible to use these data to provide rapid feedback for a control system. Further experiments are being undertaken to implement such a system.

Automatic multimodal detection for long-term seizure documentation in epilepsy.

Science.gov (United States)

Fürbass, F; Kampusch, S; Kaniusas, E; Koren, J; Pirker, S; Hopfengärtner, R; Stefan, H; Kluge, T; Baumgartner, C

2017-08-01

This study investigated sensitivity and false detection rate of a multimodal automatic seizure detection algorithm and the applicability to reduced electrode montages for long-term seizure documentation in epilepsy patients. An automatic seizure detection algorithm based on EEG, EMG, and ECG signals was developed. EEG/ECG recordings of 92 patients from two epilepsy monitoring units including 494 seizures were used to assess detection performance. EMG data were extracted by bandpass filtering of EEG signals. Sensitivity and false detection rate were evaluated for each signal modality and for reduced electrode montages. All focal seizures evolving to bilateral tonic-clonic (BTCS, n=50) and 89% of focal seizures (FS, n=139) were detected. Average sensitivity in temporal lobe epilepsy (TLE) patients was 94% and 74% in extratemporal lobe epilepsy (XTLE) patients. Overall detection sensitivity was 86%. Average false detection rate was 12.8 false detections in 24h (FD/24h) for TLE and 22 FD/24h in XTLE patients. Utilization of 8 frontal and temporal electrodes reduced average sensitivity from 86% to 81%. Our automatic multimodal seizure detection algorithm shows high sensitivity with full and reduced electrode montages. Evaluation of different signal modalities and electrode montages paces the way for semi-automatic seizure documentation systems. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Exploration of Web Users' Search Interests through Automatic Subject Categorization of Query Terms.

Science.gov (United States)

Pu, Hsiao-tieh; Yang, Chyan; Chuang, Shui-Lung

2001-01-01

Proposes a mechanism that carefully integrates human and machine efforts to explore Web users' search interests. The approach consists of a four-step process: extraction of core terms; construction of subject taxonomy; automatic subject categorization of query terms; and observation of users' search interests. Research findings are proved valuable…

Automatic sample changers maintenance manual

International Nuclear Information System (INIS)

Myers, T.A.

1978-10-01

This manual describes and provides trouble-shooting aids for the Automatic Sample Changer electronics on the automatic beta counting system, developed by the Los Alamos Scientific Laboratory Group CNC-11. The output of a gas detector is shaped by a preamplifier, then is coupled to an amplifier. Amplifier output is discriminated and is the input to a scaler. An identification number is associated with each sample. At a predetermined count length, the identification number, scaler data plus other information is punched out on a data card. The next sample to be counted is automatically selected. The beta counter uses the same electronics as the prior count did, the only difference being the sample identification number and sample itself. This manual is intended as a step-by-step aid in trouble-shooting the electronics associated with positioning the sample, counting the sample, and getting the needed data punched on an 80-column data card

Automatic failure identification of the nuclear power plant pellet fuel

International Nuclear Information System (INIS)

Oliveira, Adriano Fortunato de

2010-01-01

This paper proposed the development of an automatic technique for evaluating defects to help in the stage of fabrication of fuel elements. Was produced an intelligent image analysis for automatic recognition of defects in uranium pellets. Therefore, an Artificial Neural Network (ANN) was trained using segments of histograms of pellets, containing examples of both normal (no fault) and of defectives pellets (with major defects normally found). The images of the pellets were segmented into 11 shares. Histograms were made of these segments and trained the ANN. Besides automating the process, the system was able to obtain this classification accuracy of 98.33%. Although this percentage represents a significant advance ever in the quality control process, the use of more advanced techniques of photography and lighting will reduce it to insignificant levels with low cost. Technologically, the method developed, should it ever be implemented, will add substantial value in terms of process quality control and production outages in relation to domestic manufacturing of nuclear fuel. (author)

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

Science.gov (United States)

Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

2018-04-30

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic annotation of protein motif function with Gene Ontology terms

Directory of Open Access Journals (Sweden)

Gopalakrishnan Vanathi

2004-09-01

Full Text Available Abstract Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. Results This paperpresents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifsis viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association isfound to be a very useful feature. We take advantageof the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correctassociation. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. Conclusions In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about thefunctions of newly discovered candidate protein motifs.

Automatic identification and normalization of dosage forms in drug monographs

Science.gov (United States)

2012-01-01

Background Each day, millions of health consumers seek drug-related information on the Web. Despite some efforts in linking related resources, drug information is largely scattered in a wide variety of websites of different quality and credibility. Methods As a step toward providing users with integrated access to multiple trustworthy drug resources, we aim to develop a method capable of identifying drug's dosage form information in addition to drug name recognition. We developed rules and patterns for identifying dosage forms from different sections of full-text drug monographs, and subsequently normalized them to standardized RxNorm dosage forms. Results Our method represents a significant improvement compared with a baseline lookup approach, achieving overall macro-averaged Precision of 80%, Recall of 98%, and F-Measure of 85%. Conclusions We successfully developed an automatic approach for drug dosage form identification, which is critical for building links between different drug-related resources. PMID:22336431

Metodology of identification parameters of models control objects of automatic trailing system

Directory of Open Access Journals (Sweden)

I.V. Zimchuk

2017-04-01

Full Text Available The determining factor for the successful solution of the problem of synthesis of optimal control systems of different processes are adequacy of mathematical model of control object. In practice, the options can differ from the objects taken priori, causing a need to clarification of them. In this context, the article presents the results of the development and application of methods parameters identification of mathematical models of control object of automatic trailing system. The stated problem in the article is solved provided that control object is fully controlled and observed, and a differential equation of control object is known a priori. The coefficients of this equation to be determined. Identifying quality criterion is to minimize the integral value of squared error of identification. The method is based on a description of the dynamics of the object in space state. Equation of identification synthesized using the vector-matrix representation of model. This equation describes the interconnection of coefficients of matrix state and control with inputs and outputs of object. The initial data for calculation are the results of experimental investigation of the reaction of phase coordinates of control object at a typical input signal. The process of calculating the model parameters is reduced to solving the system of equations of the first order each. Application the above approach is illustrated in the example identification of coefficients transfer function of control object first order. Results of digital simulation are presented, they are confirming the justice of set out mathematical calculations. The approach enables to do the identification of models of one-dimensional and multidimensional objects and does not require a large amount of calculation for its implementation. The order of identified model is limited capabilities of measurement phase coordinates of corresponding control object. The practical significance of the work is

The problem of automatic identification of concepts

International Nuclear Information System (INIS)

Andreewsky, Alexandre

1975-11-01

This paper deals with the problem of the automatic recognition of concepts and describes an important language tool, the ''linguistic filter'', which facilitates the construction of statistical algorithms. Certain special filters, of prepositions, conjunctions, negatives, logical implication, compound words, are presented. This is followed by a detailed description of a statistical algorithm allowing recognition of pronoun referents, and finally the problem of the automatic treatment of negatives in French is discussed [fr

Development of an Automatic Identification System Autonomous Positioning System

Directory of Open Access Journals (Sweden)

Qing Hu

2015-11-01

Full Text Available In order to overcome the vulnerability of the global navigation satellite system (GNSS and provide robust position, navigation and time (PNT information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS is presented in the paper. The principle of the AIS autonomous positioning system (AAPS is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China. Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts.

An Automatic Identification Procedure to Promote the use of FES-Cycling Training for Hemiparetic Patients

Directory of Open Access Journals (Sweden)

Emilia Ambrosini

2014-01-01

Full Text Available Cycling induced by Functional Electrical Stimulation (FES training currently requires a manual setting of different parameters, which is a time-consuming and scarcely repeatable procedure. We proposed an automatic procedure for setting session-specific parameters optimized for hemiparetic patients. This procedure consisted of the identification of the stimulation strategy as the angular ranges during which FES drove the motion, the comparison between the identified strategy and the physiological muscular activation strategy, and the setting of the pulse amplitude and duration of each stimulated muscle. Preliminary trials on 10 healthy volunteers helped define the procedure. Feasibility tests on 8 hemiparetic patients (5 stroke, 3 traumatic brain injury were performed. The procedure maximized the motor output within the tolerance constraint, identified a biomimetic strategy in 6 patients, and always lasted less than 5 minutes. Its reasonable duration and automatic nature make the procedure usable at the beginning of every training session, potentially enhancing the performance of FES-cycling training.

Forming and detection of digital watermarks in the System for Automatic Identification of VHF Transmissions

Directory of Open Access Journals (Sweden)

О. В. Шишкін

2013-07-01

Full Text Available Forming and detection algorithms for digital watermarks are designed for automatic identification of VHF radiotelephone transmissions in the maritime and aeronautical mobile services. An audible insensitivity and interference resistance of embedded digital data are provided by means of OFDM technology jointly with normalized distortions distribution and data packet detection by the hash-function. Experiments were carried out on the base of ship’s radio station RT-2048 Sailor and USB ADC-DAC module of type Е14-140M L-CARD in the off-line processing regime in Matlab medium

Contribution to automatic speech recognition. Analysis of the direct acoustical signal. Recognition of isolated words and phoneme identification

International Nuclear Information System (INIS)

Dupeyrat, Benoit

1981-01-01

This report deals with the acoustical-phonetic step of the automatic recognition of the speech. The parameters used are the extrema of the acoustical signal (coded in amplitude and duration). This coding method, the properties of which are described, is simple and well adapted to a digital processing. The quality and the intelligibility of the coded signal after reconstruction are particularly satisfactory. An experiment for the automatic recognition of isolated words has been carried using this coding system. We have designed a filtering algorithm operating on the parameters of the coding. Thus the characteristics of the formants can be derived under certain conditions which are discussed. Using these characteristics the identification of a large part of the phonemes for a given speaker was achieved. Carrying on the studies has required the development of a particular methodology of real time processing which allowed immediate evaluation of the improvement of the programs. Such processing on temporal coding of the acoustical signal is extremely powerful and could represent, used in connection with other methods an efficient tool for the automatic processing of the speech.(author) [fr

Automatic writer identification using connected-component contours and edge-based features of uppercase Western script.

Science.gov (United States)

Schomaker, Lambert; Bulacu, Marius

2004-06-01

In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO3s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected components for the uppercase character set. Using a codebook of CO3s from an independent training set of 100 writers, the probability-density function (PDF) of CO3s was computed for an independent test set containing 150 unseen writers. Results revealed a high-sensitivity of the CO3 PDF for identifying individual writers on the basis of a single sentence of uppercase characters. The proposed automatic approach bridges the gap between image-statistics approaches on one end and manually measured allograph features of individual characters on the other end. Combining the CO3 PDF with an independent edge-based orientation and curvature PDF yielded very high correct identification rates.

Automatic vertebral identification using surface-based registration

Science.gov (United States)

Herring, Jeannette L.; Dawant, Benoit M.

2000-06-01

This work introduces an enhancement to currently existing methods of intra-operative vertebral registration by allowing the portion of the spinal column surface that correctly matches a set of physical vertebral points to be automatically selected from several possible choices. Automatic selection is made possible by the shape variations that exist among lumbar vertebrae. In our experiments, we register vertebral points representing physical space to spinal column surfaces extracted from computed tomography images. The vertebral points are taken from the posterior elements of a single vertebra to represent the region of surgical interest. The surface is extracted using an improved version of the fully automatic marching cubes algorithm, which results in a triangulated surface that contains multiple vertebrae. We find the correct portion of the surface by registering the set of physical points to multiple surface areas, including all vertebral surfaces that potentially match the physical point set. We then compute the standard deviation of the surface error for the set of points registered to each vertebral surface that is a possible match, and the registration that corresponds to the lowest standard deviation designates the correct match. We have performed our current experiments on two plastic spine phantoms and one patient.

FORENSIC LINGUISTICS: AUTOMATIC WEB AUTHOR IDENTIFICATION

Directory of Open Access Journals (Sweden)

A. A. Vorobeva

2016-03-01

Full Text Available Internet is anonymous, this allows posting under a false name, on behalf of others or simply anonymous. Thus, individuals, criminal or terrorist organizations can use Internet for criminal purposes; they hide their identity to avoid the prosecuting. Existing approaches and algorithms for author identification of web-posts on Russian language are not effective. The development of proven methods, technics and tools for author identification is extremely important and challenging task. In this work the algorithm and software for authorship identification of web-posts was developed. During the study the effectiveness of several classification and feature selection algorithms were tested. The algorithm includes some important steps: 1 Feature extraction; 2 Features discretization; 3 Feature selection with the most effective Relief-f algorithm (to find the best feature set with the most discriminating power for each set of candidate authors and maximize accuracy of author identification; 4 Author identification on model based on Random Forest algorithm. Random Forest and Relief-f algorithms are used to identify the author of a short text on Russian language for the first time. The important step of author attribution is data preprocessing - discretization of continuous features; earlier it was not applied to improve the efficiency of author identification. The software outputs top q authors with maximum probabilities of authorship. This approach is helpful for manual analysis in forensic linguistics, when developed tool is used to narrow the set of candidate authors. For experiments on 10 candidate authors, real author appeared in to top 3 in 90.02% cases, on first place real author appeared in 70.5% of cases.

Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

Science.gov (United States)

Zdravevski, Eftim; Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

2017-01-01

Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from

Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

Directory of Open Access Journals (Sweden)

Eftim Zdravevski

Full Text Available Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position.The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers.The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be

Automatic identification of mass spectra

International Nuclear Information System (INIS)

Drabloes, F.

1992-01-01

Several approaches to preprocessing and comparison of low resolution mass spectra have been evaluated by various test methods related to library search. It is shown that there is a clear correlation between the nature of any contamination of a spectrum, the basic principle of the transformation or distance measure, and the performance of the identification system. The identification of functionality from low resolution spectra has also been evaluated using several classification methods. It is shown that there is an upper limit to the success of this approach, but also that this can be improved significantly by using a very limited amount of additional information. 10 refs

A new technology for automatic identification and sorting of plastics for recycling.

Science.gov (United States)

Ahmad, S R

2004-10-01

A new technology for automatic sorting of plastics, based upon optical identification of fluorescence signatures of dyes, incorporated in such materials in trace concentrations prior to product manufacturing, is described. Three commercial tracers were selected primarily on the basis of their good absorbency in the 310-370 nm spectral band and their identifiable narrow-band fluorescence signatures in the visible band of the spectrum when present in binary combinations. This absorption band was selected because of the availability of strong emission lines in this band from a commercial Hg-arc lamp and high fluorescence quantum yields of the tracers at this excitation wavelength band. The plastics chosen for tracing and identification are HDPE, LDPE, PP, EVA, PVC and PET and the tracers were compatible and chemically non-reactive with the host matrices and did not affect the transparency of the plastics. The design of a monochromatic and collimated excitation source, the sensor system are described and their performances in identifying and sorting plastics doped with tracers at a few parts per million concentration levels are evaluated. In an industrial sorting system, the sensor was able to sort 300 mm long plastic bottles at a conveyor belt speed of 3.5 m.sec(-1) with a sorting purity of -95%. The limitation was imposed due to mechanical singulation irregularities at high speed and the limited processing speed of the computer used.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

Science.gov (United States)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

A Joint Approach for Single-Channel Speaker Identification and Speech Separation

DEFF Research Database (Denmark)

Mowlaee, Pejman; Saeidi, Rahim; Christensen, Mads Græsbøll

2012-01-01

) accuracy, here, we report the objective and subjective results as well. The results show that the proposed system performs as well as the best of the state-of-the-art in terms of perceived quality while its performance in terms of speaker identification and automatic speech recognition results......In this paper, we present a novel system for joint speaker identification and speech separation. For speaker identification a single-channel speaker identification algorithm is proposed which provides an estimate of signal-to-signal ratio (SSR) as a by-product. For speech separation, we propose...... a sinusoidal model-based algorithm. The speech separation algorithm consists of a double-talk/single-talk detector followed by a minimum mean square error estimator of sinusoidal parameters for finding optimal codevectors from pre-trained speaker codebooks. In evaluating the proposed system, we start from...

Automatically annotating web pages using Google Rich Snippets

NARCIS (Netherlands)

Hogenboom, F.P.; Frasincar, F.; Vandic, D.; Meer, van der J.; Boon, F.; Kaymak, U.

2011-01-01

We propose the Automatic Review Recognition and annO- tation of Web pages (ARROW) framework, a framework for Web page review identification and annotation using RDFa Google Rich Snippets. The ARROW framework consists of four steps: hotspot identification, subjectivity analysis, in- formation

Automatic and Controlled Processing in Sentence Recall: The Role of Long-Term and Working Memory

Science.gov (United States)

Jefferies, E.; Lambon Ralph, M.A.; Baddeley, A.D.

2004-01-01

Immediate serial recall is better for sentences than word lists presumably because of the additional support that meaningful material receives from long-term memory. This may occur automatically, without the involvement of attention, or may require additional attentionally demanding processing. For example, the episodic buffer model (Baddeley,…

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

Science.gov (United States)

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

Toward Automatic Georeferencing of Archival Aerial Photogrammetric Surveys

Science.gov (United States)

Giordano, S.; Le Bris, A.; Mallet, C.

2018-05-01

Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i) the computation of a coarse absolute image orientation; (ii) the use of the coarse Digital Surface Model (DSM) information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.

TOWARD AUTOMATIC GEOREFERENCING OF ARCHIVAL AERIAL PHOTOGRAMMETRIC SURVEYS

Directory of Open Access Journals (Sweden)

S. Giordano

2018-05-01

Full Text Available Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i the computation of a coarse absolute image orientation; (ii the use of the coarse Digital Surface Model (DSM information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.

DIRADTM - a system for real time detection and identification of radioactive objects

International Nuclear Information System (INIS)

Guillot, L.; Reboli, A.

2009-01-01

The authors present the DIRAD system (DIRAD stands for Detection and Identification of Radionuclides), an automatic system for real time identification of a radioactive anomaly and its interpretation in terms of risk level. It can be adapted to different contexts: pedestrian control, parcel or luggage control, road traffic control, and so on. In case of risk detection, an alert is transmitted in real time to a supervision station along with the whole set of spectral data

Profiling School Shooters: Automatic Text-Based Analysis

Directory of Open Access Journals (Sweden)

Yair eNeuman

2015-06-01

Full Text Available School shooters present a challenge to both forensic psychiatry and law enforcement agencies. The relatively small number of school shooters, their various charateristics, and the lack of in-depth analysis of all of the shooters prior to the shooting add complexity to our understanding of this problem. In this short paper, we introduce a new methodology for automatically profiling school shooters. The methodology involves automatic analysis of texts and the production of several measures relevant for the identification of the shooters. Comparing texts written by six school shooters to 6056 texts written by a comparison group of male subjects, we found that the shooters' texts scored significantly higher on the Narcissistic Personality dimension as well as on the Humilated and Revengeful dimensions. Using a ranking/priorization procedure, similar to the one used for the automatic identification of sexual predators, we provide support for the validity and relevance of the proposed methodology.

Automatic identification of watercourses in flat and engineered landscapes by computing the skeleton of a LiDAR point cloud

Science.gov (United States)

Broersen, Tom; Peters, Ravi; Ledoux, Hugo

2017-09-01

Drainage networks play a crucial role in protecting land against floods. It is therefore important to have an accurate map of the watercourses that form the drainage network. Previous work on the automatic identification of watercourses was typically based on grids, focused on natural landscapes, and used mostly the slope and curvature of the terrain. We focus in this paper on areas that are characterised by low-lying, flat, and engineered landscapes; these are characteristic to the Netherlands for instance. We propose a new methodology to identify watercourses automatically from elevation data, it uses solely a raw classified LiDAR point cloud as input. We show that by computing twice a skeleton of the point cloud-once in 2D and once in 3D-and that by using the properties of the skeletons we can identify most of the watercourses. We have implemented our methodology and tested it for three different soil types around Utrecht, the Netherlands. We were able to detect 98% of the watercourses for one soil type, and around 75% for the worst case, when we compared to a reference dataset that was obtained semi-automatically.

Maritime over the Horizon Sensor Integration: High Frequency Surface-Wave-Radar and Automatic Identification System Data Integration Algorithm.

Science.gov (United States)

Nikolic, Dejan; Stojkovic, Nikola; Lekic, Nikola

2018-04-09

To obtain the complete operational picture of the maritime situation in the Exclusive Economic Zone (EEZ) which lies over the horizon (OTH) requires the integration of data obtained from various sensors. These sensors include: high frequency surface-wave-radar (HFSWR), satellite automatic identification system (SAIS) and land automatic identification system (LAIS). The algorithm proposed in this paper utilizes radar tracks obtained from the network of HFSWRs, which are already processed by a multi-target tracking algorithm and associates SAIS and LAIS data to the corresponding radar tracks, thus forming an integrated data pair. During the integration process, all HFSWR targets in the vicinity of AIS data are evaluated and the one which has the highest matching factor is used for data association. On the other hand, if there is multiple AIS data in the vicinity of a single HFSWR track, the algorithm still makes only one data pair which consists of AIS and HFSWR data with the highest mutual matching factor. During the design and testing, special attention is given to the latency of AIS data, which could be very high in the EEZs of developing countries. The algorithm is designed, implemented and tested in a real working environment. The testing environment is located in the Gulf of Guinea and includes a network of HFSWRs consisting of two HFSWRs, several coastal sites with LAIS receivers and SAIS data provided by provider of SAIS data.

Automatic Threshold Determination for a Local Approach of Change Detection in Long-Term Signal Recordings

Directory of Open Access Journals (Sweden)

David Hewson

2007-01-01

Full Text Available CUSUM (cumulative sum is a well-known method that can be used to detect changes in a signal when the parameters of this signal are known. This paper presents an adaptation of the CUSUM-based change detection algorithms to long-term signal recordings where the various hypotheses contained in the signal are unknown. The starting point of the work was the dynamic cumulative sum (DCS algorithm, previously developed for application to long-term electromyography (EMG recordings. DCS has been improved in two ways. The first was a new procedure to estimate the distribution parameters to ensure the respect of the detectability property. The second was the definition of two separate, automatically determined thresholds. One of them (lower threshold acted to stop the estimation process, the other one (upper threshold was applied to the detection function. The automatic determination of the thresholds was based on the Kullback-Leibler distance which gives information about the distance between the detected segments (events. Tests on simulated data demonstrated the efficiency of these improvements of the DCS algorithm.

Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

Science.gov (United States)

Hübl, Johannes; McArdell, Brian W.; Walter, Fabian

2018-01-01

The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz), several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio. PMID:29789449

Automatic Identification of Alpine Mass Movements by a Combination of Seismic and Infrasound Sensors

Directory of Open Access Journals (Sweden)

Andreas Schimmel

2018-05-01

Full Text Available The automatic detection and identification of alpine mass movements such as debris flows, debris floods, or landslides have been of increasing importance for devising mitigation measures in densely populated and intensively used alpine regions. Since these mass movements emit characteristic seismic and acoustic waves in the low-frequency range (<30 Hz, several approaches have already been developed for detection and warning systems based on these signals. However, a combination of the two methods, for improving detection probability and reducing false alarms, is still applied rarely. This paper presents an update and extension of a previously published approach for a detection and identification system based on a combination of seismic and infrasound sensors. Furthermore, this work evaluates the possible early warning times at several test sites and aims to analyze the seismic and infrasound spectral signature produced by different sediment-related mass movements to identify the process type and estimate the magnitude of the event. Thus, this study presents an initial method for estimating the peak discharge and total volume of debris flows based on infrasound data. Tests on several catchments show that this system can detect and identify mass movements in real time directly at the sensor site with high accuracy and a low false alarm ratio.

Automatic mental heath assistant : monitoring and measuring nonverbal behavior of the crew during long-term missions

NARCIS (Netherlands)

Voynarovskaya, N.; Gorbunov, R.D.; Barakova, E.I.; Rauterberg, G.W.M.; Barakova, E.I.; Ruyter, B.; Spink, A.

2010-01-01

This paper presents a method for monitoring the mental state of small isolated crews during long-term missions (such as space mission, polar expeditions, submarine crews, meteorological stations, and etc.) The research is done as a part of Automatic Mental Health Assistant (AMHA) project which aims

Visible and NIR spectral band combination to produce high security ID tags for automatic identification

Science.gov (United States)

Pérez-Cabré, Elisabet; Millán, María S.; Javidi, Bahram

2006-09-01

Verification of a piece of information and/or authentication of a given object or person are common operations carried out by automatic security systems that can be applied, for instance, to control the entrance to restricted areas, access to public buildings, identification of cardholders, etc. Vulnerability of such security systems may depend on the ease of counterfeiting the information used as a piece of identification for verification and authentication. To protect data against tampering, the signature that identifies an object is usually encrypted to avoid an easy recognition at human sight and an easy reproduction using conventional devices for imaging or scanning. To make counterfeiting even more difficult, we propose to combine data from visible and near infrared (NIR) spectral bands. By doing this, neither the visible content nor the NIR data by theirselves are sufficient to allow the signature recognition and thus, the identification of a given object. Only the appropriate combination of both signals permits a satisfactory authentication. In addition, the resulting signature is encrypted following a fully-phase encryption technique and the obtained complex-amplitude distribution is encoded on an ID tag. Spatial multiplexing of the encrypted signature allows us to build a distortion-invariant ID tag, so that remote authentication can be achieved even if the tag is captured under rotation or at different distances. We also explore the possibility of using partial information of the encrypted signature to simplify the ID tag design.

Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.

Science.gov (United States)

Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; He, Yongqun

2015-01-01

It is time-consuming to build an ontology with many terms and axioms. Thus it is desired to automate the process of ontology development. Ontology Design Patterns (ODPs) provide a reusable solution to solve a recurrent modeling problem in the context of ontology engineering. Because ontology terms often follow specific ODPs, the Ontology for Biomedical Investigations (OBI) developers proposed a Quick Term Templates (QTTs) process targeted at generating new ontology classes following the same pattern, using term templates in a spreadsheet format. Inspired by the ODPs and QTTs, the Ontorat web application is developed to automatically generate new ontology terms, annotations of terms, and logical axioms based on a specific ODP(s). The inputs of an Ontorat execution include axiom expression settings, an input data file, ID generation settings, and a target ontology (optional). The axiom expression settings can be saved as a predesigned Ontorat setting format text file for reuse. The input data file is generated based on a template file created by a specific ODP (text or Excel format). Ontorat is an efficient tool for ontology expansion. Different use cases are described. For example, Ontorat was applied to automatically generate over 1,000 Japan RIKEN cell line cell terms with both logical axioms and rich annotation axioms in the Cell Line Ontology (CLO). Approximately 800 licensed animal vaccines were represented and annotated in the Vaccine Ontology (VO) by Ontorat. The OBI team used Ontorat to add assay and device terms required by ENCODE project. Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology. A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development. With ever increasing ontology development and applications, Ontorat provides a timely platform for generating and annotating a large number of ontology terms by following

Adoption of automatic identification systems by grocery retailersin the Johannesburg area

Directory of Open Access Journals (Sweden)

Christopher C. Darlington

2011-11-01

Full Text Available Retailers not only need the right data capture technology to meet the requirements of their applications, they must also decide on what the optimum technology is from the different symbologies that have been developed over the years. Automatic identification systems (AIS are a priority to decision makers as they attempt to obtain the best blend of equipment to ensure greater loss prevention and higher reliability in data capture. However there is a risk of having too simplistic a view of adopting AIS, since no one solution is applicable across an industry or business model. This problem is addressed through an exploratory, descriptive study, where the nature and value of AIS adoption by grocery retailers in the Johannesburg area is interrogated. Mixed empirical results indicate that, as retailers adopt AIS in order to improve their supply chain management systems, different types of applications are associated with various constraints and opportunities. Overall this study is in line with previous research that supports the notion that supply chain decisions are of a strategic nature even though efficient management of information is a day-to-day business operational decision.

Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads.

Science.gov (United States)

Giuliani, C; Agostinelli, A; Di Nardo, F; Fioretti, S; Burattini, L

2016-01-01

Electrocardiographic (ECG) T-wave endpoint (Tend) identification suffers lack of reliability due to the presence of noise and variability among leads. Tend identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve Tend identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable Tend identification. To this aim Tend measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that Tend distributions have not statistically different median values (CHS: 340 ms vs. 340 ms, respectively; AMIP: 325 ms vs. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; Pautomatic Tend identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the Tend determination from 15 dependent lead DTWs.

Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks.

Science.gov (United States)

Zazo, Ruben; Lozano-Diez, Alicia; Gonzalez-Dominguez, Javier; Toledano, Doroteo T; Gonzalez-Rodriguez, Joaquin

2016-01-01

Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.

Short-Term Load Forecasting Based Automatic Distribution Network Reconfiguration: Preprint

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-07-26

In the traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of load forecasting technique can provide accurate prediction of load power that will happen in future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during the longer time period instead of using the snapshot of load at the time when the reconfiguration happens, and thus it can provide information to the distribution system operator (DSO) to better operate the system reconfiguration to achieve optimal solutions. Thus, this paper proposes a short-term load forecasting based approach for automatically reconfiguring distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with support vector regression (SVR) based forecaster and parallel parameters optimization. And the network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum loss at the future time. The simulation results validate and evaluate the proposed approach.

Neural Bases of Automaticity

Science.gov (United States)

Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.

2018-01-01

Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

REMI and ROUSE: Quantitative Models for Long-Term and Short-Term Priming in Perceptual Identification

NARCIS (Netherlands)

E.J. Wagenmakers (Eric-Jan); R. Zeelenberg (René); D.E. Huber (David); J.G.W. Raaijmakers (Jeroen)

2003-01-01

textabstractThe REM model originally developed for recognition memory (Shiffrin & Steyvers, 1997) has recently been extended to implicit memory phenomena observed during threshold identification of words. We discuss two REM models based on Bayesian principles: a model for long-term priming (REMI;

Ferenczi's concept of identification with the aggressor: understanding dissociative structure with interacting victim and abuser self-states.

Science.gov (United States)

Howell, Elizabeth F

2014-03-01

No one has described more passionately than Ferenczi the traumatic induction of dissociative trance with its resulting fragmentation of the personality. Ferenczi introduced the concept and term, identification with the aggressor in his seminal "Confusion of Tongues" paper, in which he described how the abused child becomes transfixed and robbed of his senses. Having been traumatically overwhelmed, the child becomes hypnotically transfixed by the aggressor's wishes and behavior, automatically identifying by mimicry rather than by a purposeful identification with the aggressor's role. To expand upon Ferenczi's observations, identification with the aggressor can be understood as a two-stage process. The first stage is automatic and initiated by trauma, but the second stage is defensive and purposeful. While identification with the aggressor begins as an automatic organismic process, with repeated activation and use, gradually it becomes a defensive process. Broadly, as a dissociative defense, it has two enacted relational parts, the part of the victim and the part of the aggressor. This paper describes the intrapersonal aspects (how aggressor and victim self-states interrelate in the internal world), as well as the interpersonal aspects (how these become enacted in the external). This formulation has relevance to understanding the broad spectrum of the dissociative structure of mind, borderline personality disorder, and dissociative identity disorder.

Terminology of the public relations field: corpus — automatic term recognition — terminology database

Directory of Open Access Journals (Sweden)

Nataša Logar Berginc

2013-12-01

Full Text Available The article describes an analysis of automatic term recognition results performed for single- and multi-word terms with the LUIZ term extraction system. The target application of the results is a terminology database of Public Relations and the main resource the KoRP Public Relations Corpus. Our analysis is focused on two segments: (a single-word noun term candidates, which we compare with the frequency list of nouns from KoRP and evaluate termhood on the basis of the judgements of two domain experts, and (b multi-word term candidates with verb and noun as headword. In order to better assess the performance of the system and the soundness of our approach we also performed an analysis of recall. Our results show that the terminological relevance of extracted nouns is indeed higher than that of merely frequent nouns, and that verbal phrases only rarely count as proper terms. The most productive patterns of multi-word terms with noun as a headword have the following structure: [adjective + noun], [adjective + and + adjective + noun] and [adjective + adjective + noun]. The analysis of recall shows low inter-annotator agreement, but nevertheless very satisfactory recall levels.

Automatic identification of temporal sequences in chewing sounds

NARCIS (Netherlands)

Amft, O.D.; Kusserow, M.; Tröster, G.

2007-01-01

Chewing is an essential part of food intake. The analysis and detection of food patterns is an important component of an automatic dietary monitoring system. However chewing is a time-variable process depending on food properties. We present an automated methodology to extract sub-sequences of

Automatic and controlled processing in sentence recall: The role of long-term and working memory

OpenAIRE

Jefferies, Elizabeth; Lambon Ralph, Matthew A.; Baddeley, Alan D.

2004-01-01

Immediate serial recall is better for sentences than word lists presumably because of the additional support that meaningful material receives from long-term memory. This may occur automatically, without the involvement of attention, or may require additional attentionally demanding processing. For example, the episodic buffer model (Baddeley, 2000) proposes that the executive component of working memory plays a crucial role in the formation of links between different representational formats...

Benefit Analyses of Technologies for Automatic Identification to Be Implemented in the Healthcare Sector

Science.gov (United States)

Krey, Mike; Schlatter, Ueli

The tasks and objectives of automatic identification (Auto-ID) are to provide information on goods and products. It has already been established for years in the areas of logistics and trading and can no longer be ignored by the German healthcare sector. Some German hospitals have already discovered the capabilities of Auto-ID. Improvements in quality, safety and reductions in risk, cost and time are aspects and areas where improvements are achievable. Privacy protection, legal restraints, and the personal rights of patients and staff members are just a few aspects which make the heath care sector a sensible field for the implementation of Auto-ID. Auto-ID in this context contains the different technologies, methods and products for the registration, provision and storage of relevant data. With the help of a quantifiable and science-based evaluation, an answer is sought as to which Auto-ID has the highest capability to be implemented in healthcare business.

Automatic fault extraction using a modified ant-colony algorithm

International Nuclear Information System (INIS)

Zhao, Junsheng; Sun, Sam Zandong

2013-01-01

The basis of automatic fault extraction is seismic attributes, such as the coherence cube which is always used to identify a fault by the minimum value. The biggest challenge in automatic fault extraction is noise, including that of seismic data. However, a fault has a better spatial continuity in certain direction, which makes it quite different from noise. Considering this characteristic, a modified ant-colony algorithm is introduced into automatic fault identification and tracking, where the gradient direction and direction consistency are used as constraints. Numerical model test results show that this method is feasible and effective in automatic fault extraction and noise suppression. The application of field data further illustrates its validity and superiority. (paper)

Fuel number identification method and device

International Nuclear Information System (INIS)

Doi, Takami; Seno, Makoto; Kikuchi, Takashi; Sakamoto, Hiromi; Takahashi, Masaki; Tanaka, Keiji.

1997-01-01

The present invention provides a method of and a device for automatically identifying fuel numbers impressed on fuel assemblies disposed in a fuel reprocessing facility, power plant and a reactor core at a high speed and at a high identification rate. Namely, three or more character images are photographed for one fuel assembly as an object of the identification under different illumination conditions. As a result, different character images by the number of the illumination directions can be obtained for identical impressed characters. Learning on a neural network system is applied to the images of all of the characters impressed on the fuel assembly obtained under illumination of predetermined directions. Then, result of the identification by the number of the illumination directions can be obtained for each of the characters as an object of the identification. As a result, since the result of the identification is determined based on a theory of decision of majority, highly automatic identification can be realized. (I.S.)

AUTOMATIC RECOGNITION OF CORONAL TYPE II RADIO BURSTS: THE AUTOMATED RADIO BURST IDENTIFICATION SYSTEM METHOD AND FIRST OBSERVATIONS

International Nuclear Information System (INIS)

Lobzin, Vasili V.; Cairns, Iver H.; Robinson, Peter A.; Steward, Graham; Patterson, Garth

2010-01-01

Major space weather events such as solar flares and coronal mass ejections are usually accompanied by solar radio bursts, which can potentially be used for real-time space weather forecasts. Type II radio bursts are produced near the local plasma frequency and its harmonic by fast electrons accelerated by a shock wave moving through the corona and solar wind with a typical speed of ∼1000 km s -1 . The coronal bursts have dynamic spectra with frequency gradually falling with time and durations of several minutes. This Letter presents a new method developed to detect type II coronal radio bursts automatically and describes its implementation in an extended Automated Radio Burst Identification System (ARBIS 2). Preliminary tests of the method with spectra obtained in 2002 show that the performance of the current implementation is quite high, ∼80%, while the probability of false positives is reasonably low, with one false positive per 100-200 hr for high solar activity and less than one false event per 10000 hr for low solar activity periods. The first automatically detected coronal type II radio burst is also presented.

A computer program for automatic gamma-ray spectra analysis with isotope identification for the purpose of activation analysis

International Nuclear Information System (INIS)

Weigel, H.; Dauk, J.

1974-01-01

A FORTRAN IV program for a PDP-9 computer, with 16K storage capacity, is developed performing automatic analysis of complex gamma-spectra, taken with Ge/Li/ detectors. It searches for full energy peaks and evaluates the peak areas. The program features and automatically performed isotope identifiaction. It is written in such a flexible manner that after reactor irradiation, spectra from samples of any composition can be evaluated for activation analysis. The peak search rutin is based on the following criteria: the counting rate has to increase for two succesive channels; and the amplitude of the corresponding maximum has to be greater than/or equal to F 1 times the statistical error of the counting rate in the valley just before the maximum. In order to detect superimposed peaks, it is assumed that the dependence of FWHM on channel number is roughly approximated by a linear function, and the actual and''theoretical''FWHM values are compared. To determine the net peak area a Gaussian based function is fitted to each peak. The isotope identification is based on the procedure developed by ADAMS and DAMS. (T.G.)

Automatic and rapid identification of glycopeptides by nano-UPLC-LTQ-FT-MS and proteomic search engine.

Science.gov (United States)

Giménez, Estela; Gay, Marina; Vilaseca, Marta

2017-01-30

Here we demonstrate the potential of nano-UPLC-LTQ-FT-MS and the Byonic™ proteomic search engine for the separation, detection, and identification of N- and O-glycopeptide glycoforms in standard glycoproteins. The use of a BEH C18 nanoACQUITY column allowed the separation of the glycopeptides present in the glycoprotein digest and a baseline-resolution of the glycoforms of the same glycopeptide on the basis of the number of sialic acids. Moreover, we evaluated several acquisition strategies in order to improve the detection and characterization of glycopeptide glycoforms with the maximum number of identification percentages. The proposed strategy is simple to set up with the technology platforms commonly used in proteomic labs. The method allows the straightforward and rapid obtention of a general glycosylated map of a given protein, including glycosites and their corresponding glycosylated structures. The MS strategy selected in this work, based on a gas phase fractionation approach, led to 136 unique peptides from four standard proteins, which represented 78% of the total number of peptides identified. Moreover, the method does not require an extra glycopeptide enrichment step, thus preventing the bias that this step could cause towards certain glycopeptide species. Data are available via ProteomeXchange with identifier PXD003578. We propose a simple and high-throughput glycoproteomics-based methodology that allows the separation of glycopeptide glycoforms on the basis of the number of sialic acids, and their automatic and rapid identification without prior knowledge of protein glycosites or type and structure of the glycans. Copyright © 2016 Elsevier B.V. All rights reserved.

12th Portuguese Conference on Automatic Control

CERN Document Server

Soares, Filomena; Moreira, António

2017-01-01

The biennial CONTROLO conferences are the main events promoted by The CONTROLO 2016 – 12th Portuguese Conference on Automatic Control, Guimarães, Portugal, September 14th to 16th, was organized by Algoritmi, School of Engineering, University of Minho, in partnership with INESC TEC, and promoted by the Portuguese Association for Automatic Control – APCA, national member organization of the International Federation of Automatic Control – IFAC. The seventy-five papers published in this volume cover a wide range of topics. Thirty-one of them, of a more theoretical nature, are distributed among the first five parts: Control Theory; Optimal and Predictive Control; Fuzzy, Neural and Genetic Control; Modeling and Identification; Sensing and Estimation. The papers go from cutting-edge theoretical research to innovative control applications and show expressively how Automatic Control can be used to increase the well being of people. .

Automatic contact in DYNA3D for vehicle crashworthiness

International Nuclear Information System (INIS)

Whirley, R.G.; Engelmann, B.E.

1994-01-01

This paper presents a new formulation for the automatic definition and treatment of mechanical contact in explicit, nonlinear, finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. The authors have used a new four-step automatic contact algorithm. Key aspects of the proposed method include (1) automatic identification of adjacent and opposite surfaces in the global search phase, and (2) the use of a smoothly varying surface normal that allows a consistent treatment of shell intersection and corner contact conditions without ad hoc rules. Three examples are given to illustrate the performance of the newly proposed algorithm in the public DYNA3D code

FragIdent--automatic identification and characterisation of cDNA-fragments.

Science.gov (United States)

Seelow, Dominik; Goehler, Heike; Hoffmann, Katrin

2009-03-02

Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available. Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs) within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones. We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at http://compbio.charite.de/genetik/FragIdent/.

Automatic topics segmentation for TV news video

Science.gov (United States)

Hmayda, Mounira; Ejbali, Ridha; Zaied, Mourad

2017-03-01

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

A support vector machine approach to the automatic identification of fluorescence spectra emitted by biological agents

Science.gov (United States)

Gelfusa, M.; Murari, A.; Lungaroni, M.; Malizia, A.; Parracino, S.; Peluso, E.; Cenciarelli, O.; Carestia, M.; Pizzoferrato, R.; Vega, J.; Gaudio, P.

2016-10-01

Two of the major new concerns of modern societies are biosecurity and biosafety. Several biological agents (BAs) such as toxins, bacteria, viruses, fungi and parasites are able to cause damage to living systems either humans, animals or plants. Optical techniques, in particular LIght Detection And Ranging (LIDAR), based on the transmission of laser pulses and analysis of the return signals, can be successfully applied to monitoring the release of biological agents into the atmosphere. It is well known that most of biological agents tend to emit specific fluorescence spectra, which in principle allow their detection and identification, if excited by light of the appropriate wavelength. For these reasons, the detection of the UVLight Induced Fluorescence (UV-LIF) emitted by BAs is particularly promising. On the other hand, the stand-off detection of BAs poses a series of challenging issues; one of the most severe is the automatic discrimination between various agents which emit very similar fluorescence spectra. In this paper, a new data analysis method, based on a combination of advanced filtering techniques and Support Vector Machines, is described. The proposed approach covers all the aspects of the data analysis process, from filtering and denoising to automatic recognition of the agents. A systematic series of numerical tests has been performed to assess the potential and limits of the proposed methodology. The first investigations of experimental data have already given very encouraging results.

Semi-automatic identification of punching areas for tissue microarray building: the tubular breast cancer pilot study

Directory of Open Access Journals (Sweden)

Beltrame Francesco

2010-11-01

Full Text Available Abstract Background Tissue MicroArray technology aims to perform immunohistochemical staining on hundreds of different tissue samples simultaneously. It allows faster analysis, considerably reducing costs incurred in staining. A time consuming phase of the methodology is the selection of tissue areas within paraffin blocks: no utilities have been developed for the identification of areas to be punched from the donor block and assembled in the recipient block. Results The presented work supports, in the specific case of a primary subtype of breast cancer (tubular breast cancer, the semi-automatic discrimination and localization between normal and pathological regions within the tissues. The diagnosis is performed by analysing specific morphological features of the sample such as the absence of a double layer of cells around the lumen and the decay of a regular glands-and-lobules structure. These features are analysed using an algorithm which performs the extraction of morphological parameters from images and compares them to experimentally validated threshold values. Results are satisfactory since in most of the cases the automatic diagnosis matches the response of the pathologists. In particular, on a total of 1296 sub-images showing normal and pathological areas of breast specimens, algorithm accuracy, sensitivity and specificity are respectively 89%, 84% and 94%. Conclusions The proposed work is a first attempt to demonstrate that automation in the Tissue MicroArray field is feasible and it can represent an important tool for scientists to cope with this high-throughput technique.

The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation

Science.gov (United States)

Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.

2017-12-01

In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long-term

Precision about the automatic emotional brain.

Science.gov (United States)

Vuilleumier, Patrik

2015-01-01

The question of automaticity in emotion processing has been debated under different perspectives in recent years. Satisfying answers to this issue will require a better definition of automaticity in terms of relevant behavioral phenomena, ecological conditions of occurrence, and a more precise mechanistic account of the underlying neural circuits.

Suspect/foil identification in actual crimes and in the laboratory: a reality monitoring analysis.

Science.gov (United States)

Behrman, Bruce W; Richards, Regina E

2005-06-01

Four reality monitoring variables were used to discriminate suspect from foil identifications in 183 actual criminal cases. Four hundred sixty-one identification attempts based on five and six-person lineups were analyzed. These identification attempts resulted in 238 suspect identifications and 68 foil identifications. Confidence, automatic processing, eliminative processing and feature use comprised the set of reality monitoring variables. Thirty-five verbal confidence phrases taken from police reports were assigned numerical values on a 10-point confidence scale. Automatic processing identifications were those that occurred "immediately" or "without hesitation." Eliminative processing identifications occurred when witnesses compared or eliminated persons in the lineups. Confidence, automatic processing and eliminative processing were significant predictors, but feature use was not. Confidence was the most effective discriminator. In cases that involved substantial evidence extrinsic to the identification 43% of the suspect identifications were made with high confidence, whereas only 10% of the foil identifications were made with high confidence. The results of a laboratory study using the same predictors generally paralleled the archival results. Forensic implications are discussed.

Automatic temporal segment detection via bilateral long short-term memory recurrent neural networks

Science.gov (United States)

Sun, Bo; Cao, Siming; He, Jun; Yu, Lejun; Li, Liandong

2017-03-01

Constrained by the physiology, the temporal factors associated with human behavior, irrespective of facial movement or body gesture, are described by four phases: neutral, onset, apex, and offset. Although they may benefit related recognition tasks, it is not easy to accurately detect such temporal segments. An automatic temporal segment detection framework using bilateral long short-term memory recurrent neural networks (BLSTM-RNN) to learn high-level temporal-spatial features, which synthesizes the local and global temporal-spatial information more efficiently, is presented. The framework is evaluated in detail over the face and body database (FABO). The comparison shows that the proposed framework outperforms state-of-the-art methods for solving the problem of temporal segment detection.

Automatisms: bridging clinical neurology with criminal law.

Science.gov (United States)

Rolnick, Joshua; Parvizi, Josef

2011-03-01

The law, like neurology, grapples with the relationship between disease states and behavior. Sometimes, the two disciplines share the same terminology, such as automatism. In law, the "automatism defense" is a claim that action was involuntary or performed while unconscious. Someone charged with a serious crime can acknowledge committing the act and yet may go free if, relying on the expert testimony of clinicians, the court determines that the act of crime was committed in a state of automatism. In this review, we explore the relationship between the use of automatism in the legal and clinical literature. We close by addressing several issues raised by the automatism defense: semantic ambiguity surrounding the term automatism, the presence or absence of consciousness during automatisms, and the methodological obstacles that have hindered the study of cognition during automatisms. Copyright © 2010 Elsevier Inc. All rights reserved.

Modified automatic term selection v2: A faster algorithm to calculate inelastic scattering cross-sections

Energy Technology Data Exchange (ETDEWEB)

Rusz, Ján, E-mail: jan.rusz@fysik.uu.se

2017-06-15

Highlights: • New algorithm for calculating double differential scattering cross-section. • Shown good convergence properties. • Outperforms older MATS algorithm, particularly in zone axis calculations. - Abstract: We present a new algorithm for calculating inelastic scattering cross-section for fast electrons. Compared to the previous Modified Automatic Term Selection (MATS) algorithm (Rusz et al. [18]), it has far better convergence properties in zone axis calculations and it allows to identify contributions of individual atoms. One can think of it as a blend of MATS algorithm and a method described by Weickenmeier and Kohl [10].

Automatic tracking of wake vortices using ground-wind sensor data

Science.gov (United States)

1977-01-03

Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

Science.gov (United States)

2010-01-01

Background Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships. Results We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation. Conclusions We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider.com/ and the Chemlist dictionary is freely available as an XML file in

Automatic Bayesian single molecule identification for localization microscopy

OpenAIRE

Tang, Yunqing; Hendriks, Johnny; Gensch, Thomas; Dai, Luru; Li, Junbai

2016-01-01

Single molecule localization microscopy (SMLM) is on its way to become a mainstream imaging technique in the life sciences. However, analysis of SMLM data is biased by user provided subjective parameters required by the analysis software. To remove this human bias we introduce here the Auto-Bayes method that executes the analysis of SMLM data automatically. We demonstrate the success of the method using the photoelectron count of an emitter as selection characteristic. Moreover, the principle...

Automatic generation of warehouse mediators using an ontology engine

Energy Technology Data Exchange (ETDEWEB)

Critchlow, T., LLNL

1998-04-01

Data warehouses created for dynamic scientific environments, such as genetics, face significant challenges to their long-term feasibility One of the most significant of these is the high frequency of schema evolution resulting from both technological advances and scientific insight Failure to quickly incorporate these modifications will quickly render the warehouse obsolete, yet each evolution requires significant effort to ensure the changes are correctly propagated DataFoundry utilizes a mediated warehouse architecture with an ontology infrastructure to reduce the maintenance acquirements of a warehouse. Among the things, the ontology is used as an information source for automatically generating mediators, the methods that transfer data between the data sources and the warehouse The identification, definition and representation of the metadata required to perform this task is a primary contribution of this work.

Investigation of an automatic trim algorithm for restructurable aircraft control

Science.gov (United States)

Weiss, J.; Eterno, J.; Grunberg, D.; Looze, D.; Ostroff, A.

1986-01-01

This paper develops and solves an automatic trim problem for restructurable aircraft control. The trim solution is applied as a feed-forward control to reject measurable disturbances following control element failures. Disturbance rejection and command following performances are recovered through the automatic feedback control redesign procedure described by Looze et al. (1985). For this project the existence of a failure detection mechanism is assumed, and methods to cope with potential detection and identification inaccuracies are addressed.

The power grid AGC frequency bias coefficient online identification method based on wide area information

Science.gov (United States)

Wang, Zian; Li, Shiguang; Yu, Ting

2015-12-01

This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

Automatic operation device for control rods

International Nuclear Information System (INIS)

Sekimizu, Koichi

1984-01-01

Purpose: To enable automatic operation of control rods based on the reactor operation planning, and particularly, to decrease the operator's load upon start up and shutdown of the reactor. Constitution: Operation plannings, demand for the automatic operation, break point setting value, power and reactor core flow rate change, demand for operation interrupt, demand for restart, demand for forecasting and the like are inputted to an input device, and an overall judging device performs a long-term forecast as far as the break point by a long-term forecasting device based on the operation plannings. The automatic reactor operation or the like is carried out based on the long-term forecasting and the short time forecasting is performed by the change in the reactor core status due to the control rod operation sequence based on the control rod pattern and the operation planning. Then, it is judged if the operation for the intended control rod is possible or not based on the result of the short time forecasting. (Aizawa, K.)

[The maintenance of automatic analysers and associated documentation].

Science.gov (United States)

Adjidé, V; Fournier, P; Vassault, A

2010-12-01

The maintenance of automatic analysers and associated documentation taking part in the requirements of the ISO 15189 Standard and the French regulation as well have to be defined in the laboratory policy. The management of the periodic maintenance and documentation shall be implemented and fulfilled. The organisation of corrective maintenance has to be managed to avoid interruption of the task of the laboratory. The different recommendations concern the identification of materials including automatic analysers, the environmental conditions to take into account, the documentation provided by the manufacturer and documents prepared by the laboratory including procedures for maintenance.

Integration of low level and ontology derived features for automatic weapon recognition and identification

Science.gov (United States)

Sirakov, Nikolay M.; Suh, Sang; Attardo, Salvatore

2011-06-01

This paper presents a further step of a research toward the development of a quick and accurate weapons identification methodology and system. A basic stage of this methodology is the automatic acquisition and updating of weapons ontology as a source of deriving high level weapons information. The present paper outlines the main ideas used to approach the goal. In the next stage, a clustering approach is suggested on the base of hierarchy of concepts. An inherent slot of every node of the proposed ontology is a low level features vector (LLFV), which facilitates the search through the ontology. Part of the LLFV is the information about the object's parts. To partition an object a new approach is presented capable of defining the objects concavities used to mark the end points of weapon parts, considered as convexities. Further an existing matching approach is optimized to determine whether an ontological object matches the objects from an input image. Objects from derived ontological clusters will be considered for the matching process. Image resizing is studied and applied to decrease the runtime of the matching approach and investigate its rotational and scaling invariance. Set of experiments are preformed to validate the theoretical concepts.

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

Long term Suboxone™ emotional reactivity as measured by automatic detection in speech.

Directory of Open Access Journals (Sweden)

Edward Hill

Full Text Available Addictions to illicit drugs are among the nation's most critical public health and societal problems. The current opioid prescription epidemic and the need for buprenorphine/naloxone (Suboxone®; SUBX as an opioid maintenance substance, and its growing street diversion provided impetus to determine affective states ("true ground emotionality" in long-term SUBX patients. Toward the goal of effective monitoring, we utilized emotion-detection in speech as a measure of "true" emotionality in 36 SUBX patients compared to 44 individuals from the general population (GP and 33 members of Alcoholics Anonymous (AA. Other less objective studies have investigated emotional reactivity of heroin, methadone and opioid abstinent patients. These studies indicate that current opioid users have abnormal emotional experience, characterized by heightened response to unpleasant stimuli and blunted response to pleasant stimuli. However, this is the first study to our knowledge to evaluate "true ground" emotionality in long-term buprenorphine/naloxone combination (Suboxone™. We found in long-term SUBX patients a significantly flat affect (p<0.01, and they had less self-awareness of being happy, sad, and anxious compared to both the GP and AA groups. We caution definitive interpretation of these seemingly important results until we compare the emotional reactivity of an opioid abstinent control using automatic detection in speech. These findings encourage continued research strategies in SUBX patients to target the specific brain regions responsible for relapse prevention of opioid addiction.

Fast automatic analysis of antenatal dexamethasone on micro-seizure activity in the EEG

International Nuclear Information System (INIS)

Rastin, S.J.; Unsworth, C.P.; Bennet, L.

2010-01-01

Full text: In this work wc develop an automatic scheme for studying the effect of the antenatal Dexamethasone on the EEG activity. To do so an FFT (Fast Fourier Transform) based detector was designed and applied to the EEG recordings obtained from two groups of fetal sheep. Both groups received two injections with a time delay of 24 h between them. However the applied medicine was different for each group (Dex and saline). The detector developed was used to automatically identify and classify micro-seizures that occurred in the frequency bands corresponding to the EEG transients known as slow waves (2.5 14 Hz). For each second of the data recordings the spectrum was computed and the rise of the energy in each predefined frequency band then counted when the energy level exceeded a predefined corresponding threshold level (Where the threshold level was obtained from the long term average of the spectral points at each band). Our results demonstrate that it was possible to automatically count the micro-seizures for the three different bands in a time effective manner. It was found that the number of transients did not strongly depend on the nature of the injected medicine which was consistent with the results manually obtained by an EEG expert. Tn conclusion, the automatic detection scheme presented here would allow for rapid micro-seizure event identification of hours of highly sampled EEG data thus providing a valuable time-saving device.

Automatic welding and cladding in heavy fabrication

International Nuclear Information System (INIS)

Altamer, A. de

1980-01-01

A description is given of the automatic welding processes used by an Italian fabricator of pressure vessels for petrochemical and nuclear plant. The automatic submerged arc welding, submerged arc strip cladding, pulsed TIG, hot wire TIG and MIG welding processes have proved satisfactory in terms of process reliability, metal deposition rate, and cost effectiveness for low alloy and carbon steels. An example shows sequences required during automatic butt welding, including heat treatments. Factors which govern satisfactory automatic welding include automatic anti-drift rotator device, electrode guidance and bead programming system, the capability of single and dual head operation, flux recovery and slag removal systems, operator environment and controls, maintaining continuity of welding and automatic reverse side grinding. Automatic welding is used for: joining vessel sections; joining tubes to tubeplate; cladding of vessel rings and tubes, dished ends and extruded nozzles; nozzle to shell and butt welds, including narrow gap welding. (author)

Who identifies with suicidal film characters? Determinants of identification with suicidal protagonists of drama films.

Science.gov (United States)

Till, Benedikt; Herberth, Arno; Sonneck, Gernot; Vitouch, Peter; Niederkrotenthaler, Thomas

2013-06-01

Identification with a media character is an influential factor for the effects of a media product on the recipient, but still very little is known about this cognitive process. This study investigated to what extent identification of a recipient with the suicidal protagonist of a film drama is influenced by the similarity between them in terms of sex, age, and education as well as by the viewer's empathy and suicidality. Sixty adults were assigned randomly to one of two film groups. Both groups watched a drama that concluded with the tragic suicide of the protagonist. Identification, empathy, suicidality, as well as socio-demographic data were measured by questionnaires that were applied before and after the movie screening. Results indicated that identification was not associated with socio-demographic similarity or the viewer's suicidality. However, the greater the subjects' empathy was, the more they identified with the protagonist in one of the two films. This investigation provides evidence that challenges the common assumption that identification with a film character is automatically generated when viewer and protagonist are similar in terms of sex, age, education or attitude.

Automatically ordering events and times in text

CERN Document Server

Derczynski, Leon R A

2017-01-01

The book offers a detailed guide to temporal ordering, exploring open problems in the field and providing solutions and extensive analysis. It addresses the challenge of automatically ordering events and times in text. Aided by TimeML, it also describes and presents concepts relating to time in easy-to-compute terms. Working out the order that events and times happen has proven difficult for computers, since the language used to discuss time can be vague and complex. Mapping out these concepts for a computational system, which does not have its own inherent idea of time, is, unsurprisingly, tough. Solving this problem enables powerful systems that can plan, reason about events, and construct stories of their own accord, as well as understand the complex narratives that humans express and comprehend so naturally. This book presents a theory and data-driven analysis of temporal ordering, leading to the identification of exactly what is difficult about the task. It then proposes and evaluates machine-learning so...

Automatic Detection of Fake News

OpenAIRE

Pérez-Rosas, Verónica; Kleinberg, Bennett; Lefevre, Alexandra; Mihalcea, Rada

2017-01-01

The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. In this paper, we focus on the automatic identification of fake content in online news. Our contribution is twofold. First, we introduce two novel datasets for the task of fake news...

Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae).

Science.gov (United States)

Wang, Jiang-Ning; Chen, Xiao-Lin; Hou, Xin-Wen; Zhou, Li-Bing; Zhu, Chao-Dong; Ji, Li-Qiang

2017-07-01

Many species of Tephritidae are damaging to fruit, which might negatively impact international fruit trade. Automatic or semi-automatic identification of fruit flies are greatly needed for diagnosing causes of damage and quarantine protocols for economically relevant insects. A fruit fly image identification system named AFIS1.0 has been developed using 74 species belonging to six genera, which include the majority of pests in the Tephritidae. The system combines automated image identification and manual verification, balancing operability and accuracy. AFIS1.0 integrates image analysis and expert system into a content-based image retrieval framework. In the the automatic identification module, AFIS1.0 gives candidate identification results. Afterwards users can do manual selection based on comparing unidentified images with a subset of images corresponding to the automatic identification result. The system uses Gabor surface features in automated identification and yielded an overall classification success rate of 87% to the species level by Independent Multi-part Image Automatic Identification Test. The system is useful for users with or without specific expertise on Tephritidae in the task of rapid and effective identification of fruit flies. It makes the application of computer vision technology to fruit fly recognition much closer to production level. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Peak fitting and identification software library for high resolution gamma-ray spectra

International Nuclear Information System (INIS)

Uher, Josef; Roach, Greg; Tickner, James

2010-01-01

A new gamma-ray spectral analysis software package is under development in our laboratory. It can be operated as a stand-alone program or called as a software library from Java, C, C++ and MATLAB TM environments. It provides an advanced graphical user interface for data acquisition, spectral analysis and radioisotope identification. The code uses a peak-fitting function that includes peak asymmetry, Compton continuum and flexible background terms. Peak fitting function parameters can be calibrated as functions of energy. Each parameter can be constrained to improve fitting of overlapping peaks. All of these features can be adjusted by the user. To assist with peak identification, the code can automatically measure half-lives of single or multiple overlapping peaks from a time series of spectra. It implements library-based peak identification, with options for restricting the search based on radioisotope half-lives and reaction types. The software also improves the reliability of isotope identification by utilizing Monte-Carlo simulation results.

A new methodology for automatic detection of reference points in 3D cephalometry: A pilot study.

Science.gov (United States)

Ed-Dhahraouy, Mohammed; Riri, Hicham; Ezzahmouly, Manal; Bourzgui, Farid; El Moutaoukkil, Abdelmajid

2018-04-05

The aim of this study was to develop a new method for an automatic detection of reference points in 3D cephalometry to overcome the limits of 2D cephalometric analyses. A specific application was designed using the C++ language for automatic and manual identification of 21 (reference) points on the craniofacial structures. Our algorithm is based on the implementation of an anatomical and geometrical network adapted to the craniofacial structure. This network was constructed based on the anatomical knowledge of the 3D cephalometric (reference) points. The proposed algorithm was tested on five CBCT images. The proposed approach for the automatic 3D cephalometric identification was able to detect 21 points with a mean error of 2.32mm. In this pilot study, we propose an automated methodology for the identification of the 3D cephalometric (reference) points. A larger sample will be implemented in the future to assess the method validity and reliability. Copyright © 2018 CEO. Published by Elsevier Masson SAS. All rights reserved.

Identification of Units and Other Terms in Czech Medical Records

Czech Academy of Sciences Publication Activity Database

Zvára Jr., Karel; Kašpar, Václav

2010-01-01

Roč. 6, č. 1 (2010), s. 78-82 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : natural language processing * healthcare documentation * medical reports * EHR * finite-state machine * regular expression Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/en/ejbi/article/61-en-identification-of-units-and-other-terms-in-czech-medical-records.html

A multiparametric automatic method to monitor long-term reproducibility in digital mammography: results from a regional screening programme.

Science.gov (United States)

Gennaro, G; Ballaminut, A; Contento, G

2017-09-01

This study aims to illustrate a multiparametric automatic method for monitoring long-term reproducibility of digital mammography systems, and its application on a large scale. Twenty-five digital mammography systems employed within a regional screening programme were controlled weekly using the same type of phantom, whose images were analysed by an automatic software tool. To assess system reproducibility levels, 15 image quality indices (IQIs) were extracted and compared with the corresponding indices previously determined by a baseline procedure. The coefficients of variation (COVs) of the IQIs were used to assess the overall variability. A total of 2553 phantom images were collected from the 25 digital mammography systems from March 2013 to December 2014. Most of the systems showed excellent image quality reproducibility over the surveillance interval, with mean variability below 5%. Variability of each IQI was 5%, with the exception of one index associated with the smallest phantom objects (0.25 mm), which was below 10%. The method applied for reproducibility tests-multi-detail phantoms, cloud automatic software tool to measure multiple image quality indices and statistical process control-was proven to be effective and applicable on a large scale and to any type of digital mammography system. • Reproducibility of mammography image quality should be monitored by appropriate quality controls. • Use of automatic software tools allows image quality evaluation by multiple indices. • System reproducibility can be assessed comparing current index value with baseline data. • Overall system reproducibility of modern digital mammography systems is excellent. • The method proposed and applied is cost-effective and easily scalable.

FragIdent – Automatic identification and characterisation of cDNA-fragments

Directory of Open Access Journals (Sweden)

Goehler Heike

2009-03-01

Full Text Available Abstract Background Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments. Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available. Results Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones. Conclusion We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at http://compbio.charite.de/genetik/FragIdent/.

Automatic measurement of images on astrometric plates

Science.gov (United States)

Ortiz Gil, A.; Lopez Garcia, A.; Martinez Gonzalez, J. M.; Yershov, V.

1994-04-01

We present some results on the process of automatic detection and measurement of objects in overlapped fields of astrometric plates. The main steps of our algorithm are the following: determination of the Scale and Tilt between charge coupled devices (CCD) and microscope coordinate systems and estimation of signal-to-noise ratio in each field;--image identification and improvement of its position and size;--image final centering;--image selection and storage. Several parameters allow the use of variable criteria for image identification, characterization and selection. Problems related with faint images and crowded fields will be approached by special techniques (morphological filters, histogram properties and fitting models).

Synthesis of digital locomotive receiver of automatic locomotive signaling

Directory of Open Access Journals (Sweden)

K. V. Goncharov

2013-02-01

Full Text Available Purpose. Automatic locomotive signaling of continuous type with a numeric coding (ALSN has several disadvantages: a small number of signal indications, low noise stability, high inertia and low functional flexibility. Search for new and more advanced methods of signal processing for automatic locomotive signaling, synthesis of the noise proof digital locomotive receiver are essential. Methodology. The proposed algorithm of detection and identification locomotive signaling codes is based on the definition of mutual correlations of received oscillation and reference signals. For selecting threshold levels of decision element the following criterion has been formulated: the locomotive receiver should maximum set the correct solution for a given probability of dangerous errors. Findings. It has been found that the random nature of the ALSN signal amplitude does not affect the detection algorithm. However, the distribution law and numeric characteristics of signal amplitude affect the probability of errors, and should be considered when selecting a threshold levels According to obtained algorithm of detection and identification ALSN signals the digital locomotive receiver has been synthesized. It contains band pass filter, peak limiter, normalizing amplifier with automatic gain control circuit, analog to digital converter and digital signal processor. Originality. The ALSN system is improved by the way of the transfer of technical means to modern microelectronic element base, more perfect methods of detection and identification codes of locomotive signaling are applied. Practical value. Use of digital technology in the construction of the locomotive receiver ALSN will expand its functionality, will increase the noise immunity and operation stability of the locomotive signal system in conditions of various destabilizing factors.

Cost-benefit analysis of the ATM automatic deposit service

Directory of Open Access Journals (Sweden)

Ivica Županović

2015-03-01

Full Text Available Bankers and other financial experts have analyzed the value of automated teller machines (ATM in terms of growing consumer demand, rising costs of technology development, decreasing profitability and market share. This paper presents a step-by-step cost-benefit analysis of the ATM automatic deposit service. The first step is to determine user attitudes towards using ATM automatic deposit service by using the Technology Acceptance Model (TAM. The second step is to determine location priorities for ATMs that provide automatic deposit services using the Analytic Hierarchy Process (AHP model. The results of the previous steps enable a highly efficient application of cost-benefit analysis for evaluating costs and benefits of automatic deposit services. To understand fully the proposed procedure outside of theoretical terms, a real-world application of a case study is conducted.

Identification of persons entering through the door from the accelerometers data

OpenAIRE

Vodopivec, Tadej

2013-01-01

This thesis presents a system for automatic identification of a person who walks through a door based on the information gathered with acceleration sensors, which are mounted on the door. The proccedure for automatic identification consists of four steps. In the first step, data acquisition and coordinate system rotation is performed. Coordinate system rotation is needed in order to match the direction of measured accelerations with the direction of components of the forces acting on the door...

Evaluation of a direct method for the identification and antibiotic susceptibility assessment of microrganisms isolated from blood cultures by automatic systems

Directory of Open Access Journals (Sweden)

Sergio Frugoni

2008-03-01

Full Text Available The purpose of blood cultures in the septic patient is to address a correct therapeutic approach. Identification and antibiotic susceptibility test carried out directly from the bottle may give important information in short time.The introduction of the automatic instrumentation has improved the discovering of pathogens in the blood, however the elapsing time between the positive detection and the microbiological report is still along. Is the evaluation of this study a fast, easy, cheap method to be applied to the routine, which could reduce the response time in the bacteraemia diagnosis.The automatic systems Vitek Senior (bioMérieux, and Vitek 2 (bioMérieux were used at Pio Albergo Trivulzio (Centre1 and at Istituto dei Tumori (Centre2 respectivetly.To remove blood cells, 7 ml. of the culture has been moved by vacuum sampling in a test tube and centrifuged for 10 minutes at 1000 rpm the supernatant has been further centrifuged for 10 minutes at 3000 rpm.0.5 ml. of BHI has been added to the pellet o sediment.The concentration of bacterial suspension has been fit for the inoculation. At the same time has been prepared standard cultures in suitable culture media were carried out for comparison. In the centro1 and centro2 have been isolated and identify respectively 63 and 31 Gram negative, and, 32 and 40 gram positive microorganisms have been isolated and identify in the Centre1 and Centre2 respectively.The identification Gram-negative and Gram positive microorganisms showed an agreement of 100% and 86.2% and 93.3% and 65.78% respectively between the direct and the standard method. For antibiotic susceptibility tests, 903 (Centre1 and 491 (Centre2 and 396 and 509 compounds were totally assessed in Gram negative and Gram positive bacteria respectively.The analysis has highlighted that: Centre1 has reported 0.30% very major errors (GE, 0.92% major errors (EM, 1.23% minor errors (Em. Centre 2 showed 0.57% very major errors (GE, 0.09% major errors

Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

Energy Technology Data Exchange (ETDEWEB)

Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha (China)

2006-10-15

Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method.

Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

International Nuclear Information System (INIS)

Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P

2006-01-01

Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method

[Effects of long-term Tai Ji Quan exercise on automatic nervous modulation in the elderly].

Science.gov (United States)

Guo, Feng

2015-03-01

To examine the effects of long-term Tai Ji Quan (Chinnese Traditional Exercise) on automatic nervous modulation in the elders. The 18 subjects from Tai Ji Quan exercise class in Liaoning University of Retired Veteran Cadres were assigned into long-term Tai Ji Quan exercise group including 10 subjects and novice group including 8 subjects. Electrocardiography, respiratory and blood pressure data were collected on the following time points: at rest before Tai Ji Qhuan exercise and 30 min or 60 min after Tai Ji Quan exercise. The subjects at rest state in the long-term Tai Ji Quan exercise group showed higher than the subjects in the novice group in resperitory rate (RR), standard deviations of normal to normal intervals (SDNN), total power (TP), low frequency power (LFP), high frequency power (HFP), normalized high frequency power (nHFP), but lower in LFP/HFP, systolic and diastolic blood pressure, and heart rate. At rest state the respiratory rate of subjects in long-term Tai Ji Quan exercise group was significantly lower than the novices. After Tai Ji Quan exercise, TP, nHFP, LFP/HFP, heart rate and systolic pressure showed significantly changes, and the change level of Tai Ji Quan on these indices was larger in Tai Ji Quan exercise group than that in the novice group. Long-term Tai Ji Quan exercise can improve vagal modulations, and tend to reduce the sympathetic modulations.

Identification of alcohol abuse and transition from long-term unemployment to disability pension.

Science.gov (United States)

Nurmela, Kirsti; Heikkinen, Virpi; Hokkanen, Risto; Ylinen, Aarne; Uitti, Jukka; Mattila, Aino; Joukamaa, Matti; Virtanen, Pekka

2015-07-01

The aim of the study was to reveal potential gaps and inconsistencies in the identification of alcohol abuse in health care and in employment services and to analyse the granting of disability pensions with respect to the alcohol abuse identification pattern. The material consisted of documentary information on 505 long-term unemployed subjects with low employability sent to the development project entitled 'Eligibility for a Disability Pension' in 2001-2006 in Finland. The dichotomous variables 'Alcohol abuse identified in employment services' and 'Alcohol abuse identified in health care' were cross-tabulated to obtain a four-class variable 'Alcohol abuse identification pattern'. Logistic regression analyses were conducted to ascertain the association of alcohol abuse identification pattern with the granting of disability pensions. Alcohol abuse was detected by both health care and employment services in 47% of those identified as abusers (41% of examinees). Each service systems also identified cases that the other did not. When alcohol abuse was identified in health care only, the OR for a disability pension being granted was 2.8 (95% CI 1.5-5.2) compared with applicants without identified alcohol abuse. The result remained the same and statistically significant after adjusting for confounders. Alcohol abuse identified in health care was positively associated with the granting of a disability pension. Closer co-operation between employment services and health care could help to identify those long-term unemployed individuals with impaired work ability in need of thorough medical examination. © 2015 the Nordic Societies of Public Health.

Identity verification using computer vision for automatic garage door opening

NARCIS (Netherlands)

Wijnhoven, R.G.J.; With, de P.H.N.

2011-01-01

We present a novel system for automatic identification of vehicles as part of an intelligent access control system for a garage entrance. Using a camera in the door, cars are detected and matched to the database of authenticated cars. Once a car is detected, License Plate Recognition (LPR) is

Forensic Automatic Speaker Recognition Based on Likelihood Ratio Using Acoustic-phonetic Features Measured Automatically

Directory of Open Access Journals (Sweden)

Huapeng Wang

2015-01-01

Full Text Available Forensic speaker recognition is experiencing a remarkable paradigm shift in terms of the evaluation framework and presentation of voice evidence. This paper proposes a new method of forensic automatic speaker recognition using the likelihood ratio framework to quantify the strength of voice evidence. The proposed method uses a reference database to calculate the within- and between-speaker variability. Some acoustic-phonetic features are extracted automatically using the software VoiceSauce. The effectiveness of the approach was tested using two Mandarin databases: A mobile telephone database and a landline database. The experiment's results indicate that these acoustic-phonetic features do have some discriminating potential and are worth trying in discrimination. The automatic acoustic-phonetic features have acceptable discriminative performance and can provide more reliable results in evidence analysis when fused with other kind of voice features.

Semi-Automatic Removal of Foreground Stars from Images of Galaxies

Science.gov (United States)

Frei, Zsolt

1996-07-01

A new procedure, designed to remove foreground stars from galaxy proviles is presented here. Although several programs exist for stellar and faint object photometry, none of them treat star removal from the images very carefully. I present my attempt to develop such a system, and briefly compare the performance of my software to one of the well-known stellar photometry packages, DAOPhot (Stetson 1987). Major steps in my procedure are: (1) automatic construction of an empirical 2D point spread function from well separated stars that are situated off the galaxy; (2) automatic identification of those peaks that are likely to be foreground stars, scaling the PSF and removing these stars, and patching residuals (in the automatically determined smallest possible area where residuals are truly significant); and (3) cosmetic fix of remaining degradations in the image. The algorithm and software presented here is significantly better for automatic removal of foreground stars from images of galaxies than DAOPhot or similar packages, since: (a) the most suitable stars are selected automatically from the image for the PSF fit; (b) after star-removal an intelligent and automatic procedure removes any possible residuals; (c) unlimited number of images can be cleaned in one run without any user interaction whatsoever. (SECTION: Computing and Data Analysis)

Neuro-fuzzy system modeling based on automatic fuzzy clustering

Institute of Scientific and Technical Information of China (English)

Yuangang TANG; Fuchun SUN; Zengqi SUN

2005-01-01

A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

Automatic Service Derivation from Business Process Model Repositories via Semantic Technology

NARCIS (Netherlands)

Leopold, H.; Pittke, F.; Mendling, J.

2015-01-01

Although several approaches for service identification have been defined in research and practice, there is a notable lack of fully automated techniques. In this paper, we address the problem of manual work in the context of service derivation and present an approach for automatically deriving

Automatic identification of corrosion damage using image processing techniques

Energy Technology Data Exchange (ETDEWEB)

Bento, Mariana P.; Ramalho, Geraldo L.B.; Medeiros, Fatima N.S. de; Ribeiro, Elvis S. [Universidade Federal do Ceara (UFC), Fortaleza, CE (Brazil); Medeiros, Luiz C.L. [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

2009-07-01

This paper proposes a Nondestructive Evaluation (NDE) method for atmospheric corrosion detection on metallic surfaces using digital images. In this study, the uniform corrosion is characterized by texture attributes extracted from co-occurrence matrix and the Self Organizing Mapping (SOM) clustering algorithm. We present a technique for automatic inspection of oil and gas storage tanks and pipelines of petrochemical industries without disturbing their properties and performance. Experimental results are promising and encourage the possibility of using this methodology in designing trustful and robust early failure detection systems. (author)

Automatic detection and quantitative analysis of cells in the mouse primary motor cortex

Science.gov (United States)

Meng, Yunlong; He, Yong; Wu, Jingpeng; Chen, Shangbin; Li, Anan; Gong, Hui

2014-09-01

Neuronal cells play very important role on metabolism regulation and mechanism control, so cell number is a fundamental determinant of brain function. Combined suitable cell-labeling approaches with recently proposed three-dimensional optical imaging techniques, whole mouse brain coronal sections can be acquired with 1-μm voxel resolution. We have developed a completely automatic pipeline to perform cell centroids detection, and provided three-dimensional quantitative information of cells in the primary motor cortex of C57BL/6 mouse. It involves four principal steps: i) preprocessing; ii) image binarization; iii) cell centroids extraction and contour segmentation; iv) laminar density estimation. Investigations on the presented method reveal promising detection accuracy in terms of recall and precision, with average recall rate 92.1% and average precision rate 86.2%. We also analyze laminar density distribution of cells from pial surface to corpus callosum from the output vectorizations of detected cell centroids in mouse primary motor cortex, and find significant cellular density distribution variations in different layers. This automatic cell centroids detection approach will be beneficial for fast cell-counting and accurate density estimation, as time-consuming and error-prone manual identification is avoided.

A bar-code reader for an alpha-beta automatic counting system - FAG

Energy Technology Data Exchange (ETDEWEB)

Levinson, S; Shemesh, Y; Ankry, N; Assido, H; German, U; Peled, O [Israel Atomic Energy Commission, Beersheba (Israel). Nuclear Research Center-Negev

1996-12-01

A bar-code laser system for sample number reading was integrated into the FAG Alpha-Beta automatic counting system. The sample identification by means of an attached bar-code label enables unmistakable and reliable attribution of results to the counted sample. Installation of the bar-code reader system required several modifications: Mechanical changes in the automatic sample changer, design and production of new sample holders, modification of the sample planchettes, changes in the electronic system, update of the operating software of the system (authors).

A bar-code reader for an alpha-beta automatic counting system - FAG

International Nuclear Information System (INIS)

Levinson, S.; Shemesh, Y.; Ankry, N.; Assido, H.; German, U.; Peled, O.

1996-01-01

A bar-code laser system for sample number reading was integrated into the FAG Alpha-Beta automatic counting system. The sample identification by means of an attached bar-code label enables unmistakable and reliable attribution of results to the counted sample. Installation of the bar-code reader system required several modifications: Mechanical changes in the automatic sample changer, design and production of new sample holders, modification of the sample planchettes, changes in the electronic system, update of the operating software of the system (authors)

Testing the algorithms for automatic identification of errors on the measured quantities of the nuclear power plant. Verification tests

International Nuclear Information System (INIS)

Svatek, J.

1999-12-01

During the development and implementation of supporting software for the control room and emergency control centre at the Dukovany nuclear power plant it appeared necessary to validate the input quantities in order to assure operating reliability of the software tools. Therefore, the development of software for validation of the measured quantities of the plant data sources was initiated, and the software had to be debugged and verified. The report contains the proposal for and description of the verification tests for testing the algorithms of automatic identification of errors on the observed quantities of the NPP by means of homemade validation software. In particular, the algorithms treated serve the validation of the hot leg temperature at primary circuit loop no. 2 or 4 at the Dukovany-2 reactor unit using data from the URAN and VK3 information systems, recorded during 3 different days. (author)

The Iqmulus Urban Showcase: Automatic Tree Classification and Identification in Huge Mobile Mapping Point Clouds

Science.gov (United States)

Böhm, J.; Bredif, M.; Gierlinger, T.; Krämer, M.; Lindenberg, R.; Liu, K.; Michel, F.; Sirmacek, B.

2016-06-01

Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.

Rapid and automatic chemical identification of the medicinal flower buds of Lonicera plants by the benchtop and hand-held Fourier transform infrared spectroscopy

Science.gov (United States)

Chen, Jianbo; Guo, Baolin; Yan, Rui; Sun, Suqin; Zhou, Qun

2017-07-01

With the utilization of the hand-held equipment, Fourier transform infrared (FT-IR) spectroscopy is a promising analytical technique to minimize the time cost for the chemical identification of herbal materials. This research examines the feasibility of the hand-held FT-IR spectrometer for the on-site testing of herbal materials, using Lonicerae Japonicae Flos (LJF) and Lonicerae Flos (LF) as examples. Correlation-based linear discriminant models for LJF and LF are established based on the benchtop and hand-held FT-IR instruments. The benchtop FT-IR models can exactly recognize all articles of LJF and LF. Although a few LF articles are misjudged at the sub-class level, the hand-held FT-IR models are able to exactly discriminate LJF and LF. As a direct and label-free analytical technique, FT-IR spectroscopy has great potential in the rapid and automatic chemical identification of herbal materials either in laboratories or in fields. This is helpful to prevent the spread and use of adulterated herbal materials in time.

An automatic sodium-loop for testing the lon-term behaviour of sintered bodies flowed through by gas

International Nuclear Information System (INIS)

Barkleit, G.; George, G.; Haase, I.; Kiessling, W.

1980-08-01

An automatic sodium loop NAKOS for testing the long-term behaviour of porous stainless steel bodies which are flowed through by gas is described. The loop using a special safety protection system is capable of working without control up to 1000 h. During a 500 h-experiment the safety system and the gas permeability measuring method for testing the porous bodies were tested. Both first results of the behaviour of sintered bodies in liquid sodium of high purity and temperatures of about 850 K and some details of the production of these bodies are given. (author)

Simplified automatic on-line document searching

International Nuclear Information System (INIS)

Ebinuma, Yukio

1983-01-01

The author proposed searching method for users who need not-comprehensive retrieval. That is to provide flexible number of related documents for the users automatically. A group of technical terms are used as search terms to express an inquiry. Logical sums of the terms in the ascending order of frequency of the usage are prepared sequentially and automatically, and then the search formulas, qsub(m) and qsub(m-1) which meet certain threshold values are selected automatically also. Users justify precision of the search output up to 20 items retrieved by the formula qsub(m). If a user wishes more than 30% of recall ratio, the serach result should be output by qsub(m), and if he wishes less than 30% of it, it should be output by qsub(m-1). The search by this method using one year volume of INIS Database (76,600 items) and five inquiries resulted in 32% of recall ratio and 36% of precision ratio on the average in the case of qsub(m). The connecting time of a terminal was within 15 minutes per an inquiry. It showed more efficiency than that of an inexperienced searcher. The method can be applied to on-line searching system for database in which natural language only or natural language and controlled vocabulary are used. (author)

Usage of aids monitoring in automatic braking systems of modern cars

Directory of Open Access Journals (Sweden)

Dembitskyi V.

2016-08-01

Full Text Available Increased safety can be carried out at the expense the installation on vehicles of automatic braking systems, that monitor the traffic situation and the actions of the driver. In this paper considered the advantages and disadvantages of automatic braking systems, were analyzed modern tracking tools that are used in automatic braking systems. Based on the statistical data on accidents, are set the main dangers, that the automatic braking system will be reduced. In order to ensure the accuracy of information conducted research for determination of optimal combination of different sensors that provide an adequate perception of road conditions. The tracking system should be equipped with a combination of sensors, which in the case of detection of an obstacle or dangers of signal is transmitted to the information processing system and decision making. Information from the monitoring system should include data for the identification of the object, its condition, the speed.

Automatic Identification of Physical Activity Intensity and Modality from the Fusion of Accelerometry and Heart Rate Data.

Science.gov (United States)

García-García, Fernando; Benito, Pedro J; Hernando, María E

2016-12-07

Physical activity (PA) is essential to prevent and to treat a variety of chronic diseases. The automated detection and quantification of PA over time empowers lifestyle interventions, facilitating reliable exercise tracking and data-driven counseling. We propose and compare various combinations of machine learning (ML) schemes for the automatic classification of PA from multi-modal data, simultaneously captured by a biaxial accelerometer and a heart rate (HR) monitor. Intensity levels (low / moderate / vigorous) were recognized, as well as for vigorous exercise, its modality (sustained aerobic / resistance / mixed). In total, 178.63 h of data about PA intensity (65.55 % low / 18.96 % moderate / 15.49 % vigorous) and 17.00 h about modality were collected in two experiments: one in free-living conditions, another in a fitness center under controlled protocols. The structure used for automatic classification comprised: a) definition of 42 time-domain signal features, b) dimensionality reduction, c) data clustering, and d) temporal filtering to exploit time redundancy by means of a Hidden Markov Model (HMM). Four dimensionality reduction techniques and four clustering algorithms were studied. In order to cope with class imbalance in the dataset, a custom performance metric was defined to aggregate recognition accuracy, precision and recall. The best scheme, which comprised a projection through Linear Discriminant Analysis (LDA) and k-means clustering, was evaluated in leave-one-subject-out cross-validation; notably outperforming the standard industry procedures for PA intensity classification: score 84.65 %, versus up to 63.60 %. Errors tended to be brief and to appear around transients. The application of ML techniques for pattern identification and temporal filtering allowed to merge accelerometry and HR data in a solid manner, and achieved markedly better recognition performances than the standard methods for PA intensity estimation.

Identification of fracture zones and its application in automatic bone fracture reduction.

Science.gov (United States)

Paulano-Godino, Félix; Jiménez-Delgado, Juan J

2017-04-01

The preoperative planning of bone fractures using information from CT scans increases the probability of obtaining satisfactory results, since specialists are provided with additional information before surgery. The reduction of complex bone fractures requires solving a 3D puzzle in order to place each fragment into its correct position. Computer-assisted solutions may aid in this process by identifying the number of fragments and their location, by calculating the fracture zones or even by computing the correct position of each fragment. The main goal of this paper is the development of an automatic method to calculate contact zones between fragments and thus to ease the computation of bone fracture reduction. In this paper, an automatic method to calculate the contact zone between two bone fragments is presented. In a previous step, bone fragments are segmented and labelled from CT images and a point cloud is generated for each bone fragment. The calculated contact zones enable the automatic reduction of complex fractures. To that end, an automatic method to match bone fragments in complex fractures is also presented. The proposed method has been successfully applied in the calculation of the contact zone of 4 different bones from the ankle area. The calculated fracture zones enabled the reduction of all the tested cases using the presented matching algorithm. The performed tests show that the reduction of these fractures using the proposed methods leaded to a small overlapping between fragments. The presented method makes the application of puzzle-solving strategies easier, since it does not obtain the entire fracture zone but the contact area between each pair of fragments. Therefore, it is not necessary to find correspondences between fracture zones and fragments may be aligned two by two. The developed algorithms have been successfully applied in different fracture cases in the ankle area. The small overlapping error obtained in the performed tests

A Fully Automatic Fresh Apple Juicer: Peeling, Coring, Slicing and Juicing

Directory of Open Access Journals (Sweden)

Hu Fuwen

2017-01-01

Full Text Available With the fresh apple juice as an example, a fully automatic and intelligent juicer prototype was built via the integrated application of servo positioning modules, human-machine interface, image vision sensor system and 3D printing. All steps including peeling, coring, slicing and juicing were achieved automatically. The challenging technical problems about the identification and orientation of apple core, and adaptive peeling were settled creatively. The trial operation results illustrated that the fresh apple juice can be produced without manual intervention and the system has potential application in the crowded sites, such as mall, school, restaurant and hospital.

Automatic contact algorithm in ppercase[dyna3d] for crashworthiness and impact problems

International Nuclear Information System (INIS)

Whirley, Robert G.; Engelmann, Bruce E.

1994-01-01

This paper presents a new approach for the automatic definition and treatment of mechanical contact in explicit non-linear finite element analysis. Automatic contact offers the benefits of significantly reduced model construction time and fewer opportunities for user error, but faces significant challenges in reliability and computational costs. Key aspects of the proposed new method include automatic identification of adjacent and opposite surfaces in the global search phase, and the use of a well-defined surface normal which allows a consistent treatment of shell intersection and corner contact conditions without adhoc rules. The paper concludes with three examples which illustrate the performance of the newly proposed algorithm in the public ppercase[dyna3d] code. ((orig.))

Automatic segmentation of vertebrae from radiographs

DEFF Research Database (Denmark)

Mysling, Peter; Petersen, Peter Kersten; Nielsen, Mads

2011-01-01

Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical...... is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation...

[Isolation and identification of aerobic and facultative anaerobic bacteria in the oral cavity].

Science.gov (United States)

Lu, Wenxin; Wu, Fanzi; Zhou, Xinxuan; Wu, Lan; Li, Mingyun; Ren, Biao; Guo, Qiang; Huang, Ruijie; Li, Jiyao; Xiao, Liying; Li, Yan

2015-12-01

To establish a systematic method for isolation and identification of aerobic and facultative anaerobic bacteria in the oral cavity. Samples of the saliva, dental plaque and periapical granulation tissue were collected from 20 subjects with healthy oral condition and from 8 patients with different oral diseases. The bacteria in the samples were identified by morphological identification, VITEK automatic microorganism identification and 16s rRNA gene sequencing. VITEK automatic microorganism identification and 16s rRNA gene sequencing showed an agreement rate of 22.39% in identifying the bacteria in the samples. We identified altogether 63 bacterial genus (175 species), among which Streptococcus, Actinomyces and Staphylococcus were the most common bacterial genus, and Streptococcus anginosus, Actinomyces oris, Streptococcus mutans and Streptococcus mitis were the most common species. Streptococcus anginosus was commonly found in patients with chronic periapical periodontitis. Streptococcus intermedius and Staphylococcus aureus were common in patients with radiation caries, and in patients with rampant caries, Streptococcus mutans was found at considerably higher rate than other species. Aerobic and facultative anaerobic bacteria are commonly found in the oral cavity, and most of them are gram-positive. 16s rRNA gene sequencing is more accurate than VITEK automatic microorganism identification in identifying the bacteria.

Automatic reference selection for quantitative EEG interpretation: identification of diffuse/localised activity and the active earlobe reference, iterative detection of the distribution of EEG rhythms.

Science.gov (United States)

Wang, Bei; Wang, Xingyu; Ikeda, Akio; Nagamine, Takashi; Shibasaki, Hiroshi; Nakamura, Masatoshi

2014-01-01

EEG (Electroencephalograph) interpretation is important for the diagnosis of neurological disorders. The proper adjustment of the montage can highlight the EEG rhythm of interest and avoid false interpretation. The aim of this study was to develop an automatic reference selection method to identify a suitable reference. The results may contribute to the accurate inspection of the distribution of EEG rhythms for quantitative EEG interpretation. The method includes two pre-judgements and one iterative detection module. The diffuse case is initially identified by pre-judgement 1 when intermittent rhythmic waveforms occur over large areas along the scalp. The earlobe reference or averaged reference is adopted for the diffuse case due to the effect of the earlobe reference depending on pre-judgement 2. An iterative detection algorithm is developed for the localised case when the signal is distributed in a small area of the brain. The suitable averaged reference is finally determined based on the detected focal and distributed electrodes. The presented technique was applied to the pathological EEG recordings of nine patients. One example of the diffuse case is introduced by illustrating the results of the pre-judgements. The diffusely intermittent rhythmic slow wave is identified. The effect of active earlobe reference is analysed. Two examples of the localised case are presented, indicating the results of the iterative detection module. The focal and distributed electrodes are detected automatically during the repeating algorithm. The identification of diffuse and localised activity was satisfactory compared with the visual inspection. The EEG rhythm of interest can be highlighted using a suitable selected reference. The implementation of an automatic reference selection method is helpful to detect the distribution of an EEG rhythm, which can improve the accuracy of EEG interpretation during both visual inspection and automatic interpretation. Copyright © 2013 IPEM

Google Earth Visualizations of the Marine Automatic Identification System (AIS): Monitoring Ship Traffic in National Marine Sanctuaries

Science.gov (United States)

Schwehr, K.; Hatch, L.; Thompson, M.; Wiley, D.

2007-12-01

The Automatic Identification System (AIS) is a new technology that provides ship position reports with location, time, and identity information without human intervention from ships carrying the transponders to any receiver listening to the broadcasts. In collaboration with the USCG's Research and Development Center, NOAA's Stellwagen Bank National Marine Sanctuary (SBNMS) has installed 3 AIS receivers around Massachusetts Bay to monitor ship traffic transiting the sanctuary and surrounding waters. The SBNMS and the USCG also worked together propose the shifting the shipping lanes (termed the traffic separation scheme; TSS) that transit the sanctuary slightly to the north to reduce the probability of ship strikes of whales that frequent the sanctuary. Following approval by the United Nation's International Maritime Organization, AIS provided a means for NOAA to assess changes in the distribution of shipping traffic caused by formal change in the TSS effective July 1, 2007. However, there was no easy way to visualize this type of time series data. We have created a software package called noaadata-py to process the AIS ship reports and produce KML files for viewing in Google Earth. Ship tracks can be shown changing over time to allow the viewer to feel the motion of traffic through the sanctuary. The ship tracks can also be gridded to create ship traffic density reports for specified periods of time. The density is displayed as map draped on the sea surface or as vertical histogram columns. Additional visualizations such as bathymetry images, S57 nautical charts, and USCG Marine Information for Safety and Law Enforcement (MISLE) can be combined with the ship traffic visualizations to give a more complete picture of the maritime environment. AIS traffic analyses have the potential to give managers throughout NOAA's National Marine Sanctuaries an improved ability to assess the impacts of ship traffic on the marine resources they seek to protect. Viewing ship traffic

Automatic Validation of Protocol Narration

DEFF Research Database (Denmark)

Bodei, Chiara; Buchholtz, Mikael; Degano, Pierpablo

2003-01-01

We perform a systematic expansion of protocol narrations into terms of a process algebra in order to make precise some of the detailed checks that need to be made in a protocol. We then apply static analysis technology to develop an automatic validation procedure for protocols. Finally, we...

Analyzing Program Termination and Complexity Automatically with AProVE

DEFF Research Database (Denmark)

Giesl, Jürgen; Aschermann, Cornelius; Brockschmidt, Marc

2017-01-01

In this system description, we present the tool AProVE for automatic termination and complexity proofs of Java, C, Haskell, Prolog, and rewrite systems. In addition to classical term rewrite systems (TRSs), AProVE also supports rewrite systems containing built-in integers (int-TRSs). To analyze...... programs in high-level languages, AProVE automatically converts them to (int-)TRSs. Then, a wide range of techniques is employed to prove termination and to infer complexity bounds for the resulting rewrite systems. The generated proofs can be exported to check their correctness using automatic certifiers...

THE IQMULUS URBAN SHOWCASE: AUTOMATIC TREE CLASSIFICATION AND IDENTIFICATION IN HUGE MOBILE MAPPING POINT CLOUDS

Directory of Open Access Journals (Sweden)

J. Böhm

2016-06-01

Full Text Available Current 3D data capturing as implemented on for example airborne or mobile laser scanning systems is able to efficiently sample the surface of a city by billions of unselective points during one working day. What is still difficult is to extract and visualize meaningful information hidden in these point clouds with the same efficiency. This is where the FP7 IQmulus project enters the scene. IQmulus is an interactive facility for processing and visualizing big spatial data. In this study the potential of IQmulus is demonstrated on a laser mobile mapping point cloud of 1 billion points sampling ~ 10 km of street environment in Toulouse, France. After the data is uploaded to the IQmulus Hadoop Distributed File System, a workflow is defined by the user consisting of retiling the data followed by a PCA driven local dimensionality analysis, which runs efficiently on the IQmulus cloud facility using a Spark implementation. Points scattering in 3 directions are clustered in the tree class, and are separated next into individual trees. Five hours of processing at the 12 node computing cluster results in the automatic identification of 4000+ urban trees. Visualization of the results in the IQmulus fat client helps users to appreciate the results, and developers to identify remaining flaws in the processing workflow.

Flight Extraction and Phase Identification for Large Automatic Dependent Surveillance–Broadcast Datasets

NARCIS (Netherlands)

Sun, J.; Ellerbroek, J.; Hoekstra, J.M.

2017-01-01

AUTOMATIC dependent surveillance–broadcast (ADS-B) [1,2] is widely implemented in modern commercial aircraft and will become mandatory equipment in 2020. Flight state information such as position, velocity, and vertical rate are broadcast by tens of thousands of aircraft around the world constantly

Automatic measurement of the radioactive mercury uptake by the kidney

International Nuclear Information System (INIS)

Zurowski, S.; Raynaud, C.; CEA, 91 - Orsay

1976-01-01

An entirely automatic method to measure the Hg uptake by the kidney is proposed. The following operations are carried out in succession: measurement of extrarenal activity, demarcation of uptake areas, anatomical identification of uptake areas, separation of overlapping organ images and measurement of kidney depth. The first results thus calculated on 30 patients are very close to those obtained with a standard manual method and are highly encouraging. Two important points should be stressed: a broad demarcation of the uptake areas is necessary and an original method, that of standard errors, is useful for the background noise determination and uptake area demarcation. This automatic measurement technique is so designed that it can be applied to other special cases [fr

Automatic Adviser on stationary devices status identification and anticipated change

Science.gov (United States)

Shabelnikov, A. N.; Liabakh, N. N.; Gibner, Ya M.; Pushkarev, E. A.

2018-05-01

A task is defined to synthesize an Automatic Adviser to identify the automation systems stationary devices status using an autoregressive model of changing their key parameters. An applied model type was rationalized and the research objects monitoring process algorithm was developed. A complex of mobile objects status operation simulation and prediction results analysis was proposed. Research results are commented using a specific example of a hump yard compressor station. The work was supported by the Russian Fundamental Research Fund, project No. 17-20-01040.

Automatic semantic encoding in verbal short-term memory: evidence from the concreteness effect.

Science.gov (United States)

Campoy, Guillermo; Castellà, Judit; Provencio, Violeta; Hitch, Graham J; Baddeley, Alan D

2015-01-01

The concreteness effect in verbal short-term memory (STM) tasks is assumed to be a consequence of semantic encoding in STM, with immediate recall of concrete words benefiting from richer semantic representations. We used the concreteness effect to test the hypothesis that semantic encoding in standard verbal STM tasks is a consequence of controlled, attention-demanding mechanisms of strategic semantic retrieval and encoding. Experiment 1 analysed the effect of presentation rate, with slow presentations being assumed to benefit strategic, time-dependent semantic encoding. Experiments 2 and 3 provided a more direct test of the strategic hypothesis by introducing three different concurrent attention-demanding tasks. Although Experiment 1 showed a larger concreteness effect with slow presentations, the following two experiments yielded strong evidence against the strategic hypothesis. Limiting available attention resources by concurrent tasks reduced global memory performance, but the concreteness effect was equivalent to that found in control conditions. We conclude that semantic effects in STM result from automatic semantic encoding and provide tentative explanations for the interaction between the concreteness effect and the presentation rate.

Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

Directory of Open Access Journals (Sweden)

Malik M. Naeem Mannan

2016-02-01

Full Text Available Contamination of eye movement and blink artifacts in Electroencephalogram (EEG recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the brain-computer interface (BCI. In this paper, we proposed an automatic framework based on independent component analysis (ICA and system identification to identify and remove ocular artifacts from EEG data by using hybrid EEG and eye tracker system. The performance of the proposed algorithm is illustrated using experimental and standard EEG datasets. The proposed algorithm not only removes the ocular artifacts from artifactual zone but also preserves the neuronal activity related EEG signals in non-artifactual zone. The comparison with the two state-of-the-art techniques namely ADJUST based ICA and REGICA reveals the significant improved performance of the proposed algorithm for removing eye movement and blink artifacts from EEG data. Additionally, results demonstrate that the proposed algorithm can achieve lower relative error and higher mutual information values between corrected EEG and artifact-free EEG data.

45 CFR 95.631 - Cost identification for purpose of FFP claims.

Science.gov (United States)

2010-10-01

... INSURANCE PROGRAMS) Automatic Data Processing Equipment and Services-Conditions for Federal Financial Participation (FFP) Federal Financial Participation in Costs of Adp Acquisitions § 95.631 Cost identification... 45 Public Welfare 1 2010-10-01 2010-10-01 false Cost identification for purpose of FFP claims. 95...

An investigation into the factors that influence toolmark identifications on ammunition discharged from semi-automatic pistols recovered from car fires.

Science.gov (United States)

Collender, Mark A; Doherty, Kevin A J; Stanton, Kenneth T

2017-01-01

Following a shooting incident where a vehicle is used to convey the culprits to and from the scene, both the getaway car and the firearm are often deliberately burned in an attempt to destroy any forensic evidence which may be subsequently recovered. Here we investigate the factors that influence the ability to make toolmark identifications on ammunition discharged from pistols recovered from such car fires. This work was carried out by conducting a number of controlled furnace tests in conjunction with real car fire tests in which three 9mm semi-automatic pistols were burned. Comparisons between pre-burn and post burn test fired ammunition discharged from these pistols were then performed to establish if identifications were still possible. The surfaces of the furnace heated samples and car fire samples were examined following heating/burning to establish what factors had influenced their surface morphology. The primary influence on the surfaces of the furnace heated and car fire samples was the formation of oxide layers. The car fire samples were altered to a greater extent than the furnace heated samples. Identifications were still possible between pre- and post-burn discharged cartridge cases, but this was not the case for the discharged bullets. It is suggested that the reason for this is a difference between the types of firearms discharge-generated toolmarks impressed onto the base of cartridge cases compared to those striated along the surfaces of bullets. It was also found that the temperatures recorded in the front foot wells were considerably less than those recorded on top of the rear seats during the car fires. These factors should be assessed by forensic firearms examiners when performing casework involving pistols recovered from car fires. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Child vocalization composition as discriminant information for automatic autism detection.

Science.gov (United States)

Xu, Dongxin; Gilkerson, Jill; Richards, Jeffrey; Yapanel, Umit; Gray, Sharmi

2009-01-01

Early identification is crucial for young children with autism to access early intervention. The existing screens require either a parent-report questionnaire and/or direct observation by a trained practitioner. Although an automatic tool would benefit parents, clinicians and children, there is no automatic screening tool in clinical use. This study reports a fully automatic mechanism for autism detection/screening for young children. This is a direct extension of the LENA (Language ENvironment Analysis) system, which utilizes speech signal processing technology to analyze and monitor a child's natural language environment and the vocalizations/speech of the child. It is discovered that child vocalization composition contains rich discriminant information for autism detection. By applying pattern recognition and machine learning approaches to child vocalization composition data, accuracy rates of 85% to 90% in cross-validation tests for autism detection have been achieved at the equal-error-rate (EER) point on a data set with 34 children with autism, 30 language delayed children and 76 typically developing children. Due to its easy and automatic procedure, it is believed that this new tool can serve a significant role in childhood autism screening, especially in regards to population-based or universal screening.

Artificial Intelligence In Automatic Target Recognizers: Technology And Timelines

Science.gov (United States)

Gilmore, John F.

1984-12-01

The recognition of targets in thermal imagery has been a problem exhaustively analyzed in its current localized dimension. This paper discusses the application of artificial intelligence (AI) technology to automatic target recognition, a concept capable of expanding current ATR efforts into a new globalized dimension. Deficiencies of current automatic target recognition systems are reviewed in terms of system shortcomings. Areas of artificial intelligence which show the most promise in improving ATR performance are analyzed, and a timeline is formed in light of how near (as well as far) term artificial intelligence applications may exist. Current research in the area of high level expert vision systems is reviewed and the possible utilization of artificial intelligence architectures to improve low level image processing functions is also discussed. Additional application areas of relevance to solving the problem of automatic target recognition utilizing both high and low level processing are also explored.

Automatic personnel contamination monitor

International Nuclear Information System (INIS)

Lattin, Kenneth R.

1978-01-01

United Nuclear Industries, Inc. (UNI) has developed an automatic personnel contamination monitor (APCM), which uniquely combines the design features of both portal and hand and shoe monitors. In addition, this prototype system also has a number of new features, including: micro computer control and readout, nineteen large area gas flow detectors, real-time background compensation, self-checking for system failures, and card reader identification and control. UNI's experience in operating the Hanford N Reactor, located in Richland, Washington, has shown the necessity of automatically monitoring plant personnel for contamination after they have passed through the procedurally controlled radiation zones. This final check ensures that each radiation zone worker has been properly checked before leaving company controlled boundaries. Investigation of the commercially available portal and hand and shoe monitors indicated that they did not have the sensitivity or sophistication required for UNI's application, therefore, a development program was initiated, resulting in the subject monitor. Field testing shows good sensitivity to personnel contamination with the majority of alarms showing contaminants on clothing, face and head areas. In general, the APCM has sensitivity comparable to portal survey instrumentation. The inherit stand-in, walk-on feature of the APCM not only makes it easy to use, but makes it difficult to bypass. (author)

Automatic control system at the ''Loviisa'' NPP

International Nuclear Information System (INIS)

Kukhtevich, I.V.; Mal'tsev, B.K.; Sergievskaya, E.N.

1980-01-01

Automatic control system of the Loviisa-1 NPP (Finland) is described. According to operation conditions of Finland power system the Loviisa-1 NPP must operate in the mode of week and day control of loading schedule and participate in current control of power system frequency and capacity. With provision for these requirements NPP is equipped with the all-regime system for automatic control functioning during reactor start-up, shut-down, in normal and transient regimes and in emergency situations. The automatic control system includes: a data subsystem, an automatic control subsystem, a discrete control subsystem including remote, a subsystem for reactor control and protection and overall station system of protections: control and dosimetry inside the reactor. Structures of a data-computer complex, discrete control subsystems, reactor control and protection systems, neutron flux control system, inside-reactor control system, station protection system and system for control of fuel element tightness are presented in short. Two-year experience of the NPP operation confirmed advisability of the chosen volume of automatization. The Loviisa-1 NPP operates successfully in the mode of the week and day control of supervisor schedule and current control of frequency (short-term control)

GPU-accelerated automatic identification of robust beam setups for proton and carbon-ion radiotherapy

International Nuclear Information System (INIS)

Ammazzalorso, F; Jelen, U; Bednarz, T

2014-01-01

We demonstrate acceleration on graphic processing units (GPU) of automatic identification of robust particle therapy beam setups, minimizing negative dosimetric effects of Bragg peak displacement caused by treatment-time patient positioning errors. Our particle therapy research toolkit, RobuR, was extended with OpenCL support and used to implement calculation on GPU of the Port Homogeneity Index, a metric scoring irradiation port robustness through analysis of tissue density patterns prior to dose optimization and computation. Results were benchmarked against an independent native CPU implementation. Numerical results were in agreement between the GPU implementation and native CPU implementation. For 10 skull base cases, the GPU-accelerated implementation was employed to select beam setups for proton and carbon ion treatment plans, which proved to be dosimetrically robust, when recomputed in presence of various simulated positioning errors. From the point of view of performance, average running time on the GPU decreased by at least one order of magnitude compared to the CPU, rendering the GPU-accelerated analysis a feasible step in a clinical treatment planning interactive session. In conclusion, selection of robust particle therapy beam setups can be effectively accelerated on a GPU and become an unintrusive part of the particle therapy treatment planning workflow. Additionally, the speed gain opens new usage scenarios, like interactive analysis manipulation (e.g. constraining of some setup) and re-execution. Finally, through OpenCL portable parallelism, the new implementation is suitable also for CPU-only use, taking advantage of multiple cores, and can potentially exploit types of accelerators other than GPUs.

GPU-accelerated automatic identification of robust beam setups for proton and carbon-ion radiotherapy

Science.gov (United States)

Ammazzalorso, F.; Bednarz, T.; Jelen, U.

2014-03-01

We demonstrate acceleration on graphic processing units (GPU) of automatic identification of robust particle therapy beam setups, minimizing negative dosimetric effects of Bragg peak displacement caused by treatment-time patient positioning errors. Our particle therapy research toolkit, RobuR, was extended with OpenCL support and used to implement calculation on GPU of the Port Homogeneity Index, a metric scoring irradiation port robustness through analysis of tissue density patterns prior to dose optimization and computation. Results were benchmarked against an independent native CPU implementation. Numerical results were in agreement between the GPU implementation and native CPU implementation. For 10 skull base cases, the GPU-accelerated implementation was employed to select beam setups for proton and carbon ion treatment plans, which proved to be dosimetrically robust, when recomputed in presence of various simulated positioning errors. From the point of view of performance, average running time on the GPU decreased by at least one order of magnitude compared to the CPU, rendering the GPU-accelerated analysis a feasible step in a clinical treatment planning interactive session. In conclusion, selection of robust particle therapy beam setups can be effectively accelerated on a GPU and become an unintrusive part of the particle therapy treatment planning workflow. Additionally, the speed gain opens new usage scenarios, like interactive analysis manipulation (e.g. constraining of some setup) and re-execution. Finally, through OpenCL portable parallelism, the new implementation is suitable also for CPU-only use, taking advantage of multiple cores, and can potentially exploit types of accelerators other than GPUs.

Automatic morphometry of synaptic boutons of cultured cells using granulometric analysis of digital images

NARCIS (Netherlands)

Prodanov, D.P.; Heeroma, Joost; Marani, Enrico

2006-01-01

Numbers, linear density, and surface area of synaptic boutons can be important parameters in studies on synaptic plasticity in cultured neurons. We present a method for automatic identification and morphometry of boutons based on filtering of digital images using granulometric analysis. Cultures of

Automatic identification of tuberculosis mycobacterium

Directory of Open Access Journals (Sweden)

Cicero Ferreira Fernandes Costa Filho

Full Text Available Introduction According to the Global TB control report of 2013, “Tuberculosis (TB remains a major global health problem. In 2012, an estimated 8.6 million people developed TB and 1.3 million died from the disease. Two main sputum smear microscopy techniques are used for TB diagnosis: Fluorescence microscopy and conventional microscopy. Fluorescence microscopy is a more expensive diagnostic method because of the high costs of the microscopy unit and its maintenance. Therefore, conventional microscopy is more appropriate for use in developing countries. Methods This paper presents a new method for detecting tuberculosis bacillus in conventional sputum smear microscopy. The method consists of two main steps, bacillus segmentation and post-processing. In the first step, the scalar selection technique was used to select input variables for the segmentation classifiers from four color spaces. Thirty features were used, including the subtractions of the color components of different color spaces. In the post-processing step, three filters were used to separate bacilli from artifact: a size filter, a geometric filter and a Rule-based filter that uses the components of the RGB color space. Results In bacillus identification, an overall sensitivity of 96.80% and an error rate of 3.38% were obtained. An image database with 120-sputum-smear microscopy slices of 12 patients with objects marked as bacillus, agglomerated bacillus and artifact was generated and is now available online. Conclusions The best results were obtained with a support vector machine in bacillus segmentation associated with the application of the three post-processing filters.

A biometric approach to laboratory rodent identification.

Science.gov (United States)

Cameron, Jens; Jacobson, Christina; Nilsson, Kenneth; Rögnvaldsson, Thorsteinn

2007-03-01

Individual identification of laboratory rodents typically involves invasive methods, such as tattoos, ear clips, and implanted transponders. Beyond the ethical dilemmas they may present, these methods may cause pain or distress that confounds research results. The authors describe a prototype device for biometric identification of laboratory rodents that would allow researchers to identify rodents without the complications of other methods. The device, which uses the rodent's ear blood vessel pattern as the identifier, is fast, automatic, noninvasive, and painless.

USER EMOTION IDENTIFICATION IN TWITTER USING SPECIFIC FEATURES: HASHTAG, EMOJI, EMOTICON, AND ADJECTIVE TERM

Directory of Open Access Journals (Sweden)

Yuita Arum Sari

2014-08-01

Full Text Available Abstract Twitter is a social media application, which can give a sign for identifying user emotion. Identification of user emotion can be utilized in commercial domain, health, politic, and security problems. The problem of emotion identification in twit is the unstructured short text messages which lead the difficulty to figure out main features. In this paper, we propose a new framework for identifying the tendency of user emotions using specific features, i.e. hashtag, emoji, emoticon, and adjective term. Preprocessing is applied in the first phase, and then user emotions are identified by means of classification method using kNN. The proposed method can achieve good results, near ground truth, with accuracy of 92%.

Semi-automatic Term Extraction for an isiZulu Linguistic Terms ...

African Journals Online (AJOL)

user

This paper advances the use of frequency analysis and the keyword analysis as strategies to extract terms for the compilation of the dictionary of isiZulu linguistic terms. The study uses the isiZulu. National Corpus (INC) of about 1,2 million tokens as a reference corpus as well as an LSP corpus of about 100,000 tokens as a ...

Monitoring caustic injuries from emergency department databases using automatic keyword recognition software.

Science.gov (United States)

Vignally, P; Fondi, G; Taggi, F; Pitidis, A

2011-03-31

In Italy the European Union Injury Database reports the involvement of chemical products in 0.9% of home and leisure accidents. The Emergency Department registry on domestic accidents in Italy and the Poison Control Centres record that 90% of cases of exposure to toxic substances occur in the home. It is not rare for the effects of chemical agents to be observed in hospitals, with a high potential risk of damage - the rate of this cause of hospital admission is double the domestic injury average. The aim of this study was to monitor the effects of injuries caused by caustic agents in Italy using automatic free-text recognition in Emergency Department medical databases. We created a Stata software program to automatically identify caustic or corrosive injury cases using an agent-specific list of keywords. We focused attention on the procedure's sensitivity and specificity. Ten hospitals in six regions of Italy participated in the study. The program identified 112 cases of injury by caustic or corrosive agents. Checking the cases by quality controls (based on manual reading of ED reports), we assessed 99 cases as true positive, i.e. 88.4% of the patients were automatically recognized by the software as being affected by caustic substances (99% CI: 80.6%- 96.2%), that is to say 0.59% (99% CI: 0.45%-0.76%) of the whole sample of home injuries, a value almost three times as high as that expected (p < 0.0001) from European codified information. False positives were 11.6% of the recognized cases (99% CI: 5.1%- 21.5%). Our automatic procedure for caustic agent identification proved to have excellent product recognition capacity with an acceptable level of excess sensitivity. Contrary to our a priori hypothesis, the automatic recognition system provided a level of identification of agents possessing caustic effects that was significantly much greater than was predictable on the basis of the values from current codifications reported in the European Database.

Word level language identification in online multilingual communication

NARCIS (Netherlands)

Nguyen, Dong-Phuong; Dogruoz, A. Seza

2013-01-01

Multilingual speakers switch between languages in online and spoken communication. Analyses of large scale multilingual data require automatic language identification at the word level. For our experiments with multilingual online discussions, we first tag the language of individual words using

THEORETICAL CONSIDERATIONS REGARDING THE AUTOMATIC FISCAL STABILIZERS OPERATING MECHANISM

Directory of Open Access Journals (Sweden)

Gondor Mihaela

2012-07-01

Full Text Available This paper examines the role of Automatic Fiscal Stabilizers (AFS for stabilizing the cyclical fluctuations of macroeconomic output as an alternative to discretionary fiscal policy, admitting its huge potential of being an anti crisis solution. The objectives of the study are the identification of the general features of the concept of automatic fiscal stabilizers and the logical assessment of them from economic perspectives. Based on the literature in the field, this paper points out the disadvantages of fiscal discretionary policy and argue the need of using Automatic Fiscal Stabilizers in order to provide a faster decision making process, shielded from political interference, and reduced uncertainty for households and business environment. The paper conclude about the need of using fiscal policy for smoothing the economic cycle, but in a way which includes among its features transparency, responsibility and clear operating mechanisms. Based on the research results the present paper assumes that pro-cyclicality reduces de effectiveness of the Automatic Fiscal Stabilizer and as a result concludes that it is very important to avoid the pro-cyclicality in fiscal rule design. Moreover, by committing in advance to specific fiscal policy action contingent on economic developments, uncertainty about the fiscal policy framework during a recession should be reduced. Being based on logical analysis and not focused on empirical, contextualized one, the paper presents some features of AFS operating mechanism and also identifies and systematizes the factors which provide its importance and national individuality. Reaching common understanding on the Automatic Fiscal Stabilizer concept as a institutional device for smoothing the gap of the economic cycles across different countries, particularly for the European Union Member States, will facilitate efforts to coordinate fiscal policy responses during a crisis, especially in the context of the fiscal

Automatic Imitation

Science.gov (United States)

Heyes, Cecilia

2011-01-01

"Automatic imitation" is a type of stimulus-response compatibility effect in which the topographical features of task-irrelevant action stimuli facilitate similar, and interfere with dissimilar, responses. This article reviews behavioral, neurophysiological, and neuroimaging research on automatic imitation, asking in what sense it is "automatic"…

Automatic video shot boundary detection using k-means clustering and improved adaptive dual threshold comparison

Science.gov (United States)

Sa, Qila; Wang, Zhihui

2018-03-01

At present, content-based video retrieval (CBVR) is the most mainstream video retrieval method, using the video features of its own to perform automatic identification and retrieval. This method involves a key technology, i.e. shot segmentation. In this paper, the method of automatic video shot boundary detection with K-means clustering and improved adaptive dual threshold comparison is proposed. First, extract the visual features of every frame and divide them into two categories using K-means clustering algorithm, namely, one with significant change and one with no significant change. Then, as to the classification results, utilize the improved adaptive dual threshold comparison method to determine the abrupt as well as gradual shot boundaries.Finally, achieve automatic video shot boundary detection system.

Development of a portable equipment for identification of radionuclides

International Nuclear Information System (INIS)

Farias, Marcos Santana; Carvalho, Paulo Victor R. de; Nedjah, Nadia; Mourelle, Luiza de Macedo

2014-01-01

The rapid and automatic identification of radionuclides present in a radioactive sample detected in the field, is information that helps in decision making. In areas of high traffic of people and materials, such as ports and airports as well as at major events, radiation monitoring, together with the identification of the radionuclide, it is advisable within protective standards to the public. The correct identification of radionuclides depends on the ability to determine whether specific peaks energy sources are present in the spectrum of gamma radiation sources. Radionuclides can be identified by these energy characteristics in the sense that the energy value associated with these peaks in the spectrum corresponds to the radiation sources present in the sample. There are many methods that can be used for automatic identification of radionuclides. Most of them are based on software algorithms for the detection of peaks in the energy spectrum. Processing time of these tasks can be very long for applications requiring quick responses, as in equipment portable. A dedicated digital hardware offers better performance for tasks with high processing demand like this. This work shows the development of a handle Portable radionuclides based on a digital hardware solution using a FPGA (Field Programmable Gate Array) for implementing a clustering algorithm for the detection of energy peaks. (author)

Automatic extraction of road features in urban environments using dense ALS data

Science.gov (United States)

Soilán, Mario; Truong-Hong, Linh; Riveiro, Belén; Laefer, Debra

2018-02-01

This paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection.

The DanTermBank Project

DEFF Research Database (Denmark)

Lassen, Tine; Madsen, Bodil Nistrup; Pram Nielsen, Louise

This paper gives an introduction to the plans and ongoing work in a project, the aim of which is to develop methods for automatic knowledge extraction and automatic construction and updating of ontologies. The project also aims at developing methods for automatic merging of terminological data fr...... various existing sources, as well as methods for target group oriented knowledge dissemination. In this paper, we mainly focus on the plans for automatic knowledge extraction and knowledge structuring that will result in ontologies for a national term bank.......This paper gives an introduction to the plans and ongoing work in a project, the aim of which is to develop methods for automatic knowledge extraction and automatic construction and updating of ontologies. The project also aims at developing methods for automatic merging of terminological data from...

Development of an optimal filter substrate for the identification of small microplastic particles in food by micro-Raman spectroscopy.

Science.gov (United States)

Oßmann, Barbara E; Sarau, George; Schmitt, Sebastian W; Holtmannspötter, Heinrich; Christiansen, Silke H; Dicke, Wilhelm

2017-06-01

When analysing microplastics in food, due to toxicological reasons it is important to achieve clear identification of particles down to a size of at least 1 μm. One reliable, optical analytical technique allowing this is micro-Raman spectroscopy. After isolation of particles via filtration, analysis is typically performed directly on the filter surface. In order to obtain high qualitative Raman spectra, the material of the membrane filters should not show any interference in terms of background and Raman signals during spectrum acquisition. To facilitate the usage of automatic particle detection, membrane filters should also show specific optical properties. In this work, beside eight different, commercially available membrane filters, three newly designed metal-coated polycarbonate membrane filters were tested to fulfil these requirements. We found that aluminium-coated polycarbonate membrane filters had ideal characteristics as a substrate for micro-Raman spectroscopy. Its spectrum shows no or minimal interference with particle spectra, depending on the laser wavelength. Furthermore, automatic particle detection can be applied when analysing the filter surface under dark-field illumination. With this new membrane filter, analytics free of interference of microplastics down to a size of 1 μm becomes possible. Thus, an important size class of these contaminants can now be visualized and spectrally identified. Graphical abstract A newly developed aluminium coated polycarbonate membrane filter enables automatic particle detection and generation of high qualitative Raman spectra allowing identification of small microplastics.

Automatic identification of single- and/or few-layer thin-film material

DEFF Research Database (Denmark)

2014-01-01

One or more digital representations of single- (101) and/or few-layer (102) thin- film material are automatically identified robustly and reliably in a digital image (100), the digital image (100) having a predetermined number of colour components, by - determining (304) a background colour...... component of the digital image (100) for each colour component, and - determining or estimating (306) a colour component of thin-film material to be identified in the digital image (100) for each colour component by obtaining a pre-determined contrast value (C R; C G; C B) for each colour component...

Automatic Control of Personal Rapid Transit Vehicles

Science.gov (United States)

Smith, P. D.

1972-01-01

The requirements for automatic longitudinal control of a string of closely packed personal vehicles are outlined. Optimal control theory is used to design feedback controllers for strings of vehicles. An important modification of the usual optimal control scheme is the inclusion of jerk in the cost functional. While the inclusion of the jerk term was considered, the effect of its inclusion was not sufficiently studied. Adding the jerk term will increase passenger comfort.

Identification of conductive hearing loss using air conduction tests alone: reliability and validity of an automatic test battery.

Science.gov (United States)

Convery, Elizabeth; Keidser, Gitte; Seeto, Mark; Freeston, Katrina; Zhou, Dan; Dillon, Harvey

2014-01-01

The primary objective of this study was to determine whether a combination of automatically administered pure-tone audiometry and a tone-in-noise detection task, both delivered via an air conduction (AC) pathway, could reliably and validly predict the presence of a conductive component to the hearing loss. The authors hypothesized that performance on the battery of tests would vary according to hearing loss type. A secondary objective was to evaluate the reliability and validity of a novel automatic audiometry algorithm to assess its suitability for inclusion in the test battery. Participants underwent a series of hearing assessments that were conducted in a randomized order: manual pure-tone air conduction audiometry and bone conduction audiometry; automatic pure-tone air conduction audiometry; and an automatic tone-in-noise detection task. The automatic tests were each administered twice. The ability of the automatic test battery to: (a) predict the presence of an air-bone gap (ABG); and (b) accurately measure AC hearing thresholds was assessed against the results of manual audiometry. Test-retest conditions were compared to determine the reliability of each component of the automatic test battery. Data were collected on 120 ears from normal-hearing and conductive, sensorineural, and mixed hearing-loss subgroups. Performance differences between different types of hearing loss were observed. Ears with a conductive component (conductive and mixed ears) tended to have normal signal to noise ratios (SNR) despite impaired thresholds in quiet, while ears without a conductive component (normal and sensorineural ears) demonstrated, on average, an increasing relationship between their thresholds in quiet and their achieved SNR. Using the relationship between these two measures among ears with no conductive component as a benchmark, the likelihood that an ear has a conductive component can be estimated based on the deviation from this benchmark. The sensitivity and

Face recognition for criminal identification: An implementation of principal component analysis for face recognition

Science.gov (United States)

Abdullah, Nurul Azma; Saidi, Md. Jamri; Rahman, Nurul Hidayah Ab; Wen, Chuah Chai; Hamid, Isredza Rahmi A.

2017-10-01

In practice, identification of criminal in Malaysia is done through thumbprint identification. However, this type of identification is constrained as most of criminal nowadays getting cleverer not to leave their thumbprint on the scene. With the advent of security technology, cameras especially CCTV have been installed in many public and private areas to provide surveillance activities. The footage of the CCTV can be used to identify suspects on scene. However, because of limited software developed to automatically detect the similarity between photo in the footage and recorded photo of criminals, the law enforce thumbprint identification. In this paper, an automated facial recognition system for criminal database was proposed using known Principal Component Analysis approach. This system will be able to detect face and recognize face automatically. This will help the law enforcements to detect or recognize suspect of the case if no thumbprint present on the scene. The results show that about 80% of input photo can be matched with the template data.

Identification automatique des diatomées de la Merja fouarate : Une ...

African Journals Online (AJOL)

SARAH

30 sept. 2015 ... Automatic identification of Fouarate Merja diatoms: An alternative to manual determination and classification .... 21 genres, avec une erreur de 4% car plusieurs organismes .... Electronic, Technologies of Information and.

Accident identification system with automatic detection of abnormal condition using quantum computation

International Nuclear Information System (INIS)

Nicolau, Andressa dos Santos; Schirru, Roberto; Lima, Alan Miranda Monteiro de

2011-01-01

Transient identification systems have been proposed in order to maintain the plant operating in safe conditions and help operators in make decisions in emergency short time interval with maximum certainty associated. This article presents a system, time independent and without the use of an event that can be used as a starting point for t = 0 (reactor scram, for instance), for transient/accident identification of a pressurized water nuclear reactor (PWR). The model was developed in order to be able to recognize the normal condition and three accidents of the design basis list of the Nuclear Power Plant Angra 2, postulated in the Final Safety Analysis Report (FSAR). Were used several sets of process variables in order to establish a minimum set of variables considered necessary and sufficient. The optimization step of the identification algorithm is based upon the paradigm of Quantum Computing. In this case, the optimization metaheuristic Quantum Inspired Evolutionary Algorithm (QEA) was implemented and works as a data mining tool. The results obtained with the QEA without the time variable are compatible to the techniques in the reference literature, for the transient identification problem, with less computational effort (number of evaluations). This system allows a solution that approximates the ideal solution, the Voronoi Vectors with only one partition for the classes of accidents with robustness. (author)

Early Automatic Detection of Parkinson's Disease Based on Sleep Recordings

DEFF Research Database (Denmark)

Kempfner, Jacob; Sorensen, Helge B D; Nikolic, Miki

2014-01-01

SUMMARY: Idiopathic rapid-eye-movement (REM) sleep behavior disorder (iRBD) is most likely the earliest sign of Parkinson's Disease (PD) and is characterized by REM sleep without atonia (RSWA) and consequently increased muscle activity. However, some muscle twitching in normal subjects occurs...... during REM sleep. PURPOSE: There are no generally accepted methods for evaluation of this activity and a normal range has not been established. Consequently, there is a need for objective criteria. METHOD: In this study we propose a full-automatic method for detection of RSWA. REM sleep identification...... the number of outliers during REM sleep was used as a quantitative measure of muscle activity. RESULTS: The proposed method was able to automatically separate all iRBD test subjects from healthy elderly controls and subjects with periodic limb movement disorder. CONCLUSION: The proposed work is considered...

Improvement and automatization of a proportional alpha-beta counting system - FAG

International Nuclear Information System (INIS)

German, U.; Levinson, S.; Pelled, O.; Shemesh, Y.; Assido, H.

1997-01-01

An alpha and beta counting system - FAG*, for planchette samples is operated at the Health Physics department's laboratory of the NRCN. The original operation mode of the system was based on manual tasks handled by the FHT1 100 electronics. An option for a basic computer keyboard operation was available too. A computer with an appropriate I/O card was connected to the system and a new operating program was developed which enables full automatic control of the various components. The program includes activity calculations and statistical checks as well as data management. A bar-code laser system for sample number reading was integrated into the Alpha-Beta automatic counting system. The sample identification by means of an attached bar-code label enables unmistakable and reliable attribution of results to the counted sample. authors)

Modeling and Analysis of Surgery Patient Identification Using RFID

OpenAIRE

Byungho Jeong; Chen-Yang Cheng; Vittal Prabhu

2009-01-01

This article proposes a workflow and reliability model for surgery patient identification using RFID (Radio Frequency Identification). Certain types of mistakes may be prevented by automatically identifying the patient before surgery. The proposed workflow is designed to ensure that both the correct site and patient are engaged in the surgical process. The reliability model can be used to assess improvements in patients’ safety during this process. A proof-of-concept system is developed to ...

Radio frequency identification and its application in e-commerce

OpenAIRE

Bahr, Witold; Price, Brian J

2016-01-01

This chapter presents Radio Frequency Identification (RFID), which is one of the Automatic Identification and Data Capture (AIDC) technologies (Wamba and Boeck, 2008) and discusses the application of RFID in E-Commerce. Firstly RFID is defined and the tag and reader components of the RFID system are explained. Then historical context of RFID is briefly discussed. Next, RFID is contrasted with other AIDC technologies, especially the use of barcodes which are commonly applied in E-Commerce. Las...

Drunk identification using far infrared imagery based on DCT features in DWT domain

Science.gov (United States)

Xie, Zhihua; Jiang, Peng; Xiong, Ying; Li, Ke

2016-10-01

Drunk driving problem is a serious threat to traffic safety. Automatic drunk driver identification is vital to improve the traffic safety. This paper copes with automatic drunk driver detection using far infrared thermal images by the holistic features. To improve the robustness of drunk driver detection, instead of traditional local pixels, a holistic feature extraction method is proposed to attain compact and discriminative features for infrared face drunk identification. Discrete cosine transform (DCT) in discrete wavelet transform (DWT) domain is used to extract the useful features in infrared face images for its high speed. Then, the first six DCT coefficients are retained for drunk classification by means of "Z" scanning. Finally, SVM is applied to classify the drunk person. Experimental results illustrate that the accuracy rate of proposed infrared face drunk identification can reach 98.5% with high computation efficiency, which can be applied in real drunk driver detection system.

Automatic Text Analysis Based on Transition Phenomena of Word Occurrences

Science.gov (United States)

Pao, Miranda Lee

1978-01-01

Describes a method of selecting index terms directly from a word frequency list, an idea originally suggested by Goffman. Results of the analysis of word frequencies of two articles seem to indicate that the automated selection of index terms from a frequency list holds some promise for automatic indexing. (Author/MBR)

Radio Frequency Identification in Construction Operation and Maintenance

DEFF Research Database (Denmark)

Sørensen, Kristian Birch; Christiansson, Per; Svidt, Kjeld

2008-01-01

As early as in 1995 it was stated that automatic identification of objects using RFID was a promising technology for the construction industry. However, 13 years later the applications of RFID in the construction industry are rare and mostly used in prototype projects or used for theft prevention...

Learning connective-based word representations for implicit discourse relation identification

DEFF Research Database (Denmark)

Braud, Chloé Elodie; Denis, Pascal

2016-01-01

We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represen...... their simplicity, these connective-based rep-resentations outperform various off-the-shelf word embeddings, and achieve state-of-the-art performance on this problem.......We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represent...... words in the space of discourse connectives as a way to directly encode their rhetorical function. Experiments on the Penn Discourse Treebank demonstrate the effectiveness of these task-tailored repre-sentations in predicting implicit discourse re-lations. Our results indeed show that, despite...

Uranium casting furnace automatic temperature control development

International Nuclear Information System (INIS)

Lind, R.F.

1992-01-01

Development of an automatic molten uranium temperature control system for use on batch-type induction casting furnaces is described. Implementation of a two-color optical pyrometer, development of an optical scanner for the pyrometer, determination of furnace thermal dynamics, and design of control systems are addressed. The optical scanning system is shown to greatly improve pyrometer measurement repeatability, particularly where heavy floating slag accumulations cause surface temperature gradients. Thermal dynamics of the furnaces were determined by applying least-squares system identification techniques to actual production data. A unity feedback control system utilizing a proportional-integral-derivative compensator is designed by using frequency-domain techniques. 14 refs

Identification of pumping influences in long-term water level fluctuations.

Science.gov (United States)

Harp, Dylan R; Vesselinov, Velimir V

2011-01-01

Identification of the pumping influences at monitoring wells caused by spatially and temporally variable water supply pumping can be a challenging, yet an important hydrogeological task. The information that can be obtained can be critical for conceptualization of the hydrogeological conditions and indications of the zone of influence of the individual pumping wells. However, the pumping influences are often intermittent and small in magnitude with variable production rates from multiple pumping wells. While these difficulties may support an inclination to abandon the existing dataset and conduct a dedicated cross-hole pumping test, that option can be challenging and expensive to coordinate and execute. This paper presents a method that utilizes a simple analytical modeling approach for analysis of a long-term water level record utilizing an inverse modeling approach. The methodology allows the identification of pumping wells influencing the water level fluctuations. Thus, the analysis provides an efficient and cost-effective alternative to designed and coordinated cross-hole pumping tests. We apply this method on a dataset from the Los Alamos National Laboratory site. Our analysis also provides (1) an evaluation of the information content of the transient water level data; (2) indications of potential structures of the aquifer heterogeneity inhibiting or promoting pressure propagation; and (3) guidance for the development of more complicated models requiring detailed specification of the aquifer heterogeneity. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

Automatic detection of P- and S-wave arrival times: new strategies based on the modified fractal method and basic matching pursuit.

Science.gov (United States)

Chi Durán, R. K.; Comte, D.; Diaz, M. A.; Silva, J. F.

2017-12-01

In this work, new strategies for automatic identification of P- and S-wave arrival times from digital recorded local seismograms are proposed and analyzed. The database of arrival times previously identified by a human reader was compared with automatic identification techniques based on the Fourier transformation in reduced time (spectrograms), fractal analysis, and the basic matching pursuit algorithm. The first two techniques were used to identify the P-wave arrival times, while the third was used for the identification of the S-wave. For validation, the results were compared with the short-time average over long-time average (STA/LTA) of Rietbrock et al., Geophys Res Lett 39(8), (2012) for the database of aftershocks of the 2010 Maule Mw = 8.8 earthquake. The identifiers proposed in this work exhibit good results that outperform the STA/LTA identifier in many scenarios. The average difference from the reference picks (times obtained by the human reader) in P- and S-wave arrival times is 1 s.

Two-dimensional PCA-based human gait identification

Science.gov (United States)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

Analogue particle identifier and test unit for automatic measuring of errors

International Nuclear Information System (INIS)

Boden, A.; Lauch, J.

1979-04-01

A high accuracy analogue particle identifier is described. The unit is used for particle identification or data correction of experimental based errors in magnetic spectrometers. Signals which are proportional to the energy, the time-of-flight or the position of absorption of the particles are supplied to an analogue computation circuit (multifunction converter). Three computation functions are available for different applications. The output of the identifier produces correction signals or pulses whose amplitudes are proportional to the mass of the particles. Particle identification and data correction can be optimized by the adjustment of variable parameters. An automatic test unit has been developed for adjustment and routine checking of particle identifiers. The computation functions can be tested by this unit with an accuracy of 1%. (orig.) [de

Direct spondylolisthesis identification and measurement in MR/CT using detectors trained by articulated parameterized spine model

Science.gov (United States)

Cai, Yunliang; Leung, Stephanie; Warrington, James; Pandey, Sachin; Shmuilovich, Olga; Li, Shuo

2017-02-01

The identification of spondylolysis and spondylolisthesis is important in spinal diagnosis, rehabilitation, and surgery planning. Accurate and automatic detection of spinal portion with spondylolisthesis problem will significantly reduce the manual work of physician and provide a more robust evaluation for the spine condition. Most existing automatic identification methods adopted the indirect approach which used vertebrae locations to measure the spondylolisthesis. However, these methods relied heavily on automatic vertebra detection which often suffered from the pool spatial accuracy and the lack of validated pathological training samples. In this study, we present a novel spondylolisthesis detection method which can directly locate the irregular spine portion and output the corresponding grading. The detection is done by a set of learning-based detectors which are discriminatively trained by synthesized spondylolisthesis image samples. To provide sufficient pathological training samples, we used a parameterized spine model to synthesize different types of spondylolysis images from real MR/CT scans. The parameterized model can automatically locate the vertebrae in spine images and estimate their pose orientations, and can inversely alter the vertebrae locations and poses by changing the corresponding parameters. Various training samples can then be generated from only a few spine MR/CT images. The preliminary results suggest great potential for the fast and efficient spondylolisthesis identification and measurement in both MR and CT spine images.

ACTIV - a program for automatic processing of gamma-ray spectra

International Nuclear Information System (INIS)

Zlokazov, V.B.

1982-01-01

Program ACTIV is intended for precise analysis of γ-rays and X-ray spectra and allows the user to carry out the full cycle of automatic processing of a series of spectra, i.e. calibration, automatic peak search, determination of peak positions and areas, identification of the radioisotopes and the transformation of the areas found into masses of isotopes in the irradiated sample. ACTIV uses a complex mathematical technique and is oriented mainly to large computers, but using overlaid loading, it can be run also on small computers like the PDP 11/70. Compared with other similar programs, ACTIV has some advantages in accuracy of peak shape description and in the reliability of the peak search and its least-square analysis. The program can be used for the purpose of activation analysis. The program can analyze spectra with poor statistics and with broad and narrow peaks. (orig.)

Automatic Type Recognition and Mapping of Global Tropical Cyclone Disaster Chains (TDC

Directory of Open Access Journals (Sweden)

Ran Wang

2016-10-01

Full Text Available The catastrophic events caused by meteorological disasters are becoming more severe in the context of global warming. The disaster chains triggered by Tropical Cyclones induce the serious losses of population and economy. It is necessary to make the regional type recognition of Tropical Cyclone Disaster Chain (TDC effective in order to make targeted preventions. This study mainly explores the method of automatic recognition and the mapping of TDC and designs a software system. We constructed an automatic recognition system in terms of the characteristics of a hazard-formative environment based on the theory of a natural disaster system. The ArcEngine components enable an intelligent software system to present results by the automatic mapping approach. The study data comes from global metadata such as Digital Elevation Model (DEM, terrain slope, population density and Gross Domestic Product (GDP. The result shows that: (1 according to the characteristic of geomorphology type, we establish a type of recognition system for global TDC; (2 based on the recognition principle, we design a software system with the functions of automatic recognition and mapping; and (3 we validate the type of distribution in terms of real cases of TDC. The result shows that the automatic recognition function has good reliability. The study can provide the basis for targeted regional disaster prevention strategy, as well as regional sustainable development.

Automatic thematic content analysis: finding frames in news

NARCIS (Netherlands)

Odijk, D.; Burscher, B.; Vliegenthart, R.; de Rijke, M.; Jatowt, A.; Lim, E.P.; Ding, Y.; Miura, A.; Tezuka, T.; Dias, G.; Tanaka, K.; Flanagin, A.; Dai, B.T.

2013-01-01

Framing in news is the way in which journalists depict an issue in terms of a ‘central organizing idea.’ Frames can be a perspective on an issue. We explore the automatic classification of four generic news frames: conflict, human interest, economic consequences, and morality. Complex

Segmentation of Extrapulmonary Tuberculosis Infection Using Modified Automatic Seeded Region Growing

Directory of Open Access Journals (Sweden)

Nordin Abdul

2009-01-01

Full Text Available Abstract In the image segmentation process of positron emission tomography combined with computed tomography (PET/CT imaging, previous works used information in CT only for segmenting the image without utilizing the information that can be provided by PET. This paper proposes to utilize the hot spot values in PET to guide the segmentation in CT, in automatic image segmentation using seeded region growing (SRG technique. This automatic segmentation routine can be used as part of automatic diagnostic tools. In addition to the original initial seed selection using hot spot values in PET, this paper also introduces a new SRG growing criterion, the sliding windows. Fourteen images of patients having extrapulmonary tuberculosis have been examined using the above-mentioned method. To evaluate the performance of the modified SRG, three fidelity criteria are measured: percentage of under-segmentation area, percentage of over-segmentation area, and average time consumption. In terms of the under-segmentation percentage, SRG with average of the region growing criterion shows the least error percentage (51.85%. Meanwhile, SRG with local averaging and variance yielded the best results (2.67% for the over-segmentation percentage. In terms of the time complexity, the modified SRG with local averaging and variance growing criterion shows the best performance with 5.273 s average execution time. The results indicate that the proposed methods yield fairly good performance in terms of the over- and under-segmentation area. The results also demonstrated that the hot spot values in PET can be used to guide the automatic segmentation in CT image.

Prototype Design and Application of a Semi-circular Automatic Parking System

OpenAIRE

Atacak, Ismail; Erdogdu, Ertugrul

2017-01-01

Nowadays, with the increasing population in urban areas, the number of vehicles used in traffic has also increased in these areas. This has brought with it major problems that are caused by insufficient parking areas, in terms of traffic congestion, drivers and environment. In this study, in order to overcome these problems, a multi-storey automatic parking system that automatically performs vehicle recognition, vehicle parking, vehicle delivery and pricing processes has been designed and the...

Automatized system of radioactive material analysis

International Nuclear Information System (INIS)

Pchelkin, V.A.; Sviderskij, M.F.; Litvinov, V.A.; Lavrikov, S.A.

1979-01-01

An automatized system has been developed for the identification of substance, element and isotope content of radioactive materials on the basis of data obtained for studying physical-chemical properties of substances (with the help of atomic-absorption spectrometers, infrared spectrometer, mass-spectrometer, derivatograph etc.). The system is based on the following principles: independent operation of each device; a possibility of increasing the number of physical instruments and devices; modular properties of engineering and computer means; modular properties and standardization of mathematical equipment, high reliability of the system; continuity of programming languages; a possibility of controlling the devices with the help of high-level language, typification of the system; simple and easy service; low cost. Block-diagram of the system is given

The influence of short-term memory on standard discrimination and cued identification olfactory tasks.

Science.gov (United States)

Zucco, Gesualdo M; Hummel, Thomas; Tomaiuolo, Francesco; Stevenson, Richard J

2014-01-30

Amongst the techniques to assess olfactory functions, discrimination and cued identification are those most prone to the influence of odour short-term memory (STM). Discrimination task requires participants to detect the odd one out of three presented odourants. As re-smelling is not permitted, an un-intended STM load may generate, even though the task purports to assess discrimination ability. Analogously, cued identification task requires participants to smell an odour, and then select a label from three or four alternatives. As the interval between smelling and reading each label increases this too imposes a STM load, even though the task aims to measure identification ability. We tested whether modifying task design to reduce STM load improve performance on these tests. We examined five age-groups of participants (Adolescents, Young adults, Middle-aged, Elderly, very Elderly), some of whom should be more prone to the effects of STM load than others, on standard and modified tests of discrimination and identification. We found that using a technique to reduce STM load improved performance, especially for the very Elderly and Adolescent groups. Sources of error are now prevented. Findings indicate that STM load can adversely affect performance in groups vulnerable from memory impairment (i.e., very Elderly) and in those who may still be acquiring memory-based representations of familiar odours (i.e., Adolescents). It may be that adults in general would be even more sensitive to the effects of olfactory STM load reduction, if the odour-related task was more difficult. Copyright © 2013 Elsevier B.V. All rights reserved.

Automatic differentiation bibliography

Energy Technology Data Exchange (ETDEWEB)

Corliss, G.F. [comp.

1992-07-01

This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

Automatic evaluations and exercise setting preference in frequent exercisers.

Science.gov (United States)

Antoniewicz, Franziska; Brand, Ralf

2014-12-01

The goals of this study were to test whether exercise-related stimuli can elicit automatic evaluative responses and whether automatic evaluations reflect exercise setting preference in highly active exercisers. An adapted version of the Affect Misattribution Procedure was employed. Seventy-two highly active exercisers (26 years ± 9.03; 43% female) were subliminally primed (7 ms) with pictures depicting typical fitness center scenarios or gray rectangles (control primes). After each prime, participants consciously evaluated the "pleasantness" of a Chinese symbol. Controlled evaluations were measured with a questionnaire and were more positive in participants who regularly visited fitness centers than in those who reported avoiding this exercise setting. Only center exercisers gave automatic positive evaluations of the fitness center setting (partial eta squared = .08). It is proposed that a subliminal Affect Misattribution Procedure paradigm can elicit automatic evaluations to exercising and that, in highly active exercisers, these evaluations play a role in decisions about the exercise setting rather than the amounts of physical exercise. Findings are interpreted in terms of a dual systems theory of social information processing and behavior.

Language identification of information blocks based on lexico-grammatic markers

Directory of Open Access Journals (Sweden)

Sergey N. Kalegin

2017-12-01

Full Text Available This article is a continuation of the author's series of publications on the subjects of language identification of texts. In the article is being considered the creation of a technological basis for language identification systems of unstructured information blocks based on lexico-grammatical markers, in which are used the forms of verbs, verbal formations or functionally analogous constructions, are described method and algorithm for its software implementation. These developments will significantly reduce the resource intensity and improve the quality of such systems, which will give a significant economic effect and the possibility of creating fundamentally new technologies for determining the linguistic affiliation of information in a multilingual environment. Consequently, the study is of interest for computer linguists and developers of automatic word processing systems, such as: global monitoring systems, multilingual knowledge bases, automatic translation systems, information retrieval systems, document summarizing systems, literature catalogers, etc.

A framework for automatic custom instruction identification on multi-issue ASIPs

NARCIS (Netherlands)

Nery, A.S.; Nedjah, N.; Franca, F.M.G.; Jozwiak, L.; Corporaal, H.

2014-01-01

Custom Instruction Identification is an important part in the design of efficient Application-Specific Processors (ASIPs). It consists of profiling of a given application to find patterns of basic operations that are frequently executed. Operations of such patterns can be implemented together as a

Automatic Detection of Childhood Absence Epilepsy Seizures: Toward a Monitoring Device

DEFF Research Database (Denmark)

Duun-Henriksen, Jonas; Madsen, Rasmus E.; Remvig, Line S.

2012-01-01

Automatic detections of paroxysms in patients with childhood absence epilepsy have been neglected for several years. We acquire reliable detections using only a single-channel brainwave monitor, allowing for unobtrusive monitoring of antiepileptic drug effects. Ultimately we seek to obtain optimal...... long-term prognoses, balancing antiepileptic effects and side effects. The electroencephalographic appearance of paroxysms in childhood absence epilepsy is fairly homogeneous, making it feasible to develop patient-independent automatic detection. We implemented a state-of-the-art algorithm...

An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework.

Science.gov (United States)

Wolterink, Jelmer M; Leiner, Tim; de Vos, Bob D; Coatrieux, Jean-Louis; Kelm, B Michael; Kondo, Satoshi; Salgado, Rodrigo A; Shahzad, Rahil; Shu, Huazhong; Snoeren, Miranda; Takx, Richard A P; van Vliet, Lucas J; van Walsum, Theo; Willems, Tineke P; Yang, Guanyu; Zheng, Yefeng; Viergever, Max A; Išgum, Ivana

2016-05-01

The amount of coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular disease (CVD) events. In clinical practice, CAC is manually identified and automatically quantified in cardiac CT using commercially available software. This is a tedious and time-consuming process in large-scale studies. Therefore, a number of automatic methods that require no interaction and semiautomatic methods that require very limited interaction for the identification of CAC in cardiac CT have been proposed. Thus far, a comparison of their performance has been lacking. The objective of this study was to perform an independent evaluation of (semi)automatic methods for CAC scoring in cardiac CT using a publicly available standardized framework. Cardiac CT exams of 72 patients distributed over four CVD risk categories were provided for (semi)automatic CAC scoring. Each exam consisted of a noncontrast-enhanced calcium scoring CT (CSCT) and a corresponding coronary CT angiography (CCTA) scan. The exams were acquired in four different hospitals using state-of-the-art equipment from four major CT scanner vendors. The data were divided into 32 training exams and 40 test exams. A reference standard for CAC in CSCT was defined by consensus of two experts following a clinical protocol. The framework organizers evaluated the performance of (semi)automatic methods on test CSCT scans, per lesion, artery, and patient. Five (semi)automatic methods were evaluated. Four methods used both CSCT and CCTA to identify CAC, and one method used only CSCT. The evaluated methods correctly detected between 52% and 94% of CAC lesions with positive predictive values between 65% and 96%. Lesions in distal coronary arteries were most commonly missed and aortic calcifications close to the coronary ostia were the most common false positive errors. The majority (between 88% and 98%) of correctly identified CAC lesions were assigned to the correct artery. Linearly weighted Cohen's kappa

Automatic NMR-based identification of chemical reaction types in mixtures of co-occurring reactions.

Science.gov (United States)

Latino, Diogo A R S; Aires-de-Sousa, João

2014-01-01

The combination of chemoinformatics approaches with NMR techniques and the increasing availability of data allow the resolution of problems far beyond the original application of NMR in structure elucidation/verification. The diversity of applications can range from process monitoring, metabolic profiling, authentication of products, to quality control. An application related to the automatic analysis of complex mixtures concerns mixtures of chemical reactions. We encoded mixtures of chemical reactions with the difference between the (1)H NMR spectra of the products and the reactants. All the signals arising from all the reactants of the co-occurring reactions were taken together (a simulated spectrum of the mixture of reactants) and the same was done for products. The difference spectrum is taken as the representation of the mixture of chemical reactions. A data set of 181 chemical reactions was used, each reaction manually assigned to one of 6 types. From this dataset, we simulated mixtures where two reactions of different types would occur simultaneously. Automatic learning methods were trained to classify the reactions occurring in a mixture from the (1)H NMR-based descriptor of the mixture. Unsupervised learning methods (self-organizing maps) produced a reasonable clustering of the mixtures by reaction type, and allowed the correct classification of 80% and 63% of the mixtures in two independent test sets of different similarity to the training set. With random forests (RF), the percentage of correct classifications was increased to 99% and 80% for the same test sets. The RF probability associated to the predictions yielded a robust indication of their reliability. This study demonstrates the possibility of applying machine learning methods to automatically identify types of co-occurring chemical reactions from NMR data. Using no explicit structural information about the reactions participants, reaction elucidation is performed without structure elucidation of

Automatic NMR-based identification of chemical reaction types in mixtures of co-occurring reactions.

Directory of Open Access Journals (Sweden)

Diogo A R S Latino

Full Text Available The combination of chemoinformatics approaches with NMR techniques and the increasing availability of data allow the resolution of problems far beyond the original application of NMR in structure elucidation/verification. The diversity of applications can range from process monitoring, metabolic profiling, authentication of products, to quality control. An application related to the automatic analysis of complex mixtures concerns mixtures of chemical reactions. We encoded mixtures of chemical reactions with the difference between the (1H NMR spectra of the products and the reactants. All the signals arising from all the reactants of the co-occurring reactions were taken together (a simulated spectrum of the mixture of reactants and the same was done for products. The difference spectrum is taken as the representation of the mixture of chemical reactions. A data set of 181 chemical reactions was used, each reaction manually assigned to one of 6 types. From this dataset, we simulated mixtures where two reactions of different types would occur simultaneously. Automatic learning methods were trained to classify the reactions occurring in a mixture from the (1H NMR-based descriptor of the mixture. Unsupervised learning methods (self-organizing maps produced a reasonable clustering of the mixtures by reaction type, and allowed the correct classification of 80% and 63% of the mixtures in two independent test sets of different similarity to the training set. With random forests (RF, the percentage of correct classifications was increased to 99% and 80% for the same test sets. The RF probability associated to the predictions yielded a robust indication of their reliability. This study demonstrates the possibility of applying machine learning methods to automatically identify types of co-occurring chemical reactions from NMR data. Using no explicit structural information about the reactions participants, reaction elucidation is performed without structure

Five-way smoking status classification using text hot-spot identification and error-correcting output codes.

Science.gov (United States)

Cohen, Aaron M

2008-01-01

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using micro- and macro-averaged F1 as the primary performance metric. Our best performing system achieved a micro-F1 of 0.9000 on the test collection, equivalent to the best performing system submitted to the i2b2 challenge. Hot-spot identification, zero-vector filtering, classifier weighting, and error correcting output coding contributed additively to increased performance, with hot-spot identification having by far the largest positive effect. High performance on automatic identification of patient smoking status from discharge summaries is achievable with the efficient and straightforward machine learning techniques studied here.

The UAB Informatics Institute and 2016 CEGS N-GRID de-identification shared task challenge.

Science.gov (United States)

Bui, Duy Duc An; Wyatt, Mathew; Cimino, James J

2017-11-01

Clinical narratives (the text notes found in patients' medical records) are important information sources for secondary use in research. However, in order to protect patient privacy, they must be de-identified prior to use. Manual de-identification is considered to be the gold standard approach but is tedious, expensive, slow, and impractical for use with large-scale clinical data. Automated or semi-automated de-identification using computer algorithms is a potentially promising alternative. The Informatics Institute of the University of Alabama at Birmingham is applying de-identification to clinical data drawn from the UAB hospital's electronic medical records system before releasing them for research. We participated in a shared task challenge by the Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-Scale and RDoC Individualized Domains (N-GRID) at the de-identification regular track to gain experience developing our own automatic de-identification tool. We focused on the popular and successful methods from previous challenges: rule-based, dictionary-matching, and machine-learning approaches. We also explored new techniques such as disambiguation rules, term ambiguity measurement, and used multi-pass sieve framework at a micro level. For the challenge's primary measure (strict entity), our submissions achieved competitive results (f-measures: 87.3%, 87.1%, and 86.7%). For our preferred measure (binary token HIPAA), our submissions achieved superior results (f-measures: 93.7%, 93.6%, and 93%). With those encouraging results, we gain the confidence to improve and use the tool for the real de-identification task at the UAB Informatics Institute. Copyright © 2017 Elsevier Inc. All rights reserved.

Face Prediction Model for an Automatic Age-invariant Face Recognition System

OpenAIRE

Yadav, Poonam

2015-01-01

07.11.14 KB. Emailed author re copyright. Author says that copyright is retained by author. Ok to add to spiral Automated face recognition and identi cation softwares are becoming part of our daily life; it nds its abode not only with Facebooks auto photo tagging, Apples iPhoto, Googles Picasa, Microsofts Kinect, but also in Homeland Security Departments dedicated biometric face detection systems. Most of these automatic face identification systems fail where the e ects of aging come into...

The emergence of radiofrequency identification tags: applications in surgery.

Science.gov (United States)

Schwaitzberg, S D

2006-08-01

Radiofrequency identification (RFID) is a wireless method of automatic identification. Currently, RFID tags are emerging into our environment in many aspects of our lives. Applications are being developed in a variety of fields, including health care. Aspects of surgical care will lend themselves to this approach. This technology could provide large amounts of data that not only carry the promise of improving health care, but also may have an impact on personal aspects of our daily lives. Each of us must become familiar with the risks and benefits of RFID use.

RFID explained a primer on radio frequency identification technologies

CERN Document Server

Want, Roy

2006-01-01

This lecture provides an introduction to Radio Frequency Identification (RFID), a technology enabling automatic identification of objects at a distance without requiring line-of-sight. Electronic tagging can be divided into technologies that have a power source (active tags), and those that are powered by the tag interrogation signal (passive tags); the focus here is on passive tags. An overview of the principles of the technology divides passive tags into devices that use either near field or far field coupling to communicate with a tag reader. The strengths and weaknesses of the approaches a

48 CFR 252.211-7006 - Radio Frequency Identification.

Science.gov (United States)

2010-10-01

... supply, as defined in DoD 4140.1-R, DoD Supply Chain Materiel Management Regulation, AP1.1.11: (A... International and the Uniform Code Council to establish and support the EPC network as the global standard for immediate, automatic, and accurate identification of any item in the supply chain of any company, in any...

Feature extraction and classification in automatic weld seam radioscopy

International Nuclear Information System (INIS)

Heindoerfer, F.; Pohle, R.

1994-01-01

The investigations conducted have shown that automatic feature extraction and classification procedures permit the identification of weld seam flaws. Within this context the favored learning fuzzy classificator represents a very good alternative to conventional classificators. The results have also made clear that improvements mainly in the field of image registration are still possible by increasing the resolution of the radioscopy system. Since, only if the flaw is segmented correctly, i.e. in its full size, and due to improved detail recognizability and sufficient contrast difference will an almost error-free classification be conceivable. (orig./MM) [de

Automatic blood vessel based-liver segmentation using the portal phase abdominal CT

Science.gov (United States)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2018-02-01

Liver segmentation is the basis for computer-based planning of hepatic surgical interventions. In diagnosis and analysis of hepatic diseases and surgery planning, automatic segmentation of liver has high importance. Blood vessel (BV) has showed high performance at liver segmentation. In our previous work, we developed a semi-automatic method that segments the liver through the portal phase abdominal CT images in two stages. First stage was interactive segmentation of abdominal blood vessels (ABVs) and subsequent classification into hepatic (HBVs) and non-hepatic (non-HBVs). This stage had 5 interactions that include selective threshold for bone segmentation, selecting two seed points for kidneys segmentation, selection of inferior vena cava (IVC) entrance for starting ABVs segmentation, identification of the portal vein (PV) entrance to the liver and the IVC-exit for classifying HBVs from other ABVs (non-HBVs). Second stage is automatic segmentation of the liver based on segmented ABVs as described in [4]. For full automation of our method we developed a method [5] that segments ABVs automatically tackling the first three interactions. In this paper, we propose full automation of classifying ABVs into HBVs and non- HBVs and consequently full automation of liver segmentation that we proposed in [4]. Results illustrate that the method is effective at segmentation of the liver through the portal abdominal CT images.

A prospective multicenter clinical feasibility study of a new automatic speaking valve for postlaryngectomy voice rehabilitation

NARCIS (Netherlands)

Lansaat, L.; de Kleijn, B. J.; Hilgers, F. J. M.; van der Laan, B. F. A. M.; van den Brekel, M. W. M.

Evaluation of short- and long-term clinical feasibility and exploration of limitations and advantages of a new automatic speaking valve (ASV) for laryngectomized patients with integrated HME, the Provox FreeHands FlexiVoice (FlexiVoice). This ASV not only enables automatic, but also manual closure

Image-based automatic recognition of larvae

Science.gov (United States)

Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

2010-08-01

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Rapid Identification of Microorganisms from Positive Blood Culture by MALDI-TOF MS After Short-Term Incubation on Solid Medium.

Science.gov (United States)

Curtoni, Antonio; Cipriani, Raffaella; Marra, Elisa Simona; Barbui, Anna Maria; Cavallo, Rossana; Costa, Cristina

2017-01-01

Matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) is a useful tool for rapid identification of microorganisms. Unfortunately, its direct application to positive blood culture is still lacking standardized procedures. In this study, we evaluated an easy- and rapid-to-perform protocol for MALDI-TOF MS direct identification of microorganisms from positive blood culture after a short-term incubation on solid medium. This protocol was used to evaluate direct identification of microorganisms from 162 positive monomicrobial blood cultures; at different incubation times (3, 5, 24 h), MALDI-TOF MS assay was performed from the growing microorganism patina. Overall, MALDI-TOF MS concordance with conventional methods at species level was 60.5, 80.2, and 93.8% at 3, 5, and 24 h, respectively. Considering only bacteria, the identification performances at species level were 64.1, 85.0, and 94.1% at 3, 5, and 24 h, respectively. This protocol applied to a commercially available MS typing system may represent, a fast and powerful diagnostic tool for pathogen direct identification and for a promptly and pathogen-driven antimicrobial therapy in selected cases.

Automatic dirt trail analysis in dermoscopy images.

Science.gov (United States)

Cheng, Beibei; Joe Stanley, R; Stoecker, William V; Osterwise, Christopher T P; Stricklin, Sherea M; Hinton, Kristen A; Moss, Randy H; Oliviero, Margaret; Rabinovitz, Harold S

2013-02-01

Basal cell carcinoma (BCC) is the most common cancer in the US. Dermatoscopes are devices used by physicians to facilitate the early detection of these cancers based on the identification of skin lesion structures often specific to BCCs. One new lesion structure, referred to as dirt trails, has the appearance of dark gray, brown or black dots and clods of varying sizes distributed in elongated clusters with indistinct borders, often appearing as curvilinear trails. In this research, we explore a dirt trail detection and analysis algorithm for extracting, measuring, and characterizing dirt trails based on size, distribution, and color in dermoscopic skin lesion images. These dirt trails are then used to automatically discriminate BCC from benign skin lesions. For an experimental data set of 35 BCC images with dirt trails and 79 benign lesion images, a neural network-based classifier achieved a 0.902 are under a receiver operating characteristic curve using a leave-one-out approach. Results obtained from this study show that automatic detection of dirt trails in dermoscopic images of BCC is feasible. This is important because of the large number of these skin cancers seen every year and the challenge of discovering these earlier with instrumentation. © 2011 John Wiley & Sons A/S.

Automatic Fiscal Stabilizers

Directory of Open Access Journals (Sweden)

Narcis Eduard Mitu

2013-11-01

Full Text Available Policies or institutions (built into an economic system that automatically tend to dampen economic cycle fluctuations in income, employment, etc., without direct government intervention. For example, in boom times, progressive income tax automatically reduces money supply as incomes and spendings rise. Similarly, in recessionary times, payment of unemployment benefits injects more money in the system and stimulates demand. Also called automatic stabilizers or built-in stabilizers.

Source term identification in atmospheric modelling via sparse optimization

Science.gov (United States)

Adam, Lukas; Branda, Martin; Hamburger, Thomas

2015-04-01

Inverse modelling plays an important role in identifying the amount of harmful substances released into atmosphere during major incidents such as power plant accidents or volcano eruptions. Another possible application of inverse modelling lies in the monitoring the CO2 emission limits where only observations at certain places are available and the task is to estimate the total releases at given locations. This gives rise to minimizing the discrepancy between the observations and the model predictions. There are two standard ways of solving such problems. In the first one, this discrepancy is regularized by adding additional terms. Such terms may include Tikhonov regularization, distance from a priori information or a smoothing term. The resulting, usually quadratic, problem is then solved via standard optimization solvers. The second approach assumes that the error term has a (normal) distribution and makes use of Bayesian modelling to identify the source term. Instead of following the above-mentioned approaches, we utilize techniques from the field of compressive sensing. Such techniques look for a sparsest solution (solution with the smallest number of nonzeros) of a linear system, where a maximal allowed error term may be added to this system. Even though this field is a developed one with many possible solution techniques, most of them do not consider even the simplest constraints which are naturally present in atmospheric modelling. One of such examples is the nonnegativity of release amounts. We believe that the concept of a sparse solution is natural in both problems of identification of the source location and of the time process of the source release. In the first case, it is usually assumed that there are only few release points and the task is to find them. In the second case, the time window is usually much longer than the duration of the actual release. In both cases, the optimal solution should contain a large amount of zeros, giving rise to the

Automatic extraction and identification of users' responses in Facebook medical quizzes.

Science.gov (United States)

Rodríguez-González, Alejandro; Menasalvas Ruiz, Ernestina; Mayer Pujadas, Miguel A

2016-04-01

In the last few years the use of social media in medicine has grown exponentially, providing a new area of research based on the analysis and use of Web 2.0 capabilities. In addition, the use of social media in medical education is a subject of particular interest which has been addressed in several studies. One example of this application is the medical quizzes of The New England Journal of Medicine (NEJM) that regularly publishes a set of questions through their Facebook timeline. We present an approach for the automatic extraction of medical quizzes and their associated answers on a Facebook platform by means of a set of computer-based methods and algorithms. We have developed a tool for the extraction and analysis of medical quizzes stored on Facebook timeline at the NEJM Facebook page, based on a set of computer-based methods and algorithms using Java. The system is divided into two main modules: Crawler and Data retrieval. The system was launched on December 31, 2014 and crawled through a total of 3004 valid posts and 200,081 valid comments. The first post was dated on July 23, 2009 and the last one on December 30, 2014. 285 quizzes were analyzed with 32,780 different users providing answers to the aforementioned quizzes. Of the 285 quizzes, patterns were found in 261 (91.58%). From these 261 quizzes where trends were found, we saw that users follow trends of incorrect answers in 13 quizzes and trends of correct answers in 248. This tool is capable of automatically identifying the correct and wrong answers to a quiz provided on Facebook posts in a text format to a quiz, with a small rate of false negative cases and this approach could be applicable to the extraction and analysis of other sources after including some adaptations of the information on the Internet. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Increasing Accuracy: A New Design and Algorithm for Automatically Measuring Weights, Travel Direction and Radio Frequency Identification (RFID) of Penguins.

Science.gov (United States)

Afanasyev, Vsevolod; Buldyrev, Sergey V; Dunn, Michael J; Robst, Jeremy; Preston, Mark; Bremner, Steve F; Briggs, Dirk R; Brown, Ruth; Adlard, Stacey; Peat, Helen J

2015-01-01

A fully automated weighbridge using a new algorithm and mechanics integrated with a Radio Frequency Identification System is described. It is currently in use collecting data on Macaroni penguins (Eudyptes chrysolophus) at Bird Island, South Georgia. The technology allows researchers to collect very large, highly accurate datasets of both penguin weight and direction of their travel into or out of a breeding colony, providing important contributory information to help understand penguin breeding success, reproductive output and availability of prey. Reliable discrimination between single and multiple penguin crossings is demonstrated. Passive radio frequency tags implanted into penguins allow researchers to match weight and trip direction to individual birds. Low unit and operation costs, low maintenance needs, simple operator requirements and accurate time stamping of every record are all important features of this type of weighbridge, as is its proven ability to operate 24 hours a day throughout a breeding season, regardless of temperature or weather conditions. Users are able to define required levels of accuracy by adjusting filters and raw data are automatically recorded and stored allowing for a range of processing options. This paper presents the underlying principles, design specification and system description, provides evidence of the weighbridge's accurate performance and demonstrates how its design is a significant improvement on existing systems.

Choosing Actuators for Automatic Control Systems of Thermal Power Plants

Energy Technology Data Exchange (ETDEWEB)

Gorbunov, A. I., E-mail: gor@tornado.nsk.ru [JSC “Tornado Modular Systems” (Russian Federation); Serdyukov, O. V. [Siberian Branch of the Russian Academy of Sciences, Institute of Automation and Electrometry (Russian Federation)

2015-03-15

Two types of actuators for automatic control systems of thermal power plants are analyzed: (i) pulse-controlled actuator and (ii) analog-controlled actuator with positioning function. The actuators are compared in terms of control circuit, control accuracy, reliability, and cost.

Planning for Site Transition to Long-Term Stewardship: Identification of Requirements and Issues

International Nuclear Information System (INIS)

Banaee, J.

2002-01-01

A systematic methodology is presented and applied for the identification of requirements and issues pertaining to the planning for, and transition to, long term stewardship (LTS). The method has been applied to three of the twelve identified LTS functions. The results of the application of the methodology to contaminated and uncontaminated federal real property in those three functions are presented. The issues that could be seen as impediments to the implementation of LTS are also identified for the three areas under consideration. The identified requirements are significant and in some cases complex to implement. It is clear that early and careful planning is required in all circumstances

Planning for Site Transition to Long-Term Stewardship: Identification of Requirements and Issues

Energy Technology Data Exchange (ETDEWEB)

Banaee, J.

2002-05-16

A systematic methodology is presented and applied for the identification of requirements and issues pertaining to the planning for, and transition to, long term stewardship (LTS). The method has been applied to three of the twelve identified LTS functions. The results of the application of the methodology to contaminated and uncontaminated federal real property in those three functions are presented. The issues that could be seen as impediments to the implementation of LTS are also identified for the three areas under consideration. The identified requirements are significant and in some cases complex to implement. It is clear that early and careful planning is required in all circumstances.

Planning for Site Transition to Long-Term Stewardship: Identification of Requirements and Issues

Energy Technology Data Exchange (ETDEWEB)

Banaee, Jila

2002-08-01

A systematic methodology is presented and applied for the identification of requirements and issues pertaining to the planning for, and transition to, long term stewardship (LTS). The method has been applied to three of the twelve identified LTS functions. The results of the application of the methodology to contaminated and uncontaminated federal real property in those three functions are presented. The issues that could be seen as impediments to the implementation of LTS are also identified for the three areas under consideration. The identified requirements are significant and in some cases complex to implement. It is clear that early and careful planning is required in all circumstances.

An automated procedure for identification of a person using gait analysis

Directory of Open Access Journals (Sweden)

Alena Galajdová

2016-10-01

Full Text Available Different biometric methods are available for identification purpose of a person. The most commonly used are fingerprints, but there are also other biometric methods such as voice, morphology of ears, structure of iris and so on. In some cases, it is required to identify a person according to his/her biomechanical parameters or even his/her gait pattern. Gait is an outstanding biometric behavioural characteristic that is not widely used yet for identification purposes because efficient and proven automated processes are not yet available. Several systems and gait pattern databases have been developed for rapid evaluation and processing of gait. This article describes an original automated evaluation procedure of gait pattern and identification of unique gait parameters for automatic identification purposes.

Global Distribution Adjustment and Nonlinear Feature Transformation for Automatic Colorization

Directory of Open Access Journals (Sweden)

Terumasa Aoki

2018-01-01

Full Text Available Automatic colorization is generally classified into two groups: propagation-based methods and reference-based methods. In reference-based automatic colorization methods, color image(s are used as reference(s to reconstruct original color of a gray target image. The most important task here is to find the best matching pairs for all pixels between reference and target images in order to transfer color information from reference to target pixels. A lot of attractive local feature-based image matching methods have already been developed for the last two decades. Unfortunately, as far as we know, there are no optimal matching methods for automatic colorization because the requirements for pixel matching in automatic colorization are wholly different from those for traditional image matching. To design an efficient matching algorithm for automatic colorization, clustering pixel with low computational cost and generating descriptive feature vector are the most important challenges to be solved. In this paper, we present a novel method to address these two problems. In particular, our work concentrates on solving the second problem (designing a descriptive feature vector; namely, we will discuss how to learn a descriptive texture feature using scaled sparse texture feature combining with a nonlinear transformation to construct an optimal feature descriptor. Our experimental results show our proposed method outperforms the state-of-the-art methods in terms of robustness for color reconstruction for automatic colorization applications.

Development of the Automatic Modeling System for Reaction Mechanisms Using REX+JGG

Science.gov (United States)

Takahashi, Takahiro; Kawai, Kohei; Nakai, Hiroyuki; Ema, Yoshinori

The identification of appropriate reaction models is very helpful for developing chemical vapor deposition (CVD) processes. In this study, we developed an automatic modeling system that analyzes experimental data on the cross- sectional shapes of films deposited on substrates with nanometer- or micrometer-sized trenches. The system then identifies a suitable reaction model to describe the film deposition. The inference engine used by the system to model the reaction mechanism was designed using real-coded genetic algorithms (RCGAs): a generation alternation model named "just generation gap" (JGG) and a real-coded crossover named "real-coded ensemble crossover" (REX). We studied the effect of REX+JGG on the system's performance, and found that the system with REX+JGG was the most accurate and reliable at model identification among the algorithms that we studied.

Semi-automatic Term Extraction for the African Languages, with ...

African Journals Online (AJOL)

rbr

for the treatment of single-word terms versus multi-word terms; and the various findings are sum- marised in a ... these days in many different types of dictionary to use the systematic evidence .... not form the focus of the current investigation. ..... When one studies the first 25 unique terms on the KeyWord list, one sees that.

Annual review in automatic programming

CERN Document Server

Goodman, Richard

2014-01-01

Annual Review in Automatic Programming, Volume 2 is a collection of papers that discusses the controversy about the suitability of COBOL as a common business oriented language, and the development of different common languages for scientific computation. A couple of papers describes the use of the Genie system in numerical calculation and analyzes Mercury autocode in terms of a phrase structure language, such as in the source language, target language, the order structure of ATLAS, and the meta-syntactical language of the assembly program. Other papers explain interference or an ""intermediate

An Automatic Parameter Identification Method for a PMSM Drive with LC-Filter

DEFF Research Database (Denmark)

Bech, Michael Møller; Christensen, Jeppe Haals; Weber, Magnus L.

2016-01-01

of the PMSM fed through an LC-filter. Based on the measured current response, model parameters for both the filter (L, R, C) and the PMSM (L and R) are estimated: First, the frequency response of the system is estimated using Welch Modified Periodogram method and then an optimization algorithm is used to find...... the parameters in an analytical reference model that minimize the model error. To demonstrate the practical feasibility of the method, a fully functional drive including an embedded real-time controller has been built. In addition to modulation, data acquisition and control the whole parameter identification...... method is also implemented on the real-time controller. Based on laboratory experiments on a 22 kW drive, it is concluded that the embedded identification method can estimate the five parameters in less than ten seconds....

Radio frequency identification and sensors from rfid to chipless RFID

CERN Document Server

Perret, Etienne

2014-01-01

This book deals with the field of identification and sensors, more precisely the possibility of collecting information remotely with RF waves (RFID). The book introduces the technology of chipless RFID starting from classical RFID and barcode, and explores the field of identification and sensors without wire, without batteries, without chip, and with tags that can even be printed on paper. A technique for automatic design of UHF RFID tags is presented , aiming at making the tags as insensitive as possible to the environment (with the ability to increase the reading range reliability), or, co

Shift operation control of automatic transmission by {mu}-synthesis; {mu} synthesis ni yoru jido hensokuki no hensoku seigyo

Energy Technology Data Exchange (ETDEWEB)

Nagaoka, M; Nishiyama, Y; Nakayama, Y; Kamada, S [Mazda Motor Corp., Hiroshima (Japan)

1997-10-01

We have developed a control technology, which the robust control theory is applied, to improve a shift quality of automatic transmission for a passenger car. When applying the robust control theory to the transmission control, many issue arise such as difficulty in system identification and/or the capability of ECU for computing. Recently, We have obtained an exact performance that allows the transmission to be robust controlled with an onboard ECU by improving the system identification process and reducing the model dimensions after the controller design finalized. 6 refs., 7 figs.

Musical Instrument Identification using Multiscale Mel-frequency Cepstral Coefficients

DEFF Research Database (Denmark)

Sturm, Bob L.; Morvidone, Marcela; Daudet, Laurent

2010-01-01

We investigate the benefits of evaluating Mel-frequency cepstral coefficients (MFCCs) over several time scales in the context of automatic musical instrument identification for signals that are monophonic but derived from real musical settings. We define several sets of features derived from MFCC...... multiscale decompositions perform significantly better than features computed using a single time-resolution....

Application of image recognition-based automatic hyphae detection in fungal keratitis.

Science.gov (United States)

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal

Automatic detection and visualisation of MEG ripple oscillations in epilepsy

Directory of Open Access Journals (Sweden)

Nicole van Klink

2017-01-01

Full Text Available High frequency oscillations (HFOs, 80–500 Hz in invasive EEG are a biomarker for the epileptic focus. Ripples (80–250 Hz have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

Radio frequency identification (RFID) of dentures in long-term care facilities.

Science.gov (United States)

Madrid, Carlos; Korsvold, Tové; Rochat, Aline; Abarca, Marcelo

2012-03-01

The difficulty of identifying the ownership of lost dentures when found is a common and expensive problem in long term care facilities (LTCFs) and hospitals. The purpose of this study was to evaluate the reliability of using radiofrequency identification (RFID) in the identification of dentures for LTCF residents after 3 and 6 months. Thirty-eight residents of 2 LTCFs in Switzerland agreed to participate after providing informed consent. The tag was programmed with the family and first names of the participants and then inserted in the dentures. After placement of the tag, the information was read. A second and third assessment to review the functioning of the tag occurred at 3 and 6 months, and defective tags (if present) were reported and replaced. The data were analyzed with descriptive statistics. At the 3-month assessment of 34 residents (63 tags) 1 tag was unreadable and 62 tags (98.2%) were operational. At 6 months, the tags of 27 of the enrolled residents (50 tags) were available for review. No examined tag was defective at this time period. Within the limits of this study (number of patients, 6-month time span) RFID appears to be a reliable method of tracking and identifying dentures, with only 1 of 65 devices being unreadable at 3 months and 100% of 50 initially placed tags being readable at the end of the trial. Copyright © 2012 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

Automatic detection of adverse events to predict drug label changes using text and data mining techniques.

Science.gov (United States)

Gurulingappa, Harsha; Toldo, Luca; Rajput, Abdul Mateen; Kors, Jan A; Taweel, Adel; Tayrouz, Yorki

2013-11-01

The aim of this study was to assess the impact of automatically detected adverse event signals from text and open-source data on the prediction of drug label changes. Open-source adverse effect data were collected from FAERS, Yellow Cards and SIDER databases. A shallow linguistic relation extraction system (JSRE) was applied for extraction of adverse effects from MEDLINE case reports. Statistical approach was applied on the extracted datasets for signal detection and subsequent prediction of label changes issued for 29 drugs by the UK Regulatory Authority in 2009. 76% of drug label changes were automatically predicted. Out of these, 6% of drug label changes were detected only by text mining. JSRE enabled precise identification of four adverse drug events from MEDLINE that were undetectable otherwise. Changes in drug labels can be predicted automatically using data and text mining techniques. Text mining technology is mature and well-placed to support the pharmacovigilance tasks. Copyright © 2013 John Wiley & Sons, Ltd.

Automatic radar target recognition of objects falling on railway tracks

International Nuclear Information System (INIS)

Mroué, A; Heddebaut, M; Elbahhar, F; Rivenq, A; Rouvaen, J-M

2012-01-01

This paper presents an automatic radar target recognition procedure based on complex resonances using the signals provided by ultra-wideband radar. This procedure is dedicated to detection and identification of objects lying on railway tracks. For an efficient complex resonance extraction, a comparison between several pole extraction methods is illustrated. Therefore, preprocessing methods are presented aiming to remove most of the erroneous poles interfering with the discrimination scheme. Once physical poles are determined, a specific discrimination technique is introduced based on the Euclidean distances. Both simulation and experimental results are depicted showing an efficient discrimination of different targets including guided transport passengers

Mathematical modelling and quality indices optimization of automatic control systems of reactor facility

International Nuclear Information System (INIS)

Severin, V.P.

2007-01-01

The mathematical modeling of automatic control systems of reactor facility WWER-1000 with various regulator types is considered. The linear and nonlinear models of neutron power control systems of nuclear reactor WWER-1000 with various group numbers of delayed neutrons are designed. The results of optimization of direct quality indexes of neutron power control systems of nuclear reactor WWER-1000 are designed. The identification and optimization of level control systems with various regulator types of steam generator are executed

Automatic generation of stop word lists for information retrieval and analysis

Science.gov (United States)

Rose, Stuart J

2013-01-08

Methods and systems for automatically generating lists of stop words for information retrieval and analysis. Generation of the stop words can include providing a corpus of documents and a plurality of keywords. From the corpus of documents, a term list of all terms is constructed and both a keyword adjacency frequency and a keyword frequency are determined. If a ratio of the keyword adjacency frequency to the keyword frequency for a particular term on the term list is less than a predetermined value, then that term is excluded from the term list. The resulting term list is truncated based on predetermined criteria to form a stop word list.

A Study of Identification Performance of Facial Regions from CCTV Images

NARCIS (Netherlands)

Ali, Tauseef; Tome, Pedro; Fierrez, Julian; Vera-Rodriguez, Ruben; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Garain, Utpal; Shafait, Faisal

This paper focuses on automatic face identification for forensic applications. Forensic examiners compare different parts of the face image obtained from a closed-circuit television (CCTV) image with a database of mug shots or good quality image(s) taken from the suspect. In this work we study and

A study of identification performance of facial regions from CCTV images

NARCIS (Netherlands)

Ali, Tauseef; Tom, P.; Fierrez, J.; Vera-Rodriguez, R.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2012-01-01

This paper focuses on automatic face identification for forensic applications. Forensic examiners compare different parts of the face image obtained from a closed-circuit television (CCTV) image with a database of mug shots or good quality image(s) taken from the suspect. In this work we study and

Automatic calibration of gamma spectrometers

International Nuclear Information System (INIS)

Tluchor, D.; Jiranek, V.

1989-01-01

The principle is described of energy calibration of the spectrometric path based on the measurement of the standard of one radionuclide or a set of them. The entire computer-aided process is divided into three main steps, viz.: the insertion of the calibration standard by the operator; the start of the calibration program; energy calibration by the computer. The program was selected such that the spectrum identification should not depend on adjustment of the digital or analog elements of the gamma spectrometric measuring path. The ECL program is described for automatic energy calibration as is its control, the organization of data file ECL.DAT and the necessary hardware support. The computer-multichannel analyzer communication was provided using an interface pair of Canberra 8673V and Canberra 8573 operating in the RS-422 standard. All subroutines for communication with the multichannel analyzer were written in MACRO 11 while the main program and the other subroutines were written in FORTRAN-77. (E.J.). 1 tab., 4 refs

Portable and Automatic Moessbauer Analysis

International Nuclear Information System (INIS)

Souza, P. A. de; Garg, V. K.; Klingelhoefer, G.; Gellert, R.; Guetlich, P.

2002-01-01

A portable Moessbauer spectrometer, developed for extraterrestrial applications, opens up new industrial applications of MBS. But for industrial applications, an available tool for fast data analysis is also required, and it should be easy to handle. The analysis of Moessbauer spectra and their parameters is a barrier for the popularity of this wide-applicable spectroscopic technique in industry. Based on experience, the analysis of a Moessbauer spectrum is time-consuming and requires the dedication of a specialist. However, the analysis of Moessbauer spectra, from the fitting to the identification of the sample phases, can be faster using by genetic algorithms, fuzzy logic and artificial neural networks. Industrial applications are very specific ones and the data analysis can be performed using these algorithms. In combination with an automatic analysis, the Moessbauer spectrometer can be used as a probe instrument which covers the main industrial needs for an on-line monitoring of its products, processes and case studies. Some of these real industrial applications will be discussed.

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

Science.gov (United States)

Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

Directory of Open Access Journals (Sweden)

Yiyao Ye-Lin

2014-01-01

Full Text Available Electrohysterography (EHG is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Direct validation of atlas-based red nucleus identification for functional radiosurgery

International Nuclear Information System (INIS)

Stancanello, Joseph; Romanelli, Pantaleo; Sebastiano, Fabio; Modugno, Nicola; Muacevic, Alexander; Cerveri, Pietro; Esposito, Vincenzo; Ferrigno, Giancarlo; Uggeri, Fulvio; Cantore, Giampaolo

2007-01-01

Treatment targets in functional neurosurgery usually consist of selected structures within the thalamus and basal ganglia, which can be stimulated in order to affect specific brain pathways. Chronic electrical stimulation of these structures is a widely used approach for selected patients with advanced movement disorders. An alternative therapeutic solution consists of producing a lesion in the target nucleus, for example by means of radiosurgery, a noninvasive procedure, and this prevents the use of intraoperative microelectrode recording as a method for accurate target definition. The need to have accurate noninvasive localization of the target motivated our previous work on atlas-based identification; the aim of this present work is to provide additional validation of this approach based on the identification of the red nuclei (RN), which are located near the subthalamic nucleus (STN). Coordinates of RN were obtained from the Talairach and Tournoux (TT) atlas and transformed into the coordinates of the Montreal Neurological Institute (MNI) atlas, creating a mask representation of RN. The MNI atlas volume was nonrigidly registered onto the patient magnetic resonance imaging (MRI). This deformation field was then applied to the RN mask, providing its location on the patient MRI. Because RN are easily identifiable on 1.5 T T2-MRI images, they were manually delineated; the coordinates of the centers of mass of the manually and automatically identified structures were compared. Additionally, volumetric overlapping indices were calculated. Ten patients were examined by this technique. All indices indicated a high level of agreement between manually and automatically identified structures. These results not only confirm the accuracy of the method but also allow fine tuning of the automatic identification method to be performed

Finding weak points automatically

International Nuclear Information System (INIS)

Archinger, P.; Wassenberg, M.

1999-01-01

Operators of nuclear power stations have to carry out material tests at selected components by regular intervalls. Therefore a full automaticated test, which achieves a clearly higher reproducibility, compared to part automaticated variations, would provide a solution. In addition the full automaticated test reduces the dose of radiation for the test person. (orig.) [de

Automatic identification of NDA measured items: Use of E-tags

International Nuclear Information System (INIS)

Chitumbo, K.; Olsen, R.; Hatcher, C.R.; Kadner, S.P.

1995-01-01

This paper describes how electronic identification devices or E-tags could reduce the time spent by LAEA inspectors making nondestructive assay (NDA) measurements. As one example, the use of E-tags with a high-level neutron coincidence counter (HLNC) is discussed in detail. Sections of the paper include inspection procedures, system description, software, and future plans. Mounting of E-tabs, modifications to the HLNC, and the use of tamper indicating devices are also discussed. The technology appears to have wide application to different types of nuclear facilities and inspections and could significantly change NDA inspection procedures

Algorithms for the automatic identification of MARFEs and UFOs in JET database of visible camera videos

International Nuclear Information System (INIS)

Murari, A.; Camplani, M.; Cannas, B.; Usai, P.; Mazon, D.; Delaunay, F.

2010-01-01

MARFE instabilities and UFOs leave clear signatures in JET fast visible camera videos. Given the potential harmful consequences of these events, particularly as triggers of disruptions, it would be important to have the means of detecting them automatically. In this paper, the results of various algorithms to identify automatically the MARFEs and UFOs in JET visible videos are reported. The objective is to retrieve the videos, which have captured these events, exploring the whole JET database of images, as a preliminary step to the development of real-time identifiers in the future. For the detection of MARFEs, a complete identifier has been finalized, using morphological operators and Hu moments. The final algorithm manages to identify the videos with MARFEs with a success rate exceeding 80%. Due to the lack of a complete statistics of examples, the UFO identifier is less developed, but a preliminary code can detect UFOs quite reliably. (authors)

The automatic component of habit in health behavior: habit as cue-contingent automaticity.

Science.gov (United States)

Orbell, Sheina; Verplanken, Bas

2010-07-01

Habit might be usefully characterized as a form of automaticity that involves the association of a cue and a response. Three studies examined habitual automaticity in regard to different aspects of the cue-response relationship characteristic of unhealthy and healthy habits. In each study, habitual automaticity was assessed by the Self-Report Habit Index (SRHI). In Study 1 SRHI scores correlated with attentional bias to smoking cues in a Stroop task. Study 2 examined the ability of a habit cue to elicit an unwanted habit response. In a prospective field study, habitual automaticity in relation to smoking when drinking alcohol in a licensed public house (pub) predicted the likelihood of cigarette-related action slips 2 months later after smoking in pubs had become illegal. In Study 3 experimental group participants formed an implementation intention to floss in response to a specified situational cue. Habitual automaticity of dental flossing was rapidly enhanced compared to controls. The studies provided three different demonstrations of the importance of cues in the automatic operation of habits. Habitual automaticity assessed by the SRHI captured aspects of a habit that go beyond mere frequency or consistency of the behavior. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Development of a microcontroller-based automatic control system for the electrohydraulic total artificial heart.

Science.gov (United States)

Kim, H C; Khanwilkar, P S; Bearnson, G B; Olsen, D B

1997-01-01

An automatic physiological control system for the actively filled, alternately pumped ventricles of the volumetrically coupled, electrohydraulic total artificial heart (EHTAH) was developed for long-term use. The automatic control system must ensure that the device: 1) maintains a physiological response of cardiac output, 2) compensates for an nonphysiological condition, and 3) is stable, reliable, and operates at a high power efficiency. The developed automatic control system met these requirements both in vitro, in week-long continuous mock circulation tests, and in vivo, in acute open-chested animals (calves). Satisfactory results were also obtained in a series of chronic animal experiments, including 21 days of continuous operation of the fully automatic control mode, and 138 days of operation in a manual mode, in a 159-day calf implant.

Hierarchically structured identification and classification method for vibrational monitoring of reactor components

International Nuclear Information System (INIS)

Saedtler, E.

1981-01-01

The dissertation discusses: 1. Approximative filter algorithms for identification of systems and hierarchical structures. 2. Adaptive statistical pattern recognition and classification. 3. Parameter selection, extraction, and modelling for an automatic control system. 4. Design of a decision tree and an adaptive diagnostic system. (orig./RW) [de

A comparison of coronal mass ejections identified by manual and automatic methods

Directory of Open Access Journals (Sweden)

S. Yashiro

2008-10-01

Full Text Available Coronal mass ejections (CMEs are related to many phenomena (e.g. flares, solar energetic particles, geomagnetic storms, thus compiling of event catalogs is important for a global understanding these phenomena. CMEs have been identified manually for a long time, but in the SOHO era, automatic identification methods are being developed. In order to clarify the advantage and disadvantage of the manual and automatic CME catalogs, we examined the distributions of CME properties listed in the CDAW (manual and CACTus (automatic catalogs. Both catalogs have a good agreement on the wide CMEs (width>120° in their properties, while there is a significant discrepancy on the narrow CMEs (width≤30°: CACTus has a larger number of narrow CMEs than CDAW. We carried out an event-by-event examination of a sample of events and found that the CDAW catalog have missed many narrow CMEs during the solar maximum. Another significant discrepancy was found on the fast CMEs (speed>1000 km/s: the majority of the fast CDAW CMEs are wide and originate from low latitudes, while the fast CACTus CMEs are narrow and originate from all latitudes. Event-by-event examination of a sample of events suggests that CACTus has a problem on the detection of the fast CMEs.

Mining Twitter as a First Step toward Assessing the Adequacy of Gender Identification Terms on Intake Forms.

Science.gov (United States)

Hicks, Amanda; Hogan, William R; Rutherford, Michael; Malin, Bradley; Xie, Mengjun; Fellbaum, Christiane; Yin, Zhijun; Fabbri, Daniel; Hanna, Josh; Bian, Jiang

2015-01-01

The Institute of Medicine (IOM) recommends that health care providers collect data on gender identity. If these data are to be useful, they should utilize terms that characterize gender identity in a manner that is 1) sensitive to transgender and gender non-binary individuals (trans* people) and 2) semantically structured to render associated data meaningful to the health care professionals. We developed a set of tools and approaches for analyzing Twitter data as a basis for generating hypotheses on language used to identify gender and discuss gender-related issues across regions and population groups. We offer sample hypotheses regarding regional variations in the usage of certain terms such as 'genderqueer', 'genderfluid', and 'neutrois' and their usefulness as terms on intake forms. While these hypotheses cannot be directly validated with Twitter data alone, our data and tools help to formulate testable hypotheses and design future studies regarding the adequacy of gender identification terms on intake forms.

Microprocessor controlled system for automatic and semi-automatic syntheses of radiopharmaceuticals

International Nuclear Information System (INIS)

Ruth, T.J.; Adam, M.J.; Morris, D.; Jivan, S.

1986-01-01

A computer based system has been constructed to control the automatic synthesis of 2-deoxy-2-( 18 F)fluoro-D-glucose and is also being used in the development of an automatic synthesis of L-6-( 18 F)fluorodopa. (author)

An efficient approach to the evaluation of mid-term dynamic processes in power systems

Energy Technology Data Exchange (ETDEWEB)

Zivanovic, R M [Pretoria Technikon (South Africa); Popovic, D P [Nikola Tesla Inst., Belgrade (Yugoslavia). Power System Dept.

1993-01-01

This paper presents some improvements in the methodology for analysing mid-term dynamic processes in power systems. These improvements are: an efficient application of the hierarchical clustering algorithm to adaptive identification of coherent generator groups and a significant reduction of the mathematical model, on the basis of monitoring the state of only one generator in one of the established coherent groups. This enables a flexible, simple and fast transformation from the full to the reduced model and vice versa, a significant acceleration of the simulation while keeping the desired accuracy and the automatic use in continual dynamic analysis. Verification of the above mentioned contributions was performed on examples of the dynamic analysis of New England and Yugoslav power systems. (author)

Automatic analysis of microscopic images of red blood cell aggregates

Science.gov (United States)

Menichini, Pablo A.; Larese, Mónica G.; Riquelme, Bibiana D.

2015-06-01

Red blood cell aggregation is one of the most important factors in blood viscosity at stasis or at very low rates of flow. The basic structure of aggregates is a linear array of cell commonly termed as rouleaux. Enhanced or abnormal aggregation is seen in clinical conditions, such as diabetes and hypertension, producing alterations in the microcirculation, some of which can be analyzed through the characterization of aggregated cells. Frequently, image processing and analysis for the characterization of RBC aggregation were done manually or semi-automatically using interactive tools. We propose a system that processes images of RBC aggregation and automatically obtains the characterization and quantification of the different types of RBC aggregates. Present technique could be interesting to perform the adaptation as a routine used in hemorheological and Clinical Biochemistry Laboratories because this automatic method is rapid, efficient and economical, and at the same time independent of the user performing the analysis (repeatability of the analysis).

Automatic Camera Control

DEFF Research Database (Denmark)

Burelli, Paolo; Preuss, Mike

2014-01-01

Automatically generating computer animations is a challenging and complex problem with applications in games and film production. In this paper, we investigate howto translate a shot list for a virtual scene into a series of virtual camera configurations — i.e automatically controlling the virtual...

Automatic identification approach for high-performance liquid chromatography-multiple reaction monitoring fatty acid global profiling.

Science.gov (United States)

Tie, Cai; Hu, Ting; Jia, Zhi-Xin; Zhang, Jin-Lan

2015-08-18

Fatty acids (FAs) are a group of lipid molecules that are essential to organisms. As potential biomarkers for different diseases, FAs have attracted increasing attention from both biological researchers and the pharmaceutical industry. A sensitive and accurate method for globally profiling and identifying FAs is required for biomarker discovery. The high selectivity and sensitivity of high-performance liquid chromatography-multiple reaction monitoring (HPLC-MRM) gives it great potential to fulfill the need to identify FAs from complicated matrices. This paper developed a new approach for global FA profiling and identification for HPLC-MRM FA data mining. Mathematical models for identifying FAs were simulated using the isotope-induced retention time (RT) shift (IRS) and peak area ratios between parallel isotope peaks for a series of FA standards. The FA structures were predicated using another model based on the RT and molecular weight. Fully automated FA identification software was coded using the Qt platform based on these mathematical models. Different samples were used to verify the software. A high identification efficiency (greater than 75%) was observed when 96 FA species were identified in plasma. This FAs identification strategy promises to accelerate FA research and applications.

Automatic classification of liver scintigram patterns by computer

International Nuclear Information System (INIS)

Csernay, L.; Csirik, J.

1976-01-01

The pattern recognition of projection is one of the problems in the automatic evaluation of scintigrams. An algorythm and a computerized programme with the ability to classify the shapes of liver scintigrams has been elaborated by the authors. The programme differentiates not only normal and pathologic basic forms, but performs the identification of nine normal forms described by the literature. To pattern recognition structural and local parameters of the picture were defined. A detailed mechanism of the programme is given in their reports. The programme can classify 55 out of 60 actual liver scintigrams, a result different from subjective definition obtained in 5 cases. These were normal pattern of liver scans. No wrong definition was obtained when classifying normal and pathologic patterns

I RAN Fast and I Remembered What I Read: The Relationship between Reading, Rapid Automatic Naming, and Auditory and Visual Short-Term Memory

Directory of Open Access Journals (Sweden)

Sheila G. Crewther

2011-05-01

Full Text Available Although rapid automatic naming (RAN speed and short-term auditory memory are widely recognised as good predictors of reading ability in most age groups, the predictive value of short-term memory for visually presented digits for reading and RAN in young typically developing learner readers (mean age 91.5 months has seldom been investigated. We found that visual digit span is a better predictor of reading ability than auditory digit span in learner readers. A significant correlation has also been found between RAN speed and visual, but not auditory digit span. These results suggests that RAN speed may be a good predictor of a child's future reading ability and eventual fluency because like visual digit span, it is a measure of rate of access to memory for the visual icons and their semantic name and meaning. The results also suggest that auditory memory is not an important factor in young children learning to read.

Detection and identification of concealed weapons using matrix pencil

Science.gov (United States)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

Automatic discovery of the communication network topology for building a supercomputer model

Science.gov (United States)

Sobolev, Sergey; Stefanov, Konstantin; Voevodin, Vadim

2016-10-01

The Research Computing Center of Lomonosov Moscow State University is developing the Octotron software suite for automatic monitoring and mitigation of emergency situations in supercomputers so as to maximize hardware reliability. The suite is based on a software model of the supercomputer. The model uses a graph to describe the computing system components and their interconnections. One of the most complex components of a supercomputer that needs to be included in the model is its communication network. This work describes the proposed approach for automatically discovering the Ethernet communication network topology in a supercomputer and its description in terms of the Octotron model. This suite automatically detects computing nodes and switches, collects information about them and identifies their interconnections. The application of this approach is demonstrated on the "Lomonosov" and "Lomonosov-2" supercomputers.

Motor automaticity in Parkinson’s disease

Science.gov (United States)

Wu, Tao; Hallett, Mark; Chan, Piu

2017-01-01

Bradykinesia is the most important feature contributing to motor difficulties in Parkinson’s disease (PD). However, the pathophysiology underlying bradykinesia is not fully understood. One important aspect is that PD patients have difficulty in performing learned motor skills automatically, but this problem has been generally overlooked. Here we review motor automaticity associated motor deficits in PD, such as reduced arm swing, decreased stride length, freezing of gait, micrographia and reduced facial expression. Recent neuroimaging studies have revealed some neural mechanisms underlying impaired motor automaticity in PD, including less efficient neural coding of movement, failure to shift automated motor skills to the sensorimotor striatum, instability of the automatic mode within the striatum, and use of attentional control and/or compensatory efforts to execute movements usually performed automatically in healthy people. PD patients lose previously acquired automatic skills due to their impaired sensorimotor striatum, and have difficulty in acquiring new automatic skills or restoring lost motor skills. More investigations on the pathophysiology of motor automaticity, the effect of L-dopa or surgical treatments on automaticity, and the potential role of using measures of automaticity in early diagnosis of PD would be valuable. PMID:26102020

Ontology-Based High-Level Context Inference for Human Behavior Identification

Science.gov (United States)

Villalonga, Claudia; Razzaq, Muhammad Asif; Khan, Wajahat Ali; Pomares, Hector; Rojas, Ignacio; Lee, Sungyoung; Banos, Oresti

2016-01-01

Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is required to scale to long-term scenarios with a large number of users. PMID:27690050

Ontology-Based High-Level Context Inference for Human Behavior Identification

Directory of Open Access Journals (Sweden)

Claudia Villalonga

2016-09-01

Full Text Available Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is required to scale to long-term scenarios with a large number of users.

3D ear identification based on sparse representation.

Directory of Open Access Journals (Sweden)

Lin Zhang

Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

Directory of Open Access Journals (Sweden)

Dina Khattab

2014-01-01

Full Text Available This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique. GrabCut is considered as one of the semiautomatic image segmentation techniques, since it requires user interaction for the initialization of the segmentation process. The automation of the GrabCut technique is proposed as a modification of the original semiautomatic one in order to eliminate the user interaction. The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase. Comparisons with the original GrabCut show the efficiency of the proposed automatic technique in terms of segmentation, quality, and accuracy. As no explicit color space is recommended for every segmentation problem, automatic GrabCut is applied with RGB, HSV, CMY, XYZ, and YUV color spaces. The comparative study and experimental results using different color images show that RGB color space is the best color space representation for the set of the images used.

Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

Science.gov (United States)

Zare, Marzieh; Rezvani, Zahra; Benasich, April A

2016-07-01

This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Aircraft noise effects on sleep: a systematic comparison of EEG awakenings and automatically detected cardiac activations

International Nuclear Information System (INIS)

Basner, Mathias; Müller, Uwe; Elmenhorst, Eva-Maria; Kluge, Götz; Griefahn, Barbara

2008-01-01

Polysomnography is the gold standard for investigating noise effects on sleep, but data collection and analysis are sumptuous and expensive. We recently developed an algorithm for the automatic identification of cardiac activations associated with cortical arousals, which uses heart rate information derived from a single electrocardiogram (ECG) channel. We hypothesized that cardiac activations can be used as estimates for EEG awakenings. Polysomnographic EEG awakenings and automatically detected cardiac activations were systematically compared using laboratory data of 112 subjects (47 male, mean ± SD age 37.9 ± 13 years), 985 nights and 23 855 aircraft noise events (ANEs). The probability of automatically detected cardiac activations increased monotonically with increasing maximum sound pressure levels of ANEs, exceeding the probability of EEG awakenings by up to 18.1%. If spontaneous reactions were taken into account, exposure–response curves were practically identical for EEG awakenings and cardiac activations. Automatically detected cardiac activations may be used as estimates for EEG awakenings. More investigations are needed to further validate the ECG algorithm in the field and to investigate inter-individual differences in its ability to predict EEG awakenings. This inexpensive, objective and non-invasive method facilitates large-scale field studies on the effects of traffic noise on sleep

Automatic Photoelectric Telescope Service

International Nuclear Information System (INIS)

Genet, R.M.; Boyd, L.J.; Kissell, K.E.; Crawford, D.L.; Hall, D.S.; BDM Corp., McLean, VA; Kitt Peak National Observatory, Tucson, AZ; Dyer Observatory, Nashville, TN)

1987-01-01

Automatic observatories have the potential of gathering sizable amounts of high-quality astronomical data at low cost. The Automatic Photoelectric Telescope Service (APT Service) has realized this potential and is routinely making photometric observations of a large number of variable stars. However, without observers to provide on-site monitoring, it was necessary to incorporate special quality checks into the operation of the APT Service at its multiple automatic telescope installation on Mount Hopkins. 18 references

Automatic imitation: A meta-analysis.

Science.gov (United States)

Cracco, Emiel; Bardi, Lara; Desmet, Charlotte; Genschow, Oliver; Rigoni, Davide; De Coster, Lize; Radkova, Ina; Deschrijver, Eliane; Brass, Marcel

2018-05-01

Automatic imitation is the finding that movement execution is facilitated by compatible and impeded by incompatible observed movements. In the past 15 years, automatic imitation has been studied to understand the relation between perception and action in social interaction. Although research on this topic started in cognitive science, interest quickly spread to related disciplines such as social psychology, clinical psychology, and neuroscience. However, important theoretical questions have remained unanswered. Therefore, in the present meta-analysis, we evaluated seven key questions on automatic imitation. The results, based on 161 studies containing 226 experiments, revealed an overall effect size of g z = 0.95, 95% CI [0.88, 1.02]. Moderator analyses identified automatic imitation as a flexible, largely automatic process that is driven by movement and effector compatibility, but is also influenced by spatial compatibility. Automatic imitation was found to be stronger for forced choice tasks than for simple response tasks, for human agents than for nonhuman agents, and for goalless actions than for goal-directed actions. However, it was not modulated by more subtle factors such as animacy beliefs, motion profiles, or visual perspective. Finally, there was no evidence for a relation between automatic imitation and either empathy or autism. Among other things, these findings point toward actor-imitator similarity as a crucial modulator of automatic imitation and challenge the view that imitative tendencies are an indicator of social functioning. The current meta-analysis has important theoretical implications and sheds light on longstanding controversies in the literature on automatic imitation and related domains. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Exogenous (automatic) attention to emotional stimuli: a review

OpenAIRE

Carretié, Luis

2014-01-01

Current knowledge on the architecture of exogenous attention (also called automatic, bottom-up, or stimulus-driven attention, among other terms) has been mainly obtained from studies employing neutral, anodyne stimuli. Since, from an evolutionary perspective, exogenous attention can be understood as an adaptive tool for rapidly detecting salient events, reorienting processing resources to them, and enhancing processing mechanisms, emotional events (which are, by definition, salient for the in...

MRI in assessing children with learning disability, focal findings, and reduced automaticity.

Science.gov (United States)

Urion, David K; Huff, Hanalise V; Carullo, Maria Paulina

2015-08-18

In children with clinically diagnosed learning disabilities with focal findings on neurologic or neuropsychological evaluations, there is a hypothesized association between disorders in automaticity and focal structural abnormalities observed in brain MRIs. We undertook a retrospective analysis of cases referred to a tertiary-hospital-based learning disabilities program. Individuals were coded as having a focal deficit if either neurologic or neuropsychological evaluation demonstrated focal dysfunction. Those with abnormal MRI findings were categorized based on findings. Children with abnormalities from each of these categories were compared in terms of deficits in automaticity, as measured by the tasks of Rapid Automatized Naming, Rapid Alternating Stimulus Naming, or the timed motor performance battery from the Physical and Neurological Examination for Soft Signs. Data were compared in children with and without disorders of automaticity regarding type of brain structure abnormality. Of the 1,587 children evaluated, 127 had a focal deficit. Eighty-seven had a brain MRI (52 on 1.5-tesla machines and 35 on 3.0-tesla machines). Forty of these images were found to be abnormal. These children were compared with a clinic sample of 150 patients with learning disabilities and no focal findings on examination, who also had undergone MRI. Only 5 of the latter group had abnormalities on MRI. Reduced verbal automaticity was associated with cerebellar abnormalities, whereas reduced automaticity on motor or motor and verbal tasks was associated with white matter abnormalities. Reduced automaticity of retrieval and slow timed motor performance appear to be highly associated with MRI findings. © 2015 American Academy of Neurology.

Time-Efficient Cloning Attacks Identification in Large-Scale RFID Systems

Directory of Open Access Journals (Sweden)

Ju-min Zhao

2017-01-01

Full Text Available Radio Frequency Identification (RFID is an emerging technology for electronic labeling of objects for the purpose of automatically identifying, categorizing, locating, and tracking the objects. But in their current form RFID systems are susceptible to cloning attacks that seriously threaten RFID applications but are hard to prevent. Existing protocols aimed at detecting whether there are cloning attacks in single-reader RFID systems. In this paper, we investigate the cloning attacks identification in the multireader scenario and first propose a time-efficient protocol, called the time-efficient Cloning Attacks Identification Protocol (CAIP to identify all cloned tags in multireaders RFID systems. We evaluate the performance of CAIP through extensive simulations. The results show that CAIP can identify all the cloned tags in large-scale RFID systems fairly fast with required accuracy.

A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction

OpenAIRE

van Breen, Jolien A.; Spears, Russell; Kuppens, Toon; de Lemus, Soledad

2017-01-01

Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with f...

Automatic scatter detection in fluorescence landscapes by means of spherical principal component analysis

DEFF Research Database (Denmark)

Kotwa, Ewelina Katarzyna; Jørgensen, Bo Munk; Brockhoff, Per B.

2013-01-01

In this paper, we introduce a new method, based on spherical principal component analysis (S‐PCA), for the identification of Rayleigh and Raman scatters in fluorescence excitation–emission data. These scatters should be found and eliminated as a prestep before fitting parallel factor analysis...... models to the data, in order to avoid model degeneracies. The work is inspired and based on a previous research, where scatter removal was automatic (based on a robust version of PCA called ROBPCA) and required no visual data inspection but appeared to be computationally intensive. To overcome...... this drawback, we implement the fast S‐PCA in the scatter identification routine. Moreover, an additional pattern interpolation step that complements the method, based on robust regression, will be applied. In this way, substantial time savings are gained, and the user's engagement is restricted to a minimum...

Development of Automatic Visceral Fat Volume Calculation Software for CT Volume Data

Directory of Open Access Journals (Sweden)

Mitsutaka Nemoto

2014-01-01

Full Text Available Objective. To develop automatic visceral fat volume calculation software for computed tomography (CT volume data and to evaluate its feasibility. Methods. A total of 24 sets of whole-body CT volume data and anthropometric measurements were obtained, with three sets for each of four BMI categories (under 20, 20 to 25, 25 to 30, and over 30 in both sexes. True visceral fat volumes were defined on the basis of manual segmentation of the whole-body CT volume data by an experienced radiologist. Software to automatically calculate visceral fat volumes was developed using a region segmentation technique based on morphological analysis with CT value threshold. Automatically calculated visceral fat volumes were evaluated in terms of the correlation coefficient with the true volumes and the error relative to the true volume. Results. Automatic visceral fat volume calculation results of all 24 data sets were obtained successfully and the average calculation time was 252.7 seconds/case. The correlation coefficients between the true visceral fat volume and the automatically calculated visceral fat volume were over 0.999. Conclusions. The newly developed software is feasible for calculating visceral fat volumes in a reasonable time and was proved to have high accuracy.

First tests of a multi-wavelength mini-DIAL system for the automatic detection of greenhouse gases

Science.gov (United States)

Parracino, S.; Gelfusa, M.; Lungaroni, M.; Murari, A.; Peluso, E.; Ciparisse, J. F.; Malizia, A.; Rossi, R.; Ventura, P.; Gaudio, P.

2017-10-01

Considering the increase of atmospheric pollution levels in our cities, due to emissions from vehicles and domestic heating, and the growing threat of terrorism, it is necessary to develop instrumentation and gather know-how for the automatic detection and measurement of dangerous substances as quickly and far away as possible. The Multi- Wavelength DIAL, an extension of the conventional DIAL technique, is one of the most powerful remote sensing methods for the identification of multiple substances and seems to be a promising solution compared to existing alternatives. In this paper, first in-field tests of a smart and fully automated Multi-Wavelength mini-DIAL will be presented and discussed in details. The recently developed system, based on a long-wavelength infrared (IR-C) CO2 laser source, has the potential of giving an early warning, whenever something strange is found in the atmosphere, followed by identification and simultaneous concentration measurements of many chemical species, ranging from the most important Greenhouse Gases (GHG) to other harmful Volatile Organic Compounds (VOCs). Preliminary studies, regarding the fingerprint of the investigated substances, have been carried out by cross-referencing database of infrared (IR) spectra, obtained using in-cell measurements, and typical Mixing Ratios in the examined region, extrapolated from the literature. First experiments in atmosphere have been performed into a suburban and moderately-busy area of Rome. Moreover, to optimize the automatic identification of the harmful species to be recognized on the basis of in cell measurements of the absorption coefficient spectra, an advanced multivariate statistical method for classification has been developed and tested.

Automatic indexing, compiling and classification

International Nuclear Information System (INIS)

Andreewsky, Alexandre; Fluhr, Christian.

1975-06-01

A review of the principles of automatic indexing, is followed by a comparison and summing-up of work by the authors and by a Soviet staff from the Moscou INFORM-ELECTRO Institute. The mathematical and linguistic problems of the automatic building of thesaurus and automatic classification are examined [fr

A unified framework for evaluating the risk of re-identification of text de-identification tools.

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Scaiano, Martin; Middleton, Grant; Arbuckle, Luk; Kolhatkar, Varada; Peyton, Liam; Dowling, Moira; Gipson, Debbie S; El Emam, Khaled

2016-10-01

It has become regular practice to de-identify unstructured medical text for use in research using automatic methods, the goal of which is to remove patient identifying information to minimize re-identification risk. The metrics commonly used to determine if these systems are performing well do not accurately reflect the risk of a patient being re-identified. We therefore developed a framework for measuring the risk of re-identification associated with textual data releases. We apply the proposed evaluation framework to a data set from the University of Michigan Medical School. Our risk assessment results are then compared with those that would be obtained using a typical contemporary micro-average evaluation of recall in order to illustrate the difference between the proposed evaluation framework and the current baseline method. We demonstrate how this framework compares against common measures of the re-identification risk associated with an automated text de-identification process. For the probability of re-identification using our evaluation framework we obtained a mean value for direct identifiers of 0.0074 and a mean value for quasi-identifiers of 0.0022. The 95% confidence interval for these estimates were below the relevant thresholds. The threshold for direct identifier risk was based on previously used approaches in the literature. The threshold for quasi-identifiers was determined based on the context of the data release following commonly used de-identification criteria for structured data. Our framework attempts to correct for poorly distributed evaluation corpora, accounts for the data release context, and avoids the often optimistic assumptions that are made using the more traditional evaluation approach. It therefore provides a more realistic estimate of the true probability of re-identification. This framework should be used as a basis for computing re-identification risk in order to more realistically evaluate future text de-identification tools

AISLE: an automatic volumetric segmentation method for the study of lung allometry.

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Ren, Hongliang; Kazanzides, Peter

2011-01-01

We developed a fully automatic segmentation method for volumetric CT (computer tomography) datasets to support construction of a statistical atlas for the study of allometric laws of the lung. The proposed segmentation method, AISLE (Automated ITK-Snap based on Level-set), is based on the level-set implementation from an existing semi-automatic segmentation program, ITK-Snap. AISLE can segment the lung field without human interaction and provide intermediate graphical results as desired. The preliminary experimental results show that the proposed method can achieve accurate segmentation, in terms of volumetric overlap metric, by comparing with the ground-truth segmentation performed by a radiologist.

Behavioral and electrophysiological evidence for early and automatic detection of phonological equivalence in variable speech inputs.

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Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

2011-11-01

Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

Science.gov (United States)

Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

2013-01-08

Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

Automatic construction of a recurrent neural network based classifier for vehicle passage detection

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Burnaev, Evgeny; Koptelov, Ivan; Novikov, German; Khanipov, Timur

2017-03-01

Recurrent Neural Networks (RNNs) are extensively used for time-series modeling and prediction. We propose an approach for automatic construction of a binary classifier based on Long Short-Term Memory RNNs (LSTM-RNNs) for detection of a vehicle passage through a checkpoint. As an input to the classifier we use multidimensional signals of various sensors that are installed on the checkpoint. Obtained results demonstrate that the previous approach to handcrafting a classifier, consisting of a set of deterministic rules, can be successfully replaced by an automatic RNN training on an appropriately labelled data.

Automatic de-identification of textual documents in the electronic health record: a review of recent research

Directory of Open Access Journals (Sweden)

South Brett R

2010-08-01

Full Text Available Abstract Background In the United States, the Health Insurance Portability and Accountability Act (HIPAA protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. Methods This review focuses on recently published research (after 1995, and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. Results The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

Science.gov (United States)

Meystre, Stephane M; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2010-08-02

In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and

Automatic identification of epileptic seizures from EEG signals using linear programming boosting.

Science.gov (United States)

Hassan, Ahnaf Rashik; Subasi, Abdulhamit

2016-11-01

Computerized epileptic seizure detection is essential for expediting epilepsy diagnosis and research and for assisting medical professionals. Moreover, the implementation of an epilepsy monitoring device that has low power and is portable requires a reliable and successful seizure detection scheme. In this work, the problem of automated epilepsy seizure detection using singe-channel EEG signals has been addressed. At first, segments of EEG signals are decomposed using a newly proposed signal processing scheme, namely complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Six spectral moments are extracted from the CEEMDAN mode functions and train and test matrices are formed afterward. These matrices are fed into the classifier to identify epileptic seizures from EEG signal segments. In this work, we implement an ensemble learning based machine learning algorithm, namely linear programming boosting (LPBoost) to perform classification. The efficacy of spectral features in the CEEMDAN domain is validated by graphical and statistical analyses. The performance of CEEMDAN is compared to those of its predecessors to further inspect its suitability. The effectiveness and the appropriateness of LPBoost are demonstrated as opposed to the commonly used classification models. Resubstitution and 10 fold cross-validation error analyses confirm the superior algorithm performance of the proposed scheme. The algorithmic performance of our epilepsy seizure identification scheme is also evaluated against state-of-the-art works in the literature. Experimental outcomes manifest that the proposed seizure detection scheme performs better than the existing works in terms of accuracy, sensitivity, specificity, and Cohen's Kappa coefficient. It can be anticipated that owing to its use of only one channel of EEG signal, the proposed method will be suitable for device implementation, eliminate the onus of clinicians for analyzing a large bulk of data manually, and

Automatic identification of bird targets with radar via patterns produced by wing flapping

NARCIS (Netherlands)

Zaugg, S.; Saporta, G.; van Loon, E.; Schmaljohann, H.; Liechti, F.

2008-01-01

Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

Science.gov (United States)

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models

Science.gov (United States)

Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.

2014-03-01

Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.

Genetic Programming for Automatic Hydrological Modelling

Science.gov (United States)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach

Exploring the potential of machine learning for automatic slum identification from VHR imagery

NARCIS (Netherlands)

Duque, J.C.; Patino, J.E.; Betancourt, A.

2017-01-01

Slum identification in urban settlements is a crucial step in the process of formulation of pro-poor policies. However, the use of conventional methods for slum detection such as field surveys can be time-consuming and costly. This paper explores the possibility of implementing a low-cost

Automatic sets and Delone sets

International Nuclear Information System (INIS)

Barbe, A; Haeseler, F von

2004-01-01

Automatic sets D part of Z m are characterized by having a finite number of decimations. They are equivalently generated by fixed points of certain substitution systems, or by certain finite automata. As examples, two-dimensional versions of the Thue-Morse, Baum-Sweet, Rudin-Shapiro and paperfolding sequences are presented. We give a necessary and sufficient condition for an automatic set D part of Z m to be a Delone set in R m . The result is then extended to automatic sets that are defined as fixed points of certain substitutions. The morphology of automatic sets is discussed by means of examples

A survey on the automatic object tracking technology using video signals

International Nuclear Information System (INIS)

Lee, Jae Cheol; Jun, Hyeong Seop; Choi, Yu Rak; Kim, Jae Hee

2003-01-01

Recently, automatic identification and tracking of the object are actively studied according to the rapid development of signal processing and vision technology using improved hardware and software. The object tracking technology can be applied to various fields such as road watching of the vehicles, weather satellite, traffic observation, intelligent remote video-conferences and autonomous mobile robots. Object tracking system receives subsequent pictures from the camera and detects motions of the objects in these pictures. In this report, we investigate various object tracking techniques such as brightness change using histogram characteristic, differential image analysis, contour and feature extraction, and try to find proper methods that can be used to mobile robots actually

Does long-term object priming depend on the explicit detection of object identity at encoding?

Directory of Open Access Journals (Sweden)

Carlos Alexandre Gomes

2015-03-01

Full Text Available It is currently unclear whether objects have to be explicitly identified at encoding for reliable behavioural long-term object priming to occur. We conducted two experiments that investigated long-term object and non-object priming using a selective-attention encoding manipulation that reduces explicit object identification. In Experiment 1, participants either counted dots flashed within an object picture (shallow encoding or engaged in an animacy task (deep encoding at study, whereas, at test, they performed an object-decision task. Priming, as measured by reaction times, was observed for both types of encoding, and was of equivalent magnitude. In Experiment 2, non-object priming (faster reaction times for studied relative to unstudied non-objects was also obtained under the same selective-attention encoding manipulation as in Experiment 1, and the magnitude of the priming effect was equivalent between experiments. In contrast, we observed a linear decrement in recognition memory accuracy across conditions (deep encoding of Experiment 1 > shallow encoding Experiment 1 > shallow encoding of Experiment 2, suggesting that priming was not contaminated by explicit memory strategies. We argue that our results are more consistent with the identification/production framework than the perceptual/conceptual distinction, and we conclude that priming of pictures largely ignored at encoding can be subserved by the automatic retrieval of two types of instances: one at the motor-level and another at an object-decision level.

Attendance fingerprint identification system using arduino and single board computer

Science.gov (United States)

Muchtar, M. A.; Seniman; Arisandi, D.; Hasanah, S.

2018-03-01

Fingerprint is one of the most unique parts of the human body that distinguishes one person from others and is easily accessed. This uniqueness is supported by technology that can automatically identify or recognize a person called fingerprint sensor. Yet, the existing Fingerprint Sensor can only do fingerprint identification on one machine. For the mentioned reason, we need a method to be able to recognize each user in a different fingerprint sensor. The purpose of this research is to build fingerprint sensor system for fingerprint data management to be centralized so identification can be done in each Fingerprint Sensor. The result of this research shows that by using Arduino and Raspberry Pi, data processing can be centralized so that fingerprint identification can be done in each fingerprint sensor with 98.5 % success rate of centralized server recording.

COUNTERMEASURE FOR MINIMIZE UNWANTED ALARM OF AUTOMATIC FIRE NOTIFICATION SYSTEM IN THE REPUBLIC OF KOREA

Directory of Open Access Journals (Sweden)

Hasung Kong

2015-01-01

Full Text Available In this article investigated the cause of error through survey to building officials for minimizing the unwanted alarm of automatic fire notification and suggested countermeasure for minimizing the unwanted alarm. The main cause of the unwanted alarm is defective fire detector, interlocking with automatic fire detection system, lack in fire safety warden’s ability, worn-out fire detect receiving system. The countermeasure for minimizing unwanted alarm is firstly, tightening up the standard of model approval, Secondly, interlocking with cross-section circuit method fire extinguishing system or realizing automatic fire notification system interlocking with home network, thirdly, tightening up licensing examination of fire safety warden, lastly, it suggested term of use rule of fire detect receiving system.

Fuel number identification method and device therefor

International Nuclear Information System (INIS)

Doi, Takami; Seno, Makoto; Tanaka, Keiji

1998-01-01

The present invention provides a method of and a device for automatically identifying the number on the upper surface of a fuel of a fuel assembly in a PWR type reactor. Namely, the number on the upper surface of the fuel assembly of the PWR is not arranged in a row, but indent letters are dispersed to predetermined positions of the surface to be indented. Accordingly, the identification of letters is difficult. In the present invention, the letters are identified by the following procedures. Procedure (1): the letters are detected while having a corner portion of the upper surface of a fuel assembly where the number is indented as characteristic points. A procedure (2): a letter region is determined to a relative position based on the characteristic points while determining indent letters having the same direction as one group. A procedure (3): a letter identification treatment is applied to the letter images in the above-mentioned letter region to identify them. A neural network is used for the letter identification treatment. (N.H.)

Patient identification error among prostate needle core biopsy specimens--are we ready for a DNA time-out?

Science.gov (United States)

Suba, Eric J; Pfeifer, John D; Raab, Stephen S

2007-10-01

Patient identification errors in surgical pathology often involve switches of prostate or breast needle core biopsy specimens among patients. We assessed strategies for decreasing the occurrence of these uncommon and yet potentially catastrophic events. Root cause analyses were performed following 3 cases of patient identification error involving prostate needle core biopsy specimens. Patient identification errors in surgical pathology result from slips and lapses of automatic human action that may occur at numerous steps during pre-laboratory, laboratory and post-laboratory work flow processes. Patient identification errors among prostate needle biopsies may be difficult to entirely prevent through the optimization of work flow processes. A DNA time-out, whereby DNA polymorphic microsatellite analysis is used to confirm patient identification before radiation therapy or radical surgery, may eliminate patient identification errors among needle biopsies.

UHF RFID technologies for identification and traceability

CERN Document Server

Laheurte, Jean-Marc; Paret, Dominique; Loussert, Christophe

2014-01-01

UHF Radio Frequency Identification (RFID) is an electronic tagging technology that allows an object, place or person to be automatically identified at a distance without a direct line-of-sight using a radio wave exchange. Applications include inventory tracking, prescription medication tracking and authentication, secure automobile keys, and access control for secure facilities. This book begins with an overview of UHF RFID challenges describing the applications, markets, trades and basic technologies. It follows this by highlighting the main features distinguishing UHF (860MHz-960MHz) and HF

Telecommand and monitoring of automatic recloser through cell phone communication; Telecomando e monitoramento de religadoras automaticas via comunicacao celular

Energy Technology Data Exchange (ETDEWEB)

Gardiman, Vitor Luiz G.; Pires Neto, Francisco M.; Rufini, Ricardo; Marques, Rogerio [Bandeirante Energia, Sao Paulo, SP (Brazil)

2004-02-01

This article presents the system of tele command and monitoring automatic recloser of the medium voltage distribution network adopted by the Bandeirante Energia, Brazil, by using the cell phone network. The system, installed in 110 automatic reclosers, presented short term availability of tele supervision and tele control, fast installation, and operation and reliability low costs.

Rapid Automatic Motor Encoding of Competing Reach Options

Directory of Open Access Journals (Sweden)

Jason P. Gallivan

2017-02-01

Full Text Available Mounting neural evidence suggests that, in situations in which there are multiple potential targets for action, the brain prepares, in parallel, competing movements associated with these targets, prior to implementing one of them. Central to this interpretation is the idea that competing viewed targets, prior to selection, are rapidly and automatically transformed into corresponding motor representations. Here, by applying target-specific, gradual visuomotor rotations and dissociating, unbeknownst to participants, the visual direction of potential targets from the direction of the movements required to reach the same targets, we provide direct evidence for this provocative idea. Our results offer strong empirical support for theories suggesting that competing action options are automatically represented in terms of the movements required to attain them. The rapid motor encoding of potential targets may support the fast optimization of motor costs under conditions of target uncertainty and allow the motor system to inform decisions about target selection.

AUTOMATIC GLOBAL REGISTRATION BETWEEN AIRBORNE LIDAR DATA AND REMOTE SENSING IMAGE BASED ON STRAIGHT LINE FEATURES

Directory of Open Access Journals (Sweden)

Z. Q. Liu

2018-04-01

Full Text Available An automatic global registration approach for point clouds and remote sensing image based on straight line features is proposed which is insensitive to rotational and scale transformation. First, the building ridge lines and contour lines in point clouds are automatically detected as registration primitives by integrating region growth and topology identification. Second, the collinear condition equation is selected as registration transformation function which is based on rotation matrix described by unit quaternion. The similarity measure is established according to the distance between the corresponding straight line features from point clouds and the image in the same reference coordinate system. Finally, an iterative Hough transform is adopted to simultaneously estimate the parameters and obtain correspondence between registration primitives. Experimental results prove the proposed method is valid and the spectral information is useful for the following classification processing.

Application of Pattern Recognition Techniques to the Classification of Full-Term and Preterm Infant Cry.

Science.gov (United States)

Orlandi, Silvia; Reyes Garcia, Carlos Alberto; Bandini, Andrea; Donzelli, Gianpaolo; Manfredi, Claudia

2016-11-01

Scientific and clinical advances in perinatology and neonatology have enhanced the chances of survival of preterm and very low weight neonates. Infant cry analysis is a suitable noninvasive complementary tool to assess the neurologic state of infants particularly important in the case of preterm neonates. This article aims at exploiting differences between full-term and preterm infant cry with robust automatic acoustical analysis and data mining techniques. Twenty-two acoustical parameters are estimated in more than 3000 cry units from cry recordings of 28 full-term and 10 preterm newborns. Feature extraction is performed through the BioVoice dedicated software tool, developed at the Biomedical Engineering Lab, University of Firenze, Italy. Classification and pattern recognition is based on genetic algorithms for the selection of the best attributes. Training is performed comparing four classifiers: Logistic Curve, Multilayer Perceptron, Support Vector Machine, and Random Forest and three different testing options: full training set, 10-fold cross-validation, and 66% split. Results show that the best feature set is made up by 10 parameters capable to assess differences between preterm and full-term newborns with about 87% of accuracy. Best results are obtained with the Random Forest method (receiver operating characteristic area, 0.94). These 10 cry features might convey important additional information to assist the clinical specialist in the diagnosis and follow-up of possible delays or disorders in the neurologic development due to premature birth in this extremely vulnerable population of patients. The proposed approach is a first step toward an automatic infant cry recognition system for fast and proper identification of risk in preterm babies. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Computerized identification and classification of stance phases as made by front og hind feet of walking cows based on 3-dimensional ground reaction forces

DEFF Research Database (Denmark)

Skjøth, F; Thorup, Vivi Mørkøre; do Nascimento, Omar Feix

2013-01-01

Lameness is a frequent disorder in dairy cows and in large dairy herds manual lameness detection is a time-consuming task. This study describes a method for automatic identification of stance phases in walking cows, and their classification as made by a front or a hind foot based on ground reaction...... phases, of these 1146 (62%) were automatically identified as full stance phases and classified as made by a front or hind foot. As intended, the procedures did not favour identification of stance phases of healthy cows over lame cows. In addition, a human observer evaluated the stance phases by visual...... inspection, revealing a very low discrepancy (3.5%) between manual and automated approaches. Further, a sensitivity test indicated large robustness in the automatic procedures. In conclusion, the experimental setup combined with the computerized procedures described in the present study resulted in a high...

IDENTIFICATION ASPECT OF METHODOLOGY DESIGN OF CONTROL SYSTEM TIME-VARIANT PROCESS

Directory of Open Access Journals (Sweden)

M. M. Blagoveshchenskaia

2014-01-01

Full Text Available Summary. Specificity of a food manufacture demands perfection of automatic control systems of processes in devices, units and installations. Creation of an adaptive control system by technological process of a food on the basis of model of control object it is necessary to carry out the additional analysis for choice algorithm of identification on real enough to representative sample of input data and output signal/data. In article on the basis of simulation it is analyzed over 53 algorithms of recurrent identification plus the basic modifications of these algorithms by 47 criteria for time-varying multivariable linear dynamic objects. On the basis of this analysis for engineering practice for a considered class of objects some algorithms are recommended. Possibilities of the software suite having for today the fullest set of parametrical identification algorithms are discussed. For given specific conditions of comparison in the package identification algorithms for identification of stationary coefficients in the equation object of the most effective were: Yzerman-1, Kaczmarz, Nagumo-Noda, Rastrigin, Kalman filter, the forgetting factor, Zipkin. When pointwise object - Kaczmarz, Nagumo-Noda, Kalman filter; showed the best result identification algorithm-Nagumo Noda.

Efficient Identification Using a Prime-Feature-Based Technique

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar; Haq, Shaiq A.; Valente, Andrea

2011-01-01

. Fingerprint identification system, implemented on PC/104 based real-time systems, can accurately identify the operator. Traditionally, the uniqueness of a fingerprint is determined by the overall pattern of ridges and valleys as well as the local ridge anomalies e.g., a ridge bifurcation or a ridge ending......, which are called minutiae points. Designing a reliable automatic fingerprint matching algorithm for minimal platform is quite challenging. In real-time systems, efficiency of the matching algorithm is of utmost importance. To achieve this goal, a prime-feature-based indexing algorithm is proposed......Identification of authorized train drivers through biometrics is a growing area of interest in locomotive radio remote control systems. The existing technique of password authentication is not very reliable and potentially unauthorized personnel may also operate the system on behalf of the operator...

An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images.

Science.gov (United States)

Hajimani, Elmira; Ruano, M G; Ruano, A E

2017-07-01

This paper presents a Radial Basis Functions Neural Network (RBFNN) based detection system, for automatic identification of Cerebral Vascular Accidents (CVA) through analysis of Computed Tomographic (CT) images. For the design of a neural network classifier, a Multi Objective Genetic Algorithm (MOGA) framework is used to determine the architecture of the classifier, its corresponding parameters and input features by maximizing the classification precision, while ensuring generalization. This approach considers a large number of input features, comprising first and second order pixel intensity statistics, as well as symmetry/asymmetry information with respect to the ideal mid-sagittal line. Values of specificity of 98% and sensitivity of 98% were obtained, at pixel level, by an ensemble of non-dominated models generated by MOGA, in a set of 150 CT slices (1,867,602pixels), marked by a NeuroRadiologist. This approach also compares favorably at a lesion level with three other published solutions, in terms of specificity (86% compared with 84%), degree of coincidence of marked lesions (89% compared with 77%) and classification accuracy rate (96% compared with 88%). Copyright © 2017. Published by Elsevier B.V.

Radiation dosimetry by automatic image analysis of dicentric chromosomes

International Nuclear Information System (INIS)

Bayley, R.; Carothers, A.; Farrow, S.; Gordon, J.; Ji, L.; Piper, J.; Rutovitz, D.; Stark, M.; Chen, X.; Wald, N.; Pittsburgh Univ., PA

1991-01-01

A system for scoring dicentric chromosomes by image analysis comprised fully automatic location of mitotic cells, automatic retrieval, focus and digitisation at high resolution, automatic rejection of nuclei and debris and detection and segmentation of chromosome clusters, automatic centromere location, and subsequent rapid interactive visual review of potential dicentric chromosomes to confirm positives and reject false positives. A calibration set of about 15000 cells was used to establish the quadratic dose response for 60 Co γ-irradiation. The dose-response function parameters were established by a maximum likelihood technique, and confidence limits in the dose response and in the corresponding inverse curve, of estimated dose for observed dicentric frequency, were established by Monte Carlo techniques. The system was validated in a blind trial by analysing a test comprising a total of about 8000 cells irradiated to 1 of 10 dose levels, and estimating the doses from the observed dicentric frequency. There was a close correspondence between the estimated and true doses. The overall sensitivity of the system in terms of the proportion of the total population of dicentrics present in the cells analysed that were detected by the system was measured to be about 40%. This implies that about 2.5 times more cells must be analysed by machine than by visual analysis. Taking this factor into account, the measured review time and false positive rates imply that analysis by the system of sufficient cells to provide the equivalent of a visual analysis of 500 cells would require about 1 h for operator review. (author). 20 refs.; 4 figs.; 5 tabs

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection

International Nuclear Information System (INIS)

Ghose, Soumya; Mitra, Jhimli; Rivest-Hénault, David; Fazlollahi, Amir; Fripp, Jurgen; Dowling, Jason A.; Stanwell, Peter; Pichler, Peter; Sun, Jidi; Greer, Peter B.

2016-01-01

Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering “similar” gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection

Energy Technology Data Exchange (ETDEWEB)

Ghose, Soumya, E-mail: soumya.ghose@case.edu; Mitra, Jhimli [Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 and CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029 (Australia); Rivest-Hénault, David; Fazlollahi, Amir; Fripp, Jurgen; Dowling, Jason A. [CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Herston, QLD 4029 (Australia); Stanwell, Peter [School of health sciences, The University of Newcastle, Newcastle, NSW 2308 (Australia); Pichler, Peter [Department of Radiation Oncology, Cavalry Mater Newcastle Hospital, Newcastle, NSW 2298 (Australia); Sun, Jidi; Greer, Peter B. [School of Mathematical and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia and Department of Radiation Oncology, Cavalry Mater Newcastle Hospital, Newcastle, NSW 2298 (Australia)

2016-05-15

Purpose: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Methods: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering “similar” gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. Results: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). Conclusions: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold

COUNTERMEASURE FOR MINIMIZE UNWANTED ALARM OF AUTOMATIC FIRE NOTIFICATION SYSTEM IN THE REPUBLIC OF KOREA

Directory of Open Access Journals (Sweden)

Hasung Kong

2015-01-01

Full Text Available In this article investigated the cause of error through survey to building officials for minimizing the unwanted alarm of automatic fire notification and suggested countermeasure for minimizing the unwanted alarm. The main cause of the unwanted alarm is defective fire detector, interlocking with automatic fire detection system, lack in fire safety warden’s ability, worn-out fire detect receiving system. The countermeasure for minimizing unwanted alarm is firstly, tightening up the standard of model approval, Secondly, interlocking with cross-section circuit method fire extinguishing system or realizing automatic fire notification system interlocking with home network, thirdly, tightening up licensing examination of fire safety warden, lastly, it suggested term of use rule of fire detect receiving system. 

Automatic identification of otological drilling faults: an intelligent recognition algorithm.

Science.gov (United States)

Cao, Tianyang; Li, Xisheng; Gao, Zhiqiang; Feng, Guodong; Shen, Peng

2010-06-01

This article presents an intelligent recognition algorithm that can recognize milling states of the otological drill by fusing multi-sensor information. An otological drill was modified by the addition of sensors. The algorithm was designed according to features of the milling process and is composed of a characteristic curve, an adaptive filter and a rule base. The characteristic curve can weaken the impact of the unstable normal milling process and reserve the features of drilling faults. The adaptive filter is capable of suppressing interference in the characteristic curve by fusing multi-sensor information. The rule base can identify drilling faults through the filtering result data. The experiments were repeated on fresh porcine scapulas, including normal milling and two drilling faults. The algorithm has high rates of identification. This study shows that the intelligent recognition algorithm can identify drilling faults under interference conditions. (c) 2010 John Wiley & Sons, Ltd.

Automated detection of retinal landmarks for the identification of clinically relevant regions in fundus photography

Science.gov (United States)

Ometto, Giovanni; Calivá, Francesco; Al-Diri, Bashir; Bek, Toke; Hunter, Andrew

2016-03-01

Automatic, quick and reliable identification of retinal landmarks from fundus photography is key for measurements used in research, diagnosis, screening and treating of common diseases affecting the eyes. This study presents a fast method for the detection of the centre of mass of the vascular arcades, optic nerve head (ONH) and fovea, used in the definition of five clinically relevant areas in use for screening programmes for diabetic retinopathy (DR). Thirty-eight fundus photographs showing 7203 DR lesions were analysed to find the landmarks manually by two retina-experts and automatically by the proposed method. The automatic identification of the ONH and fovea were performed using template matching based on normalised cross correlation. The centre of mass of the arcades was obtained by fitting an ellipse on sample coordinates of the main vessels. The coordinates were obtained by processing the image with hessian filtering followed by shape analyses and finally sampling the results. The regions obtained manually and automatically were used to count the retinal lesions falling within, and to evaluate the method. 92.7% of the lesions were falling within the same regions based on the landmarks selected by the two experts. 91.7% and 89.0% were counted in the same areas identified by the method and the first and second expert respectively. The inter-repeatability of the proposed method and the experts is comparable, while the 100% intra-repeatability makes the algorithm a valuable tool in tasks like analyses in real-time, of large datasets and of intra-patient variability.

A novel GLM-based method for the Automatic IDentification of functional Events (AIDE) in fNIRS data recorded in naturalistic environments.

Science.gov (United States)

Pinti, Paola; Merla, Arcangelo; Aichelburg, Clarisse; Lind, Frida; Power, Sarah; Swingler, Elizabeth; Hamilton, Antonia; Gilbert, Sam; Burgess, Paul W; Tachtsidis, Ilias

2017-07-15

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that "brain-first" rather than "behaviour-first" analysis is

C-mii: a tool for plant miRNA and target identification.

Science.gov (United States)

Numnark, Somrak; Mhuantong, Wuttichai; Ingsriswang, Supawadee; Wichadakul, Duangdao

2012-01-01

MicroRNAs (miRNAs) have been known to play an important role in several biological processes in both animals and plants. Although several tools for miRNA and target identification are available, the number of tools tailored towards plants is limited, and those that are available have specific functionality, lack graphical user interfaces, and restrict the number of input sequences. Large-scale computational identifications of miRNAs and/or targets of several plants have been also reported. Their methods, however, are only described as flow diagrams, which require programming skills and the understanding of input and output of the connected programs to reproduce. To overcome these limitations and programming complexities, we proposed C-mii as a ready-made software package for both plant miRNA and target identification. C-mii was designed and implemented based on established computational steps and criteria derived from previous literature with the following distinguishing features. First, software is easy to install with all-in-one programs and packaged databases. Second, it comes with graphical user interfaces (GUIs) for ease of use. Users can identify plant miRNAs and targets via step-by-step execution, explore the detailed results from each step, filter the results according to proposed constraints in plant miRNA and target biogenesis, and export sequences and structures of interest. Third, it supplies bird's eye views of the identification results with infographics and grouping information. Fourth, in terms of functionality, it extends the standard computational steps of miRNA target identification with miRNA-target folding and GO annotation. Fifth, it provides helper functions for the update of pre-installed databases and automatic recovery. Finally, it supports multi-project and multi-thread management. C-mii constitutes the first complete software package with graphical user interfaces enabling computational identification of both plant miRNA genes and mi

SAVLOC, computer program for automatic control and analysis of X-ray fluorescence experiments

Science.gov (United States)

Leonard, R. F.

1977-01-01

A program for a PDP-15 computer is presented which provides for control and analysis of trace element determinations by using X-ray fluorescence. The program simultaneously handles data accumulation for one sample and analysis of data from previous samples. Data accumulation consists of sample changing, timing, and data storage. Analysis requires the locating of peaks in X-ray spectra, determination of intensities of peaks, identification of origins of peaks, and determination of a real density of the element responsible for each peak. The program may be run in either a manual (supervised) mode or an automatic (unsupervised) mode.

Brand and automaticity

OpenAIRE

Liu, J.

2008-01-01

A presumption of most consumer research is that consumers endeavor to maximize the utility of their choices and are in complete control of their purchasing and consumption behavior. However, everyday life experience suggests that many of our choices are not all that reasoned or conscious. Indeed, automaticity, one facet of behavior, is indispensable to complete the portrait of consumers. Despite its importance, little attention is paid to how the automatic side of behavior can be captured and...

Automatic spent fuel ID number reader (I)

International Nuclear Information System (INIS)

Tanabe, S.; Kawamoto, H.; Fujimaki, K.; Kobe, A.

1991-01-01

An effective and efficient technique has been developed for facilitating identification works of LWR spent fuel stored in large scale spent fuel storage pools of such as processing plants. Experience shows that there are often difficulties in the implementation of operator's nuclear material accountancy and control works as well as safeguards inspections conducted on spent fuel assemblies stored in deep water pool. This paper reports that the technique is realized as an automatic spent fuel ID number reader system installed on fuel handling machine. The ID number reader system consists of an optical sub-system and an image processing sub-system. Thousands of spent fuel assemblies stored in under water open racks in each storage pool could be identified within relatively short time (e.g. within several hours) by using this combination. Various performance tests were carried out on image processing sub-system in 1990 using TV images obtained from different types of spent fuel assemblies stored in various storage pools of PWR and BWR power stations

Automatic Program Development

DEFF Research Database (Denmark)

Automatic Program Development is a tribute to Robert Paige (1947-1999), our accomplished and respected colleague, and moreover our good friend, whose untimely passing was a loss to our academic and research community. We have collected the revised, updated versions of the papers published in his...... honor in the Higher-Order and Symbolic Computation Journal in the years 2003 and 2005. Among them there are two papers by Bob: (i) a retrospective view of his research lines, and (ii) a proposal for future studies in the area of the automatic program derivation. The book also includes some papers...... by members of the IFIP Working Group 2.1 of which Bob was an active member. All papers are related to some of the research interests of Bob and, in particular, to the transformational development of programs and their algorithmic derivation from formal specifications. Automatic Program Development offers...

Sleep facilitates long-term face adaptation

OpenAIRE

Ditye, Thomas; Javadi, Amir Homayoun; Carbon, Claus-Christian; Walsh, Vincent

2013-01-01

Adaptation is an automatic neural mechanism supporting the optimization of visual processing on the basis of previous experiences. While the short-term effects of adaptation on behaviour and physiology have been studied extensively, perceptual long-term changes associated with adaptation are still poorly understood. Here, we show that the integration of adaptation-dependent long-term shifts in neural function is facilitated by sleep. Perceptual shifts induced by adaptation to a distorted imag...

Term clouds as surrogates for user generated speech

NARCIS (Netherlands)

Tsagkias, M.; Larson, M.; de Rijke, M.; Myaeng, S.-H.; Oard, D.W.; Sebastiani, F.; Chua, T.-S.; Leong, M.-K.

2008-01-01

User generated spoken audio remains a challenge for Automatic Speech Recognition (ASR) technology and content-based audio surrogates derived from ASR-transcripts must be error robust. An investigation of the use of term clouds as surrogates for podcasts demonstrates that ASR term clouds closely

Development of advanced automatic operation system for nuclear ship. 1. Perfect automatic normal operation

International Nuclear Information System (INIS)

Nakazawa, Toshio; Yabuuti, Noriaki; Takahashi, Hiroki; Shimazaki, Junya

1999-02-01

Development of operation support system such as automatic operating system and anomaly diagnosis systems of nuclear reactor is very important in practical nuclear ship because of a limited number of operators and severe conditions in which receiving support from others in a case of accident is very difficult. The goal of development of the operation support systems is to realize the perfect automatic control system in a series of normal operation from the reactor start-up to the shutdown. The automatic control system for the normal operation has been developed based on operating experiences of the first Japanese nuclear ship 'Mutsu'. Automation technique was verified by 'Mutsu' plant data at manual operation. Fully automatic control of start-up and shutdown operations was achieved by setting the desired value of operation and the limiting value of parameter fluctuation, and by making the operation program of the principal equipment such as the main coolant pump and the heaters. This report presents the automatic operation system developed for the start-up and the shutdown of reactor and the verification of the system using the Nuclear Ship Engineering Simulator System. (author)

14 CFR 23.1329 - Automatic pilot system.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Automatic pilot system. 23.1329 Section 23...: Installation § 23.1329 Automatic pilot system. If an automatic pilot system is installed, it must meet the following: (a) Each system must be designed so that the automatic pilot can— (1) Be quickly and positively...

46 CFR 52.01-10 - Automatic controls.

Science.gov (United States)

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Automatic controls. 52.01-10 Section 52.01-10 Shipping... Requirements § 52.01-10 Automatic controls. (a) Each main boiler must meet the special requirements for automatic safety controls in § 62.35-20(a)(1) of this chapter. (b) Each automatically controlled auxiliary...

Personal Identification and the Assessment of the Psychophysiological State While Writing a Signature

Directory of Open Access Journals (Sweden)

Pavel Lozhnikov

2015-08-01

Full Text Available This article discusses the problem of user identification and psychophysiological state assessment while writing a signature using a graphics tablet. The solution of the problem includes the creation of templates containing handwriting signature features simultaneously with the hidden registration of physiological parameters of a person being tested. Heart rate variability description in the different time points is used as a physiological parameter. As a result, a signature template is automatically generated for psychophysiological states of an identified person. The problem of user identification and psychophysiological state assessment is solved depending on the registered value of a physiological parameter.

Fully automatic oil spill detection from COSMO-SkyMed imagery using a neural network approach

Science.gov (United States)

Avezzano, Ruggero G.; Del Frate, Fabio; Latini, Daniele

2012-09-01

The increased amount of available Synthetic Aperture Radar (SAR) images acquired over the ocean represents an extraordinary potential for improving oil spill detection activities. On the other side this involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In the framework of an ASI Announcement of Opportunity for the exploitation of COSMO-SkyMed data, a research activity (ASI contract L/020/09/0) aiming at studying the possibility to use neural networks architectures to set up fully automatic processing chains using COSMO-SkyMed imagery has been carried out and results are presented in this paper. The automatic identification of an oil spill is seen as a three step process based on segmentation, feature extraction and classification. We observed that a PCNN (Pulse Coupled Neural Network) was capable of providing a satisfactory performance in the different dark spots extraction, close to what it would be produced by manual editing. For the classification task a Multi-Layer Perceptron (MLP) Neural Network was employed.

Automatic X-ray inspection for the HTR-PM spherical fuel elements

Energy Technology Data Exchange (ETDEWEB)

Yi, DU, E-mail: duyi11@mails.tsinghua.edu.cn [Institute of Nuclear and New Energy Technology (INET), Tsinghua University, Energy Science Building A309, Haidian District, Beijing 100084 (China); Xiangang, WANG, E-mail: wangxiangang@tsinghua.edu.cn [Institute of Nuclear and New Energy Technology (INET), Tsinghua University, Energy Science Building A309, Haidian District, Beijing 100084 (China); Xincheng, XIANG, E-mail: inetxxc@tsinghua.edu.cn [Institute of Nuclear and New Energy Technology (INET), Tsinghua University, Energy Science Building, Haidian District, Beijing 100084 (China); Bing, LIU, E-mail: bingliu@tsinghua.edu.cn [Institute of Nuclear and New Energy Technology (INET), Tsinghua University, Energy Science Building, Haidian District, Beijing 100084 (China)

2014-12-15

Highlights: • An automatic X-ray inspection method is established to characterize HTR pebbles. • The method provides physical characterization and the inner structure of pebbles. • The method can be conducted non-destructively, quickly and automatically. • Sample pebbles were measured with this AXI method for validation. • The method shows the potential to be applied in situ. - Abstract: Inefficient quality assessment and control (QA and C) of spherical fuel elements for high temperature reactor-pebblebed modules (HTR-PM) has been a long-term problem, since conventional methods are labor intensive and cannot reveal the inside information nondestructively. Herein, we proposed a nondestructive, automated X-ray inspection (AXI) method to characterize spherical fuel elements including their inner structures based on X-ray digital radiography (DR). Briefly, DR images at different angles are first obtained and then the chosen important parameters such as spherical diameters, geometric and mass centers, can be automatically extracted and calculated via image processing techniques. Via evaluating sample spherical fuel elements, we proved that this AXI method can be conducted non-destructively, quickly and automatically. This method not only provides accurate physical characterization of spherical fuel elements but also reveals their inner structure with good resolution, showing great potentials to facilitate fast QA and C in HTM-PM spherical fuel element development and production.

Automatic X-ray inspection for the HTR-PM spherical fuel elements

International Nuclear Information System (INIS)

Yi, DU; Xiangang, WANG; Xincheng, XIANG; Bing, LIU

2014-01-01

Highlights: • An automatic X-ray inspection method is established to characterize HTR pebbles. • The method provides physical characterization and the inner structure of pebbles. • The method can be conducted non-destructively, quickly and automatically. • Sample pebbles were measured with this AXI method for validation. • The method shows the potential to be applied in situ. - Abstract: Inefficient quality assessment and control (QA and C) of spherical fuel elements for high temperature reactor-pebblebed modules (HTR-PM) has been a long-term problem, since conventional methods are labor intensive and cannot reveal the inside information nondestructively. Herein, we proposed a nondestructive, automated X-ray inspection (AXI) method to characterize spherical fuel elements including their inner structures based on X-ray digital radiography (DR). Briefly, DR images at different angles are first obtained and then the chosen important parameters such as spherical diameters, geometric and mass centers, can be automatically extracted and calculated via image processing techniques. Via evaluating sample spherical fuel elements, we proved that this AXI method can be conducted non-destructively, quickly and automatically. This method not only provides accurate physical characterization of spherical fuel elements but also reveals their inner structure with good resolution, showing great potentials to facilitate fast QA and C in HTM-PM spherical fuel element development and production

Automatic measurement of axial length of human eye using three-dimensional magnetic resonance imaging

International Nuclear Information System (INIS)

Watanabe, Masaki; Kiryu, Tohru

2011-01-01

The measurement of axial length and the evaluation of three dimensional (3D) form of an eye are essential to evaluate the mechanism of myopia progression. We propose a method of automatic measurement of axial length including adjustment of the pulse sequence of short-term scan which could suppress influence of eyeblink, using a magnetic resonance imaging (MRI) which acquires 3D images noninvasively. Acquiring T 2 -weighted images with 3.0 tesla MRI device and eight-channel phased-array head coil, we extracted left and right eye ball images, and then reconstructed 3D volume. The surface coordinates were calculated from 3D volume, fitting the ellipsoid model coordinates with the surface coordinates, and measured the axial length automatically. Measuring twenty one subjects, we compared the automatically measured values of axial length with the manually measured ones, then confirmed significant elongation in the axial length of myopia compared with that of emmetropia. Furthermore, there were no significant differences (P<0.05) between the means of automatic measurements and the manual ones. Accordingly, the automatic measurement process of axial length could be a tool for the elucidation of the mechanism of myopia progression, which would be suitable for evaluating the axial length easily and noninvasively. (author)

ERPs reveal deficits in automatic cerebral stimulus processing in patients with NIDDM.

Science.gov (United States)

Vanhanen, M; Karhu, J; Koivisto, K; Pääkkönen, A; Partanen, J; Laakso, M; Riekkinen, P

1996-11-04

We compared auditory event-related potentials (ERPs) and neuropsychological test scores in nine patients with non-insulin-dependent diabetes mellitus (NIDDM) and in nine control subjects. The measures of automatic stimulus processing, habituation of auditory N100 and mismatch negativity (MMN) were impaired in patients. No differences were observed in the N2b and P3 components, which presumably reflect conscious cognitive analysis of the stimuli. A trend towards impaired performance in the Digit Span backward was found in diabetic subjects, but in the tests of secondary or long-term memory the groups were comparable. Patients with NIDDM may have defects in arousal and in the automatic ability to redirect attention, which can affect their cognitive performance.

Beef identification in industrial slaughterhouses using machine vision techniques

Directory of Open Access Journals (Sweden)

J. F. Velez

2013-10-01

Full Text Available Accurate individual animal identification provides the producers with useful information to take management decisions about an individual animal or about the complete herd. This identification task is also important to ensure the integrity of the food chain. Consequently, many consumers are turning their attention to issues of quality in animal food production methods. This work describes an implemented solution for individual beef identification, taking in the time from cattle shipment arrival at the slaughterhouse until the animals are slaughtered and cut up. Our beef identification approach is image-based and the pursued goals are the correct automatic extraction and matching between some numeric information extracted from the beef ear-tag and the corresponding one from the Bovine Identification Document (BID. The achieved correct identification results by our method are near 90%, by considering the practical working conditions of slaughterhouses (i.e. problems with dirt and bad illumination conditions. Moreover, the presence of multiple machinery in industrial slaughterhouses make it difficult the use of Radio Frequency Identification (RFID beef tags due to the high risks of interferences between RFID and the other technologies in the workplace. The solution presented is hardware/software since it includes a specialized hardware system that was also developed. Our approach considers the current EU legislation for beef traceability and it reduces the economic cost of individual beef identification with respect to RFID transponders. The system implemented has been in use satisfactorily for more than three years in one of the largest industrial slaughterhouses in Spain.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

Science.gov (United States)

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Rapid identification of microorganisms from positive blood cultures by MALDI-TOF mass spectrometry subsequent to very short-term incubation on solid medium.

Science.gov (United States)

Idelevich, E A; Schüle, I; Grünastel, B; Wüllenweber, J; Peters, G; Becker, K

2014-10-01

Rapid identification of the causative microorganism is important for appropriate antimicrobial therapy of bloodstream infections. Bacteria from positive blood culture (BC) bottles are not readily available for identification by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Lysis and centrifugation procedures suggested for direct MALDI-TOF MS from positive BCs without previous culture are associated with additional hands-on processing time and costs. Here, we describe an alternative approach applying MALDI-TOF MS from bacterial cultures incubated very briefly on solid medium. After plating of positive BC broth on Columbia blood agar (n = 165), MALDI-TOF MS was performed after 1.5, 2, 3, 4, 5, 6, 7, 8, 12 and (for control) 24 h of incubation until reliable identification to the species level was achieved (score ≥2.0). Mean incubation time needed to achieve species-level identification was 5.9 and 2.0 h for Gram-positive aerobic cocci (GPC, n = 86) and Gram-negative aerobic rods (GNR, n = 42), respectively. Short agar cultures with incubation times ≤2, ≤4, ≤6, ≤8 and ≤12 h yielded species identification in 1.2%, 18.6%, 64.0%, 96.5%, 98.8% of GPC, and in 76.2%, 95.2%, 97.6%, 97.6%, 97.6% of GNR, respectively. Control species identification at 24 h was achieved in 100% of GPC and 97.6% of GNR. Ethanol/formic acid protein extraction performed for an additional 34 GPC isolates cultivated from positive BCs showed further reduction in time to species identification (3.1 h). MALDI-TOF MS using biomass subsequent to very short-term incubation on solid medium allows very early and reliable bacterial identification from positive BCs without additional time and cost expenditure. © 2014 The Authors Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

Computational botany methods for automated species identification

CERN Document Server

Remagnino, Paolo; Wilkin, Paul; Cope, James; Kirkup, Don

2017-01-01

This book discusses innovative methods for mining information from images of plants, especially leaves, and highlights the diagnostic features that can be implemented in fully automatic systems for identifying plant species. Adopting a multidisciplinary approach, it explores the problem of plant species identification, covering both the concepts of taxonomy and morphology. It then provides an overview of morphometrics, including the historical background and the main steps in the morphometric analysis of leaves together with a number of applications. The core of the book focuses on novel diagnostic methods for plant species identification developed from a computer scientist’s perspective. It then concludes with a chapter on the characterization of botanists' visions, which highlights important cognitive aspects that can be implemented in a computer system to more accurately replicate the human expert’s fixation process. The book not only represents an authoritative guide to advanced computational tools fo...

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Science.gov (United States)

Zheng, Jiaping; Yu, Hong

2016-01-01

identification, the performance of FOCUS for identifying important terms from EHR notes was 0.866 AUC-ROC. Both performance scores significantly exceeded the corresponding baseline system scores (P<.001). Rich learning features contributed to FOCUS’s performance substantially. Conclusions FOCUS can automatically rank terms from EHR notes based on their importance to patients. It may help develop future interventions that improve quality of care. PMID:27903489

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

International Nuclear Information System (INIS)

Qiu, J; Yang, D

2015-01-01

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

Energy Technology Data Exchange (ETDEWEB)

Qiu, J [Washington University in St Louis, Taian, Shandong (China); Yang, D [Washington University School of Medicine, St Louis, MO (United States)

2015-06-15

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from

Combining Multiple Features for Text-Independent Writer Identification and Verification

OpenAIRE

Bulacu , Marius; Schomaker , Lambert

2006-01-01

http://www.suvisoft.com; In recent years, we proposed a number of new and very effective features for automatic writer identification and verification. They are probability distribution functions (PDFs) extracted from the handwriting images and characterize writer individuality independently of the textual content of the written samples. In this paper, we perform an extensive analysis of feature combinations. In our fusion scheme, the final unique distance between two handwritten samples is c...

Automatic differentiation of functions

International Nuclear Information System (INIS)

Douglas, S.R.

1990-06-01

Automatic differentiation is a method of computing derivatives of functions to any order in any number of variables. The functions must be expressible as combinations of elementary functions. When evaluated at specific numerical points, the derivatives have no truncation error and are automatically found. The method is illustrated by simple examples. Source code in FORTRAN is provided

A Method of Fire Scenarios Identification in a Consolidated Fire Risk Analysis

International Nuclear Information System (INIS)

Lim, Ho Gon; Han, Sang Hoon; Yang, Joon Eon

2010-01-01

Conventional fire PSA consider only two cases of fire scenarios, that is one for fire without propagation and the other for single propagation to neighboring compartment. Recently, a consolidated fire risk analysis using single fault tree (FT) was developed. However, the fire scenario identification in the new method is similar to conventional fire analysis method. The present study develops a new method of fire scenario identification in a consolidated fire risk analysis method. An equation for fire propagation is developed to identify fire scenario and a mapping method of fire scenarios into internal event risk model is discussed. Finally, an algorithm for automatic program is suggested

Exploration of Uninitialized Configuration Memory Space for Intrinsic Identification of Xilinx Virtex-5 FPGA Devices

Directory of Open Access Journals (Sweden)

Oliver Sander

2012-01-01

Full Text Available SRAM-based fingerprinting uses deviations in power-up behaviour caused by the CMOS fabrication process to identify distinct devices. This method is a promising technique for unique identification of physical devices. In the case of SRAM-based hardware reconfigurable devices such as FPGAs, the integrated SRAM cells are often initialized automatically at power-up, sweeping potential identification data. We demonstrate an approach to utilize unused parts of configuration memory space for device identification. Based on a total of over 200,000 measurements on nine Xilinx Virtex-5 FPGAs, we show that the retrieved values have promising properties with respect to consistency on one device, variety between different devices, and stability considering temperature variation and aging.

Impact of the accuracy of automatic tumour functional volume delineation on radiotherapy treatment planning

International Nuclear Information System (INIS)

Le Maitre, Amandine; Hatt, Mathieu; Pradier, Olivier; Cheze-le Rest, Catherine; Visvikis, Dimitris

2012-01-01

Over the past few years several automatic and semi-automatic PET segmentation methods for target volume definition in radiotherapy have been proposed. The objective of this study is to compare different methods in terms of dosimetry. For such a comparison, a gold standard is needed. For this purpose, realistic GATE-simulated PET images were used. Three lung cases and three H and N cases were designed with various shapes, contrasts and heterogeneities. Four different segmentation approaches were compared: fixed and adaptive thresholds, a fuzzy C-mean and the fuzzy locally adaptive Bayesian method. For each of these target volumes, an IMRT treatment plan was defined. The different algorithms and resulting plans were compared in terms of segmentation errors and ground-truth volume coverage using different metrics (V 95 , D 95 , homogeneity index and conformity index). The major differences between the threshold-based methods and automatic methods occurred in the most heterogeneous cases. Within the two groups, the major differences occurred for low contrast cases. For homogeneous cases, equivalent ground-truth volume coverage was observed for all methods but for more heterogeneous cases, significantly lower coverage was observed for threshold-based methods. Our study demonstrates that significant dosimetry errors can be avoided by using more advanced image-segmentation methods. (paper)

Automatic health record review to help prioritize gravely ill Social Security disability applicants.

Science.gov (United States)

Abbott, Kenneth; Ho, Yen-Yi; Erickson, Jennifer

2017-07-01

Every year, thousands of patients die waiting for disability benefits from the Social Security Administration. Some qualify for expedited service under the Compassionate Allowance (CAL) initiative, but CAL software focuses exclusively on information from a single form field. This paper describes the development of a supplemental process for identifying some overlooked but gravely ill applicants, through automatic annotation of health records accompanying new claims. We explore improved prioritization instead of fully autonomous claims approval. We developed a sample of claims containing medical records at the moment of arrival in a single office. A series of tools annotated both patient records and public Web page descriptions of CAL medical conditions. We trained random forests to identify CAL patients and validated each model with 10-fold cross validation. Our main model, a general CAL classifier, had an area under the receiver operating characteristic curve of 0.915. Combining this classifier with existing software improved sensitivity from 0.960 to 0.994, detecting every deceased patient, but reducing positive predictive value to 0.216. True positive CAL identification is a priority, given CAL patient mortality. Mere prioritization of the false positives would not create a meaningful burden in terms of manual review. Death certificate data suggest the presence of truly ill patients among putative false positives. To a limited extent, it is possible to identify gravely ill Social Security disability applicants by analyzing annotations of unstructured electronic health records, and the level of identification is sufficient to be useful in prioritizing case reviews. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.

Automatic Classification of the Sub-Techniques (Gears Used in Cross-Country Ski Skating Employing a Mobile Phone

Directory of Open Access Journals (Sweden)

Thomas Stöggl

2014-10-01

Full Text Available The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC ski-skating gears (G using Smartphone accelerometer data. Eleven XC skiers (seven men, four women with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 ± 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% ± 8.9% of the time, a value that rose to 90.3% ± 4.1% (P < 0.01 with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear.

Automatic Classification of the Sub-Techniques (Gears) Used in Cross-Country Ski Skating Employing a Mobile Phone

Science.gov (United States)

Stöggl, Thomas; Holst, Anders; Jonasson, Arndt; Andersson, Erik; Wunsch, Tobias; Norström, Christer; Holmberg, Hans-Christer

2014-01-01

The purpose of the current study was to develop and validate an automatic algorithm for classification of cross-country (XC) ski-skating gears (G) using Smartphone accelerometer data. Eleven XC skiers (seven men, four women) with regional-to-international levels of performance carried out roller skiing trials on a treadmill using fixed gears (G2left, G2right, G3, G4left, G4right) and a 950-m trial using different speeds and inclines, applying gears and sides as they normally would. Gear classification by the Smartphone (on the chest) and based on video recordings were compared. Formachine-learning, a collective database was compared to individual data. The Smartphone application identified the trials with fixed gears correctly in all cases. In the 950-m trial, participants executed 140 ± 22 cycles as assessed by video analysis, with the automatic Smartphone application giving a similar value. Based on collective data, gears were identified correctly 86.0% ± 8.9% of the time, a value that rose to 90.3% ± 4.1% (P < 0.01) with machine learning from individual data. Classification was most often incorrect during transition between gears, especially to or from G3. Identification was most often correct for skiers who made relatively few transitions between gears. The accuracy of the automatic procedure for identifying G2left, G2right, G3, G4left and G4right was 96%, 90%, 81%, 88% and 94%, respectively. The algorithm identified gears correctly 100% of the time when a single gear was used and 90% of the time when different gears were employed during a variable protocol. This algorithm could be improved with respect to identification of transitions between gears or the side employed within a given gear. PMID:25365459

Solar Powered Automatic Shrimp Feeding System

Directory of Open Access Journals (Sweden)

Dindo T. Ani

2015-12-01

Full Text Available - Automatic system has brought many revolutions in the existing technologies. One among the technologies, which has greater developments, is the solar powered automatic shrimp feeding system. For instance, the solar power which is a renewable energy can be an alternative solution to energy crisis and basically reducing man power by using it in an automatic manner. The researchers believe an automatic shrimp feeding system may help solve problems on manual feeding operations. The project study aimed to design and develop a solar powered automatic shrimp feeding system. It specifically sought to prepare the design specifications of the project, to determine the methods of fabrication and assembly, and to test the response time of the automatic shrimp feeding system. The researchers designed and developed an automatic system which utilizes a 10 hour timer to be set in intervals preferred by the user and will undergo a continuous process. The magnetic contactor acts as a switch connected to the 10 hour timer which controls the activation or termination of electrical loads and powered by means of a solar panel outputting electrical power, and a rechargeable battery in electrical communication with the solar panel for storing the power. By undergoing through series of testing, the components of the modified system were proven functional and were operating within the desired output. It was recommended that the timer to be used should be tested to avoid malfunction and achieve the fully automatic system and that the system may be improved to handle changes in scope of the project.

Automatic methods for long-term tracking and the detection and decoding of communication dances in honeybees

Directory of Open Access Journals (Sweden)

Fernando eWario

2015-09-01

Full Text Available The honeybee waggle dance communication system is an intriguing example of abstract animal communication and has been investigated thoroughly throughout the last seven decades. Typically, observables such as durations or angles are extracted manually directly from the observation hive or from video recordings to quantify dance properties, particularly to determine where bees have foraged. In recent years, biology has profited from automation, improving measurement precision, removing human bias, and accelerating data collection. As a further step, we have developed technologies to track all individuals of a honeybee colony and detect and decode communication dances automatically. In strong contrast to conventional approaches that focus on a small subset of the hive life, whether this regards time, space, or animal identity, our more inclusive system will help the understanding of the dance comprehensively in its spatial, temporal, and social context. In this contribution, we present full specifications of the recording setup and the software for automatic recognition and decoding of tags and dances, and we discuss potential research directions that may benefit from automation. Lastly, to exemplify the power of the methodology, we show experimental data and respective analyses for a continuous, experimental recording of nine weeks duration.

Team reasoning and group identification

NARCIS (Netherlands)

Hindriks, Frank

The team reasoning approach explains cooperation in terms of group identification, which in turn is explicated in terms of agency transformation and payoff transformation. Empirical research in social psychology is consistent with the significance of agency and payoff transformation. However, it

Optimum Identification Method of Sorting Green Household Waste

Directory of Open Access Journals (Sweden)

Daud Mohd Hisam

2016-01-01

Full Text Available This project is related to design of sorting facility for reducing, reusing, recycling green waste material, and in particular to invent an automatic system to distinguish household waste in order to separate them from the main waste stream. The project focuses on thorough analysis of the properties of green household waste. The method of identification is using capacitive sensor where the characteristic data taken on three different sensor drive frequency. Three types of material have been chosen as a medium of this research, to be separated using the selected method. Based on capacitance characteristics and its ability to penetrate green object, optimum identification method is expected to be recognized in this project. The output capacitance sensor is in analogue value. The results demonstrate that the information from the sensor is enough to recognize the materials that have been selected.

High-speed holographic correlation system for video identification on the internet

Science.gov (United States)

Watanabe, Eriko; Ikeda, Kanami; Kodate, Kashiko

2013-12-01

Automatic video identification is important for indexing, search purposes, and removing illegal material on the Internet. By combining a high-speed correlation engine and web-scanning technology, we developed the Fast Recognition Correlation system (FReCs), a video identification system for the Internet. FReCs is an application thatsearches through a number of websites with user-generated content (UGC) and detects video content that violates copyright law. In this paper, we describe the FReCs configuration and an approach to investigating UGC websites using FReCs. The paper also illustrates the combination of FReCs with an optical correlation system, which is capable of easily replacing a digital authorization sever in FReCs with optical correlation.

An automatic system to study sperm motility and energetics

OpenAIRE

Shi, LZ; Nascimento, JM; Chandsawangbhuwana, C; Botvinick, EL; Berns, MW

2008-01-01

An integrated robotic laser and microscope system has been developed to automatically analyze individual sperm motility and energetics. The custom-designed optical system directs near-infrared laser light into an inverted microscope to create a single-point 3-D gradient laser trap at the focal spot of the microscope objective. A two-level computer structure is described that quantifies the sperm motility (in terms of swimming speed and swimming force) and energetics (measuring mid-piece membr...

Long-term clinical evaluation of the automatic stance-phase lock-controlled prosthetic knee joint in young adults with unilateral above-knee amputation.

Science.gov (United States)

Andrysek, Jan; Wright, F Virginia; Rotter, Karin; Garcia, Daniela; Valdebenito, Rebeca; Mitchell, Carlos Alvarez; Rozbaczylo, Claudio; Cubillos, Rafael

2017-05-01

The purpose of this study was to clinically evaluate the automatic stance-phase lock (ASPL) knee mechanism against participants' existing weight-activated braking (WAB) prosthetic knee joint. This prospective crossover study involved 10 young adults with an above-knee amputation. Primary measurements consisted of tests of walking speeds and capacity. Heart rate was measured during the six-minute walk test and the Physiological Cost Index (PCI) which was calculated from heart rate estimated energy expenditure. Activity was measured with a pedometer. User function and quality of life were assessed using the Lower Limb Function Questionnaire (LLFQ) and Prosthetic Evaluation Questionnaire (PEQ). Long-term follow-up over 12 months were completed. Walking speeds were the same for WAB and APSL knees. Energy expenditure (PCI) was lower for the ASPL knees (p = 0.007). Step counts were the same for both knees, and questionnaires indicated ASPL knee preference attributed primarily to knee stability and improved walking, while limitations included terminal impact noise. Nine of 10 participants chose to keep using the ASPL knee as part of the long-term follow-up. Potential benefits of the ASPL knee were identified in this study by functional measures, questionnaires and user feedback, but not changes in activity or the PEQ.

Long-term memory for odors: influences of familiarity and identification across 64 days.

Science.gov (United States)

Cornell Kärnekull, Stina; Jönsson, Fredrik U; Willander, Johan; Sikström, Sverker; Larsson, Maria

2015-05-01

Few studies have investigated long-term odor recognition memory, although some early observations suggested that the forgetting rate of olfactory representations is slower than for other sensory modalities. This study investigated recognition memory across 64 days for high and low familiar odors and faces. Memory was assessed in 83 young participants at 4 occasions; immediate, 4, 16, and 64 days after encoding. The results indicated significant forgetting for odors and faces across the 64 days. The forgetting functions for the 2 modalities were not fundamentally different. Moreover, high familiar odors and faces were better remembered than low familiar ones, indicating an important role of semantic knowledge on recognition proficiency for both modalities. Although odor recognition was significantly better than chance at the 64 days testing, memory for the low familiar odors was relatively poor. Also, the results indicated that odor identification consistency across sessions, irrespective of accuracy, was positively related to successful recognition. © The Author 2015. Published by Oxford University Press.

Automatic/Control Processing Concepts and Their Implications for the Training of Skills.

Science.gov (United States)

1982-04-01

driving a car are examples of automatic processes. Controll p s is comparatively slow, serial, limited by short-term memory, and requires subject effort...development has convinced us that moivation a oftn more Jmportn nti mAn =other iJli velLJoa jjthpgy gI. njj Lautomatic U_2,LLjjk. Motivation Is much more

Automatic address validation and health record review to identify homeless Social Security disability applicants.

Science.gov (United States)

Erickson, Jennifer; Abbott, Kenneth; Susienka, Lucinda

2018-06-01

Homeless patients face a variety of obstacles in pursuit of basic social services. Acknowledging this, the Social Security Administration directs employees to prioritize homeless patients and handle their disability claims with special care. However, under existing manual processes for identification of homelessness, many homeless patients never receive the special service to which they are entitled. In this paper, we explore address validation and automatic annotation of electronic health records to improve identification of homeless patients. We developed a sample of claims containing medical records at the moment of arrival in a single office. Using address validation software, we reconciled patient addresses with public directories of homeless shelters, veterans' hospitals and clinics, and correctional facilities. Other tools annotated electronic health records. We trained random forests to identify homeless patients and validated each model with 10-fold cross validation. For our finished model, the area under the receiver operating characteristic curve was 0.942. The random forest improved sensitivity from 0.067 to 0.879 but decreased positive predictive value to 0.382. Presumed false positive classifications bore many characteristics of homelessness. Organizations could use these methods to prompt early collection of information necessary to avoid labor-intensive attempts to reestablish contact with homeless individuals. Annually, such methods could benefit tens of thousands of patients who are homeless, destitute, and in urgent need of assistance. We were able to identify many more homeless patients through a combination of automatic address validation and natural language processing of unstructured electronic health records. Copyright © 2018. Published by Elsevier Inc.

Digital Modulation Identification Model Using Wavelet Transform and Statistical Parameters

Directory of Open Access Journals (Sweden)

P. Prakasam

2008-01-01

Full Text Available A generalized modulation identification scheme is developed and presented. With the help of this scheme, the automatic modulation classification and recognition of wireless communication signals with a priori unknown parameters are possible effectively. The special features of the procedure are the possibility to adapt it dynamically to nearly all modulation types, and the capability to identify. The developed scheme based on wavelet transform and statistical parameters has been used to identify M-ary PSK, M-ary QAM, GMSK, and M-ary FSK modulations. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB. The identification percentage has been analyzed based on the confusion matrix. When SNR is above 5 dB, the probability of detection of the proposed system is more than 0.968. The performance of the proposed scheme has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.

Go with the flow: how the consideration of joy versus pride influences automaticity.

Science.gov (United States)

Katzir, Maayan; Ori, Bnaya; Eyal, Tal; Meiran, Nachshon

2015-02-01

Recently, we have shown that the consideration of joy, without the actual experience of the emotion, impaired performance on the antisaccade task (Katzir, Eyal, Meiran, & Kessler, 2010). We interpreted this finding as indicating inhibitory control failure. However, impaired antisaccade performance may result from either the weakening of inhibitory control, the potentiation of the competing automatic response, or both. In the current research we used a task switching paradigm, which allowed us to assess cognitive control more directly, using Backward Inhibition, Competitor Rule Suppression, and Competitor Rule Priming as cognitive-control indices as well as assessing the Task Rule Congruency Effect (TRCE) which, like the antisaccade, is influenced by both control and automaticity. We found that considering joy compared to pride did not influence any of the cognitive control indices but increased the TRCE. We interpret this finding as evidence that joy consideration leads to increased reliance on automatic tendencies, such as short-term desires. Copyright © 2014 Elsevier B.V. All rights reserved.

Automatic text summarization

CERN Document Server

Torres Moreno, Juan Manuel

2014-01-01

This new textbook examines the motivations and the different algorithms for automatic document summarization (ADS). We performed a recent state of the art. The book shows the main problems of ADS, difficulties and the solutions provided by the community. It presents recent advances in ADS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several exemples are included in order to clarify the theoretical concepts.  The books currently available in the area of Automatic Document Summarization are not recent. Powerful algorithms have been develop

Automatic Ultrasound Scanning

DEFF Research Database (Denmark)

Moshavegh, Ramin

on the user adjustments on the scanner interface to optimize the scan settings. This explains the huge interest in the subject of this PhD project entitled “AUTOMATIC ULTRASOUND SCANNING”. The key goals of the project have been to develop automated techniques to minimize the unnecessary settings...... on the scanners, and to improve the computer-aided diagnosis (CAD) in ultrasound by introducing new quantitative measures. Thus, four major issues concerning automation of the medical ultrasound are addressed in this PhD project. They touch upon gain adjustments in ultrasound, automatic synthetic aperture image...

Automatic classification of blank substrate defects

Science.gov (United States)

Boettiger, Tom; Buck, Peter; Paninjath, Sankaranarayanan; Pereira, Mark; Ronald, Rob; Rost, Dan; Samir, Bhamidipati

2014-10-01

Mask preparation stages are crucial in mask manufacturing, since this mask is to later act as a template for considerable number of dies on wafer. Defects on the initial blank substrate, and subsequent cleaned and coated substrates, can have a profound impact on the usability of the finished mask. This emphasizes the need for early and accurate identification of blank substrate defects and the risk they pose to the patterned reticle. While Automatic Defect Classification (ADC) is a well-developed technology for inspection and analysis of defects on patterned wafers and masks in the semiconductors industry, ADC for mask blanks is still in the early stages of adoption and development. Calibre ADC is a powerful analysis tool for fast, accurate, consistent and automatic classification of defects on mask blanks. Accurate, automated classification of mask blanks leads to better usability of blanks by enabling defect avoidance technologies during mask writing. Detailed information on blank defects can help to select appropriate job-decks to be written on the mask by defect avoidance tools [1][4][5]. Smart algorithms separate critical defects from the potentially large number of non-critical defects or false defects detected at various stages during mask blank preparation. Mechanisms used by Calibre ADC to identify and characterize defects include defect location and size, signal polarity (dark, bright) in both transmitted and reflected review images, distinguishing defect signals from background noise in defect images. The Calibre ADC engine then uses a decision tree to translate this information into a defect classification code. Using this automated process improves classification accuracy, repeatability and speed, while avoiding the subjectivity of human judgment compared to the alternative of manual defect classification by trained personnel [2]. This paper focuses on the results from the evaluation of Automatic Defect Classification (ADC) product at MP Mask

Study on the man-operator characteristics in the peak identification problem in line spectra

International Nuclear Information System (INIS)

Gopych, P.M.; Sorokin, V.I.; Sotnikov, V.V.

1992-01-01

ATOS program complex (automatical test spectra processing) realizing all stages of investigation necessary to obtain qualitative characteristics of the man-operator in the peak identification problem is developed. Qualitative characteristics of identitication ion quality of peaks by operators searching for peaks in line spectra are determined due to simulation experiment. It is shown, that for trained operators reference possibility of false detection of peaks is equal to F=0.012±0.004, while for untrained ones - F≅0.3. Comparison of results with analogous data on on-line programs for identification of peaks in γ-spectra is conducted

Identification of suicidal tendencies in individuals using a quantitative analysis of their speech production

Directory of Open Access Journals (Sweden)

Zagorovskaya Olga Vladimirovna

2016-04-01

Full Text Available Suicide is one of the top factors contributing to deaths around the globe with individuals not making other people aware of their suicidal plans. Therefore it is of increasing importance to develop the methods of identification of these individuals. One of the directions of the ongoing research is identification of typological features of their speech patterns using the methods of mathematical linguistics and automatic text processing. Most studies addressing the problem use materials written in English. The article presents the analysis of the above studies and points out the ways of dealing with the issue employing materials written in Russian.

An inverse method for non linear ablative thermics with experimentation of automatic differentiation

Energy Technology Data Exchange (ETDEWEB)

Alestra, S [Simulation Information Technology and Systems Engineering, EADS IW Toulouse (France); Collinet, J [Re-entry Systems and Technologies, EADS ASTRIUM ST, Les Mureaux (France); Dubois, F [Professor of Applied Mathematics, Conservatoire National des Arts et Metiers Paris (France)], E-mail: stephane.alestra@eads.net, E-mail: jean.collinet@astrium.eads.net, E-mail: fdubois@cnam.fr

2008-11-01

Thermal Protection System is a key element for atmospheric re-entry missions of aerospace vehicles. The high level of heat fluxes encountered in such missions has a direct effect on mass balance of the heat shield. Consequently, the identification of heat fluxes is of great industrial interest but is in flight only available by indirect methods based on temperature measurements. This paper is concerned with inverse analyses of highly evolutive heat fluxes. An inverse problem is used to estimate transient surface heat fluxes (convection coefficient), for degradable thermal material (ablation and pyrolysis), by using time domain temperature measurements on thermal protection. The inverse problem is formulated as a minimization problem involving an objective functional, through an optimization loop. An optimal control formulation (Lagrangian, adjoint and gradient steepest descent method combined with quasi-Newton method computations) is then developed and applied, using Monopyro, a transient one-dimensional thermal model with one moving boundary (ablative surface) that has been developed since many years by ASTRIUM-ST. To compute numerically the adjoint and gradient quantities, for the inverse problem in heat convection coefficient, we have used both an analytical manual differentiation and an Automatic Differentiation (AD) engine tool, Tapenade, developed at INRIA Sophia-Antipolis by the TROPICS team. Several validation test cases, using synthetic temperature measurements are carried out, by applying the results of the inverse method with minimization algorithm. Accurate results of identification on high fluxes test cases, and good agreement for temperatures restitutions, are obtained, without and with ablation and pyrolysis, using bad fluxes initial guesses. First encouraging results with an automatic differentiation procedure are also presented in this paper.

30 CFR 77.314 - Automatic temperature control instruments.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic temperature control instruments. 77... UNDERGROUND COAL MINES Thermal Dryers § 77.314 Automatic temperature control instruments. (a) Automatic temperature control instruments for thermal dryer system shall be of the recording type. (b) Automatic...

Identification of granite varieties from colour spectrum data.

Science.gov (United States)

Araújo, María; Martínez, Javier; Ordóñez, Celestino; Vilán, José Antonio

2010-01-01

The granite processing sector of the northwest of Spain handles many varieties of granite with specific technical and aesthetic properties that command different prices in the natural stone market. Hence, correct granite identification and classification from the outset of processing to the end-product stage optimizes the management and control of stocks of granite slabs and tiles and facilitates the operation of traceability systems. We describe a methodology for automatically identifying granite varieties by processing spectral information captured by a spectrophotometer at various stages of processing using functional machine learning techniques.

Automatic control systems engineering

International Nuclear Information System (INIS)

Shin, Yun Gi

2004-01-01

This book gives descriptions of automatic control for electrical electronics, which indicates history of automatic control, Laplace transform, block diagram and signal flow diagram, electrometer, linearization of system, space of situation, state space analysis of electric system, sensor, hydro controlling system, stability, time response of linear dynamic system, conception of root locus, procedure to draw root locus, frequency response, and design of control system.

Automatic pattern identification of rock moisture based on the Staff-RF model

Science.gov (United States)

Zheng, Wei; Tao, Kai; Jiang, Wei

2018-04-01

Studies on the moisture and damage state of rocks generally focus on the qualitative description and mechanical information of rocks. This method is not applicable to the real-time safety monitoring of rock mass. In this study, a musical staff computing model is used to quantify the acoustic emission signals of rocks with different moisture patterns. Then, the random forest (RF) method is adopted to form the staff-RF model for the real-time pattern identification of rock moisture. The entire process requires only the computing information of the AE signal and does not require the mechanical conditions of rocks.

Workflow-centred evaluation of an automatic lesion tracking software for chemotherapy monitoring by CT

Energy Technology Data Exchange (ETDEWEB)

Moltz, Jan Hendrik; Peitgen, Heinz-Otto [Fraunhofer MEVIS - Institute for Medical Image Computing, Bremen (Germany); D' Anastasi, Melvin [University Hospital Munich-Grosshadern, Department of Clinical Radiology, Muenchen (Germany); Kiessling, Andreas [University Hospital Giessen and Marburg, Department of Diagnostic Radiology, Marburg (Germany); Pinto dos Santos, Daniel [University Hospital Mainz, Department of Diagnostic and Interventional Radiology, Mainz (Germany); Schuelke, Christoph [University Hospital Muenster, Institute of Clinical Radiology, Muenster (Germany)

2012-12-15

In chemotherapy monitoring, an estimation of the change in tumour size is an important criterion for the assessment of treatment success. This requires a comparison between corresponding lesions in the baseline and follow-up computed tomography (CT) examinations. We evaluate the clinical benefits of an automatic lesion tracking tool that identifies the target lesions in the follow-up CT study and pre-computes the lesion volumes. Four radiologists performed volumetric follow-up examinations for 52 patients with and without lesion tracking. In total, 139 lung nodules, liver metastases and lymph nodes were given as target lesions. We measured reading time, inter-reader variability in lesion identification and volume measurements, and the amount of manual adjustments of the segmentation results. With lesion tracking, target lesion assessment time decreased by 38 % or 22 s per lesion. Relative volume difference between readers was reduced from 0.171 to 0.1. Segmentation quality was comparable with and without lesion tracking. Our automatic lesion tracking tool can make interpretation of follow-up CT examinations quicker and provide results that are less reader-dependent. (orig.)

Development of advanced automatic control system for nuclear ship. 2. Perfect automatic operation after reactor scram events

International Nuclear Information System (INIS)

Yabuuchi, Noriaki; Nakazawa, Toshio; Takahashi, Hiroki; Shimazaki, Junya; Hoshi, Tsutao

1997-11-01

An automatic operation system has been developed for the purpose of realizing a perfect automatic plant operation after reactor scram events. The goal of the automatic operation after a reactor scram event is to bring the reactor hot stand-by condition automatically. The basic functions of this system are as follows; to monitor actions of the equipments of safety actions after a reactor scram, to control necessary control equipments to bring a reactor to a hot stand-by condition automatically, and to energize a decay heat removal system. The performance evaluation on this system was carried out by comparing the results using to Nuclear Ship Engineering Simulation System (NESSY) and the those measured in the scram test of the nuclear ship 'Mutsu'. As the result, it was showed that this system had the sufficient performance to bring a reactor to a hot syand-by condition quickly and safety. (author)

Development of advanced automatic control system for nuclear ship. 2. Perfect automatic operation after reactor scram events

Energy Technology Data Exchange (ETDEWEB)

Yabuuchi, Noriaki; Nakazawa, Toshio; Takahashi, Hiroki; Shimazaki, Junya; Hoshi, Tsutao [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1997-11-01

An automatic operation system has been developed for the purpose of realizing a perfect automatic plant operation after reactor scram events. The goal of the automatic operation after a reactor scram event is to bring the reactor hot stand-by condition automatically. The basic functions of this system are as follows; to monitor actions of the equipments of safety actions after a reactor scram, to control necessary control equipments to bring a reactor to a hot stand-by condition automatically, and to energize a decay heat removal system. The performance evaluation on this system was carried out by comparing the results using to Nuclear Ship Engineering Simulation System (NESSY) and the those measured in the scram test of the nuclear ship `Mutsu`. As the result, it was showed that this system had the sufficient performance to bring a reactor to a hot syand-by condition quickly and safety. (author)

Automated de-identification of free-text medical records

Directory of Open Access Journals (Sweden)

Long William J

2008-07-01

Full Text Available Abstract Background Text-based patient medical records are a vital resource in medical research. In order to preserve patient confidentiality, however, the U.S. Health Insurance Portability and Accountability Act (HIPAA requires that protected health information (PHI be removed from medical records before they can be disseminated. Manual de-identification of large medical record databases is prohibitively expensive, time-consuming and prone to error, necessitating automatic methods for large-scale, automated de-identification. Methods We describe an automated Perl-based de-identification software package that is generally usable on most free-text medical records, e.g., nursing notes, discharge summaries, X-ray reports, etc. The software uses lexical look-up tables, regular expressions, and simple heuristics to locate both HIPAA PHI, and an extended PHI set that includes doctors' names and years of dates. To develop the de-identification approach, we assembled a gold standard corpus of re-identified nursing notes with real PHI replaced by realistic surrogate information. This corpus consists of 2,434 nursing notes containing 334,000 words and a total of 1,779 instances of PHI taken from 163 randomly selected patient records. This gold standard corpus was used to refine the algorithm and measure its sensitivity. To test the algorithm on data not used in its development, we constructed a second test corpus of 1,836 nursing notes containing 296,400 words. The algorithm's false negative rate was evaluated using this test corpus. Results Performance evaluation of the de-identification software on the development corpus yielded an overall recall of 0.967, precision value of 0.749, and fallout value of approximately 0.002. On the test corpus, a total of 90 instances of false negatives were found, or 27 per 100,000 word count, with an estimated recall of 0.943. Only one full date and one age over 89 were missed. No patient names were missed in either

Automatic exchange unit for control rod drive device

International Nuclear Information System (INIS)

Nasu, Seiji; Sasaki, Masayoshi.

1982-01-01

Purpose: To enable automatic reoperation and continuation without external power interruption remedy device at the time of recovering the interrupted power soruce during automatic positioning operation. Constitution: In case of an automatic exchange unit for a control rod drive device of the control type for setting the deviation between the positioning target position and the present position of the device to zero, the position data of the drive device of the positioning target value of the device is automatically read, and an interlock of operation inhibit is applied to a control system until the data reading is completed and automatic operation start or restart conditions are sequentially confirmed. After the confirmation, the interlock is released to start the automatic operation or reoperation. Accordingly, the automatic operation can be safely restarted and continued. (Yoshihara, H.)

Farm-specific economic value of automatic lameness detection systems in dairy cattle: From concepts to operational simulations.

Science.gov (United States)

Van De Gucht, Tim; Saeys, Wouter; Van Meensel, Jef; Van Nuffel, Annelies; Vangeyte, Jurgen; Lauwers, Ludwig

2018-01-01

Although prototypes of automatic lameness detection systems for dairy cattle exist, information about their economic value is lacking. In this paper, a conceptual and operational framework for simulating the farm-specific economic value of automatic lameness detection systems was developed and tested on 4 system types: walkover pressure plates, walkover pressure mats, camera systems, and accelerometers. The conceptual framework maps essential factors that determine economic value (e.g., lameness prevalence, incidence and duration, lameness costs, detection performance, and their relationships). The operational simulation model links treatment costs and avoided losses with detection results and farm-specific information, such as herd size and lameness status. Results show that detection performance, herd size, discount rate, and system lifespan have a large influence on economic value. In addition, lameness prevalence influences the economic value, stressing the importance of an adequate prior estimation of the on-farm prevalence. The simulations provide first estimates for the upper limits for purchase prices of automatic detection systems. The framework allowed for identification of knowledge gaps obstructing more accurate economic value estimation. These include insights in cost reductions due to early detection and treatment, and links between specific lameness causes and their related losses. Because this model provides insight in the trade-offs between automatic detection systems' performance and investment price, it is a valuable tool to guide future research and developments. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Directory of Open Access Journals (Sweden)

Dazhi Jiang

2015-01-01

Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.

Reactor protection system with automatic self-testing and diagnostic

International Nuclear Information System (INIS)

Gaubatz, D.C.

1996-01-01

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ''identical'' values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs

A Cough-Based Algorithm for Automatic Diagnosis of Pertussis

Science.gov (United States)

Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

2016-01-01

Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. PMID:27583523

GASPACHO: a generic automatic solver using proximal algorithms for convex huge optimization problems

Science.gov (United States)

Goossens, Bart; Luong, Hiêp; Philips, Wilfried

2017-08-01

Many inverse problems (e.g., demosaicking, deblurring, denoising, image fusion, HDR synthesis) share various similarities: degradation operators are often modeled by a specific data fitting function while image prior knowledge (e.g., sparsity) is incorporated by additional regularization terms. In this paper, we investigate automatic algorithmic techniques for evaluating proximal operators. These algorithmic techniques also enable efficient calculation of adjoints from linear operators in a general matrix-free setting. In particular, we study the simultaneous-direction method of multipliers (SDMM) and the parallel proximal algorithm (PPXA) solvers and show that the automatically derived implementations are well suited for both single-GPU and multi-GPU processing. We demonstrate this approach for an Electron Microscopy (EM) deconvolution problem.

Position automatic determination technology

International Nuclear Information System (INIS)

1985-10-01

This book tells of method of position determination and characteristic, control method of position determination and point of design, point of sensor choice for position detector, position determination of digital control system, application of clutch break in high frequency position determination, automation technique of position determination, position determination by electromagnetic clutch and break, air cylinder, cam and solenoid, stop position control of automatic guide vehicle, stacker crane and automatic transfer control.

ContextD: an algorithm to identify contextual properties of medical terms in a Dutch clinical corpus.

Science.gov (United States)

Afzal, Zubair; Pons, Ewoud; Kang, Ning; Sturkenboom, Miriam C J M; Schuemie, Martijn J; Kors, Jan A

2014-11-29

In order to extract meaningful information from electronic medical records, such as signs and symptoms, diagnoses, and treatments, it is important to take into account the contextual properties of the identified information: negation, temporality, and experiencer. Most work on automatic identification of these contextual properties has been done on English clinical text. This study presents ContextD, an adaptation of the English ConText algorithm to the Dutch language, and a Dutch clinical corpus. We created a Dutch clinical corpus containing four types of anonymized clinical documents: entries from general practitioners, specialists' letters, radiology reports, and discharge letters. Using a Dutch list of medical terms extracted from the Unified Medical Language System, we identified medical terms in the corpus with exact matching. The identified terms were annotated for negation, temporality, and experiencer properties. To adapt the ConText algorithm, we translated English trigger terms to Dutch and added several general and document specific enhancements, such as negation rules for general practitioners' entries and a regular expression based temporality module. The ContextD algorithm utilized 41 unique triggers to identify the contextual properties in the clinical corpus. For the negation property, the algorithm obtained an F-score from 87% to 93% for the different document types. For the experiencer property, the F-score was 99% to 100%. For the historical and hypothetical values of the temporality property, F-scores ranged from 26% to 54% and from 13% to 44%, respectively. The ContextD showed good performance in identifying negation and experiencer property values across all Dutch clinical document types. Accurate identification of the temporality property proved to be difficult and requires further work. The anonymized and annotated Dutch clinical corpus can serve as a useful resource for further algorithm development.

A neurocomputational model of automatic sequence production.

Science.gov (United States)

Helie, Sebastien; Roeder, Jessica L; Vucovich, Lauren; Rünger, Dennis; Ashby, F Gregory

2015-07-01

Most behaviors unfold in time and include a sequence of submovements or cognitive activities. In addition, most behaviors are automatic and repeated daily throughout life. Yet, relatively little is known about the neurobiology of automatic sequence production. Past research suggests a gradual transfer from the associative striatum to the sensorimotor striatum, but a number of more recent studies challenge this role of the BG in automatic sequence production. In this article, we propose a new neurocomputational model of automatic sequence production in which the main role of the BG is to train cortical-cortical connections within the premotor areas that are responsible for automatic sequence production. The new model is used to simulate four different data sets from human and nonhuman animals, including (1) behavioral data (e.g., RTs), (2) electrophysiology data (e.g., single-neuron recordings), (3) macrostructure data (e.g., TMS), and (4) neurological circuit data (e.g., inactivation studies). We conclude with a comparison of the new model with existing models of automatic sequence production and discuss a possible new role for the BG in automaticity and its implication for Parkinson's disease.

Naming Speed and Effortful and Automatic Inhibition in Children with Arithmetic Learning Disabilities

Science.gov (United States)

D'Amico, Antonella; Passolunghi, Maria Chiara

2009-01-01

We report a two-year longitudinal study aimed at investigating the rate of access to numerical and non-numerical information in long-term memory and the functioning of automatic and effortful cognitive inhibition processes in children with arithmetical learning disabilities (ALDs). Twelve children with ALDs, of age 9.3 years, and twelve…

A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction

Directory of Open Access Journals (Sweden)

Jolien A. van Breen

2017-06-01

Full Text Available Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with feminists, on the other hand, is a politicized identity dimension reflecting attitudes toward the social position of the group: what does it mean to be a woman in terms of disadvantage, inequality, and relative status? We examine the utility of this multiple identity approach in four studies. Study 1 showed that identification with women reflects attitudes toward group characteristics, such as femininity and self-stereotyping, while identification with feminists reflects attitudes toward the group's social position, such as perceived sexism. The two dimensions are shown to be largely independent, and as such provide support for the multiple identity approach. In Studies 2–4, we examine the utility of this multiple identity approach in predicting qualitative differences in gender attitudes. Results show that specific combinations of identification with women and feminists predicted attitudes toward collective action and gender stereotypes. Higher identification with feminists led to endorsement of radical collective action (Study 2 and critical attitudes toward gender stereotypes (Studies 3–4, especially at lower levels of identification with women. The different combinations of high vs. low identification with women and feminists can be thought of as reflecting four theoretical identity “types.” A woman can be (1 strongly identified with neither women nor feminists (“low identifier”, (2 strongly identified with women but less so with feminists (�

A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction

Science.gov (United States)

van Breen, Jolien A.; Spears, Russell; Kuppens, Toon; de Lemus, Soledad

2017-01-01

Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with feminists, on the other hand, is a politicized identity dimension reflecting attitudes toward the social position of the group: what does it mean to be a woman in terms of disadvantage, inequality, and relative status? We examine the utility of this multiple identity approach in four studies. Study 1 showed that identification with women reflects attitudes toward group characteristics, such as femininity and self-stereotyping, while identification with feminists reflects attitudes toward the group's social position, such as perceived sexism. The two dimensions are shown to be largely independent, and as such provide support for the multiple identity approach. In Studies 2–4, we examine the utility of this multiple identity approach in predicting qualitative differences in gender attitudes. Results show that specific combinations of identification with women and feminists predicted attitudes toward collective action and gender stereotypes. Higher identification with feminists led to endorsement of radical collective action (Study 2) and critical attitudes toward gender stereotypes (Studies 3–4), especially at lower levels of identification with women. The different combinations of high vs. low identification with women and feminists can be thought of as reflecting four theoretical identity “types.” A woman can be (1) strongly identified with neither women nor feminists (“low identifier”), (2) strongly identified with women but less so with feminists (�

A Multiple Identity Approach to Gender: Identification with Women, Identification with Feminists, and Their Interaction.

Science.gov (United States)

van Breen, Jolien A; Spears, Russell; Kuppens, Toon; de Lemus, Soledad

2017-01-01

Across four studies, we examine multiple identities in the context of gender and propose that women's attitudes toward gender group membership are governed by two largely orthogonal dimensions of gender identity: identification with women and identification with feminists. We argue that identification with women reflects attitudes toward the content society gives to group membership: what does it mean to be a woman in terms of group characteristics, interests and values? Identification with feminists, on the other hand, is a politicized identity dimension reflecting attitudes toward the social position of the group: what does it mean to be a woman in terms of disadvantage, inequality, and relative status? We examine the utility of this multiple identity approach in four studies. Study 1 showed that identification with women reflects attitudes toward group characteristics, such as femininity and self-stereotyping, while identification with feminists reflects attitudes toward the group's social position, such as perceived sexism. The two dimensions are shown to be largely independent, and as such provide support for the multiple identity approach. In Studies 2-4, we examine the utility of this multiple identity approach in predicting qualitative differences in gender attitudes. Results show that specific combinations of identification with women and feminists predicted attitudes toward collective action and gender stereotypes. Higher identification with feminists led to endorsement of radical collective action (Study 2) and critical attitudes toward gender stereotypes (Studies 3-4), especially at lower levels of identification with women. The different combinations of high vs. low identification with women and feminists can be thought of as reflecting four theoretical identity "types." A woman can be (1) strongly identified with neither women nor feminists ("low identifier"), (2) strongly identified with women but less so with feminists ("traditional identifier"), (3

A New Approach to Environmentally Safe Unique Identification of Long-Term Stored Copper Canisters

International Nuclear Information System (INIS)

Chernikova, D.; Axell, K.; Nordlund, A.

2015-01-01

A new approach to environmentally safe unique identification of long-term stored copper canisters is suggested in this paper. The approach is based on the use of a tungstenbased insert placed inside a copper cask between a top iron lid and a copper lid. The insert/label is marked with unique code in a form of binary number, which is implemented as a combination of holes in the tungsten plate. In order to provide a necessary redundancy of the identifier, the tungsten label marked with few identical binary codes. The position of code (i.e., holes in tungsten) corresponds to a predefined placement of the spent fuel assembles in the iron container. This is in order to avoid any non-uniformity of the gamma background at the canister surface caused by a presence of iron-filled spaces between spent nuclear fuel assembles. Due to the use of the tungsten material gamma rays emitted by the spent fuel assembles are collimated in a specific way because of strong attenuation properties of tungsten. As a result, the variation in the gamma-counting rate in a detector array placed on the top of copper lid provides the distribution of the holes in the tungsten insert or in other words the unique identifier. Thus, this way of identification of copper cask do not impair the integrity of the cask and it offers a way that the information about spent nuclear fuel is legible for a time scale up to a few thousands years. (author)

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

Science.gov (United States)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

IDENTIFICATION SYSTEM, TRACKING AND SUPPORT FOR VESSELS ON RIVERS

Directory of Open Access Journals (Sweden)

SAMOILESCU Gheorghe

2015-05-01

Full Text Available According to the program COMPRIS (Consortium Operational Management Platform River Information Services, AIS (Automatic Identification System, RIS (River Information Services have compiled a reference model based on the perspective of navigation on the river with related information services. This paper presents a tracking and monitoring surveillance system necessary for assistance of each ship sailing in an area of interest. It shows the operating principle of the composition and role of each equipment. Transferring data to traffic monitoring authority is part of this work.

The ‘Continuing Misfortune’ of Automatism in Early Surrealism

Directory of Open Access Journals (Sweden)

Tessel M. Bauduin

2015-09-01

Full Text Available In the 1924 Manifesto of Surrealism surrealist leader André Breton (1896-1966 defined Surrealism as ‘psychic automatism in its pure state,’ positioning ‘psychic automatism’ as both a concept and a technique. This definition followed upon an intense period of experimentation with various forms of automatism among the proto-surrealist group; predominantly automatic writing, but also induced dream states. This article explores how surrealist ‘psychic automatism’ functioned as a mechanism for communication, or the expression of thought as directly as possible through the unconscious, in the first two decades of Surrealism. It touches upon automatic writing, hysteria as an automatic bodily performance of the unconscious, dreaming and the experimentation with induced dream states, and automatic drawing and other visual arts-techniques that could be executed more or less automatically as well. For all that the surrealists reinvented automatism for their own poetic, artistic and revolutionary aims, the automatic techniques were primarily drawn from contemporary Spiritualism, psychical research and experimentation with mediums, and the article teases out the connections to mediumistic automatism. It is demonstrated how the surrealists effectively and successfully divested automatism of all things spiritual. It furthermore becomes clear that despite various mishaps, automatism in many forms was a very successful creative technique within Surrealism.

Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

NARCIS (Netherlands)

Chen, Junwen; Liu, Zhigang; Wang, H.; Nunez Vicencio, Alfredo; Han, Zhiwei

2018-01-01

The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary

Price strategy and pricing strategy: terms and content identification

OpenAIRE

Panasenko Tetyana

2015-01-01

The article is devoted to the terminology and content identification of seemingly identical concepts "price strategy" and "pricing strategy". The article contains evidence that the price strategy determines the direction, principles and procedure of implementing the company price policy and pricing strategy creates a set of rules and practical methods of price formation in accordance with the pricing strategy of the company.

Automatic semi-continuous accumulation chamber for diffuse gas emissions monitoring in volcanic and non-volcanic areas

Science.gov (United States)

Lelli, Matteo; Raco, Brunella; Norelli, Francesco; Virgili, Giorgio; Continanza, Davide

2016-04-01

Since various decades the accumulation chamber method is intensively used in monitoring activities of diffuse gas emissions in volcanic areas. Although some improvements have been performed in terms of sensitivity and reproducibility of the detectors, the equipment used for measurement of gas emissions temporal variation usually requires expensive and bulky equipment. The unit described in this work is a low cost, easy to install-and-manage instrument that will make possible the creation of low-cost monitoring networks. The Non-Dispersive Infrared detector used has a concentration range of 0-5% CO2, but the substitution with other detector (range 0-5000 ppm) is possible and very easy. Power supply unit has a 12V, 7Ah battery, which is recharged by a 35W solar panel (equipped with charge regulator). The control unit contains a custom programmed CPU and the remote transmission is assured by a GPRS modem. The chamber is activated by DataLogger unit, using a linear actuator between the closed position (sampling) and closed position (idle). A probe for the measure of soil temperature, soil electrical conductivity, soil volumetric water content, air pressure and air temperature is assembled on the device, which is already arranged for the connection of others external sensors, including an automatic weather station. The automatic station has been tested on the field at Lipari island (Sicily, Italy) during a period of three months, performing CO2 flux measurement (and also weather parameters), each 1 hour. The possibility to measure in semi-continuous mode, and at the same time, the gas fluxes from soil and many external parameters, helps the time series analysis aimed to the identification of gas flux anomalies due to variations in deep system (e.g. onset of volcanic crises) from those triggered by external conditions.

Tests with VHR images for the identification of olive trees and other fruit trees in the European Union

Science.gov (United States)

Masson, Josiane; Soille, Pierre; Mueller, Rick

2004-10-01

In the context of the Common Agricultural Policy (CAP) there is a strong interest of the European Commission for counting and individually locating fruit trees. An automatic counting algorithm developed by the JRC (OLICOUNT) was used in the past for olive trees only, on 1m black and white orthophotos but with limits in case of young trees or irregular groves. This study investigates the improvement of fruit tree identification using VHR images on a large set of data in three test sites, one in Creta (Greece; one in the south-east of France with a majority of olive trees and associated fruit trees, and the last one in Florida on citrus trees. OLICOUNT was compared with two other automatic tree counting, applications, one using the CRISP software on citrus trees and the other completely automatic based on regional minima (morphological image analysis). Additional investigation was undertaken to refine the methods. This paper describes the automatic methods and presents the results derived from the tests.

Programmable automatic alpha--beta air sample counter

International Nuclear Information System (INIS)

Howell, W.P.

1978-01-01

A programmable automatic alpha-beta air sample counter was developed for routine sample counting by operational health physics personnel. The system is composed of an automatic sample changer utilizing a large silicon diode detector, an electronic counting system with energy analysis capability, an automatic data acquisition controller, an interface module, and a teletypewriter with paper tape punch and paper tape reader. The system is operated through the teletypewriter keyboard and the paper tape reader, which are used to instruct the automatic data acquisition controller. Paper tape programs are provided for background counting, Chi 2 test, and sample counting. Output data are printed by the teletypewriter on standard continuous roll or multifold paper. Data are automatically corrected for background and counter efficiency

Automatic control algorithm effects on energy production

Science.gov (United States)

Mcnerney, G. M.

1981-01-01

A computer model was developed using actual wind time series and turbine performance data to simulate the power produced by the Sandia 17-m VAWT operating in automatic control. The model was used to investigate the influence of starting algorithms on annual energy production. The results indicate that, depending on turbine and local wind characteristics, a bad choice of a control algorithm can significantly reduce overall energy production. The model can be used to select control algorithms and threshold parameters that maximize long term energy production. The results from local site and turbine characteristics were generalized to obtain general guidelines for control algorithm design.

Automated identification of crystallographic ligands using sparse-density representations

International Nuclear Information System (INIS)

Carolan, C. G.; Lamzin, V. S.

2014-01-01

A novel procedure for identifying ligands in macromolecular crystallographic electron-density maps is introduced. Density clusters in such maps can be rapidly attributed to one of 82 different ligands in an automated manner. A novel procedure for the automatic identification of ligands in macromolecular crystallographic electron-density maps is introduced. It is based on the sparse parameterization of density clusters and the matching of the pseudo-atomic grids thus created to conformationally variant ligands using mathematical descriptors of molecular shape, size and topology. In large-scale tests on experimental data derived from the Protein Data Bank, the procedure could quickly identify the deposited ligand within the top-ranked compounds from a database of candidates. This indicates the suitability of the method for the identification of binding entities in fragment-based drug screening and in model completion in macromolecular structure determination

A network identity authentication system based on Fingerprint identification technology

Science.gov (United States)

Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

2005-10-01

Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

Robot-assisted automatic ultrasound calibration.

Science.gov (United States)

Aalamifar, Fereshteh; Cheng, Alexis; Kim, Younsu; Hu, Xiao; Zhang, Haichong K; Guo, Xiaoyu; Boctor, Emad M

2016-10-01

Ultrasound (US) calibration is the process of determining the unknown transformation from a coordinate frame such as the robot's tooltip to the US image frame and is a necessary task for any robotic or tracked US system. US calibration requires submillimeter-range accuracy for most applications, but it is a time-consuming and repetitive task. We provide a new framework for automatic US calibration with robot assistance and without the need for temporal calibration. US calibration based on active echo (AE) phantom was previously proposed, and its superiority over conventional cross-wire phantom-based calibration was shown. In this work, we use AE to guide the robotic arm motion through the process of data collection; we combine the capability of the AE point to localize itself in the frame of the US image with the automatic motion of the robotic arm to provide a framework for calibrating the arm to the US image automatically. We demonstrated the efficacy of the automated method compared to the manual method through experiments. To highlight the necessity of frequent ultrasound calibration, it is demonstrated that the calibration precision changed from 1.67 to 3.20 mm if the data collection is not repeated after a dismounting/mounting of the probe holder. In a large data set experiment, similar reconstruction precision of automatic and manual data collection was observed, while the time was reduced by 58 %. In addition, we compared ten automatic calibrations with ten manual ones, each performed in 15 min, and showed that all the automatic ones could converge in the case of setting the initial matrix as identity, while this was not achieved by manual data sets. Given the same initial matrix, the repeatability of the automatic was [0.46, 0.34, 0.80, 0.47] versus [0.42, 0.51, 0.98, 1.15] mm in the manual case for the US image four corners. The submillimeter accuracy requirement of US calibration makes frequent data collections unavoidable. We proposed an automated

New Directions In Radioisotope Spectrum Identification

International Nuclear Information System (INIS)

Salaymeh, S.; Jeffcoat, R.

2010-01-01

Recent studies have found the performance of commercial handheld detectors with automatic RIID software to be less than acceptable. Previously, we have explored approaches rooted in speech processing such as cepstral features and information-theoretic measures. Scientific advances are often made when researchers identify mathematical or physical commonalities between different fields and are able to apply mature techniques or algorithms developed in one field to another field which shares some of the same challenges. The authors of this paper have identified similarities between the unsolved problems faced in gamma-spectroscopy for automated radioisotope identification and the challenges of the much larger body of research in speech processing. Our research has led to a probabilistic framework for describing and solving radioisotope identification problems. Many heuristic approaches to classification in current use, including for radioisotope classification, make implicit probabilistic assumptions which are not clear to the users and, if stated explicitly, might not be considered desirable. Our framework leads to a classification approach with demonstrable improvements using standard feature sets on proof-of-concept simulated and field-collected data.

Requirements to a Norwegian national automatic gamma monitoring system

DEFF Research Database (Denmark)

Lauritzen, B.; Jensen, Per Hedemann; Nielsen, F.

2005-01-01

increments above the natural background levels. The study is based upon simplified deterministic calculations of the radiological consequences of generic nuclear accident scenarios. The density of gammamonitoring stations has been estimated from an analysis of the dispersion of radioactive materials over......An assessment of the overall requirements to a Norwegian gamma-monitoring network is undertaken with special emphasis on the geographical distribution of automatic gamma monitoring stations, type of detectors in such stations and the sensitivity of thesystem in terms of ambient dose equivalent rate...

MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank.

Science.gov (United States)

Mao, Yuqing; Lu, Zhiyong

2017-04-17

MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in biomedical research. Unfortunately, given its manual nature, the process of MeSH indexing is both time-consuming (new articles are not immediately indexed until 2 or 3 months later) and costly (approximately ten dollars per article). In response, automatic indexing by computers has been previously proposed and attempted but remains challenging. In order to advance the state of the art in automatic MeSH indexing, a community-wide shared task called BioASQ was recently organized. We propose MeSH Now, an integrated approach that first uses multiple strategies to generate a combined list of candidate MeSH terms for a target article. Through a novel learning-to-rank framework, MeSH Now then ranks the list of candidate terms based on their relevance to the target article. Finally, MeSH Now selects the highest-ranked MeSH terms via a post-processing module. We assessed MeSH Now on two separate benchmarking datasets using traditional precision, recall and F 1 -score metrics. In both evaluations, MeSH Now consistently achieved over 0.60 in F-score, ranging from 0.610 to 0.612. Furthermore, additional experiments show that MeSH Now can be optimized by parallel computing in order to process MEDLINE documents on a large scale. We conclude that MeSH Now is a robust approach with state-of-the-art performance for automatic MeSH indexing and that MeSH Now is capable of processing PubMed scale documents within a reasonable time frame. http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/MeSHNow/ .

Sensitivity analysis and design optimization through automatic differentiation

International Nuclear Information System (INIS)

Hovland, Paul D; Norris, Boyana; Strout, Michelle Mills; Bhowmick, Sanjukta; Utke, Jean

2005-01-01

Automatic differentiation is a technique for transforming a program or subprogram that computes a function, including arbitrarily complex simulation codes, into one that computes the derivatives of that function. We describe the implementation and application of automatic differentiation tools. We highlight recent advances in the combinatorial algorithms and compiler technology that underlie successful implementation of automatic differentiation tools. We discuss applications of automatic differentiation in design optimization and sensitivity analysis. We also describe ongoing research in the design of language-independent source transformation infrastructures for automatic differentiation algorithms

An intelligent identification algorithm for the monoclonal picking instrument

Science.gov (United States)

Yan, Hua; Zhang, Rongfu; Yuan, Xujun; Wang, Qun

2017-11-01

The traditional colony selection is mainly operated by manual mode, which takes on low efficiency and strong subjectivity. Therefore, it is important to develop an automatic monoclonal-picking instrument. The critical stage of the automatic monoclonal-picking and intelligent optimal selection is intelligent identification algorithm. An auto-screening algorithm based on Support Vector Machine (SVM) is proposed in this paper, which uses the supervised learning method, which combined with the colony morphological characteristics to classify the colony accurately. Furthermore, through the basic morphological features of the colony, system can figure out a series of morphological parameters step by step. Through the establishment of maximal margin classifier, and based on the analysis of the growth trend of the colony, the selection of the monoclonal colony was carried out. The experimental results showed that the auto-screening algorithm could screen out the regular colony from the other, which meets the requirement of various parameters.

An Automated System for Garment Texture Design Class Identification

Directory of Open Access Journals (Sweden)

Emon Kumar Dey

2015-09-01

Full Text Available Automatic identification of garment design class might play an important role in the garments and fashion industry. To achieve this, essential initial works are found in the literature. For example, construction of a garment database, automatic segmentation of garments from real life images, categorizing them into the type of garments such as shirts, jackets, tops, skirts, etc. It is now essential to find a system such that it will be possible to identify the particular design (printed, striped or single color of garment product for an automated system to recommend the garment trends. In this paper, we have focused on this specific issue and thus propose two new descriptors namely Completed CENTRIST (cCENTRIST and Ternary CENTRIST (tCENTRIST. To test these descriptors, we used two different publically available databases. The experimental results of these databases demonstrate that both cCENTRIST and tCENTRIST achieve nearly about 3% more accuracy than the existing state-of-the art methods.

The sensitivity of characteristics of cyclone activity to identification procedures in tracking algorithms

Directory of Open Access Journals (Sweden)

Irina Rudeva

2014-12-01

Full Text Available The IMILAST project (‘Intercomparison of Mid-Latitude Storm Diagnostics’ was set up to compare low-level cyclone climatologies derived from a number of objective identification algorithms. This paper is a contribution to that effort where we determine the sensitivity of three key aspects of Northern Hemisphere cyclone behaviour [namely the number of cyclones, their intensity (defined here in terms of the central pressure and their deepening rates] to specific features in the automatic cyclone identification. The sensitivity is assessed with respect to three such features which may be thought to influence the ultimate climatology produced (namely performance in areas of complicated orography, time of the detection of a cyclone, and the representation of rapidly propagating cyclones. We make use of 13 tracking methods in this analysis. We find that the filtering of cyclones in regions where the topography exceeds 1500 m can significantly change the total number of cyclones detected by a scheme, but has little impact on the cyclone intensity distribution. More dramatically, late identification of cyclones (simulated by the truncation of the first 12 hours of cyclone life cycle leads to a large reduction in cyclone numbers over the both continents and oceans (up to 80 and 40%, respectively. Finally, the potential splitting of the trajectories at times of the fastest propagation has a negligible climatological effect on geographical distribution of cyclone numbers. Overall, it has been found that the averaged deepening rates and averaged cyclone central pressure are rather insensitive to the specifics of the tracking procedure, being more sensitive to the data set used (as shown in previous studies and the geographical location of a cyclone.

Identification of apical vertebra for grading of idiopathic scoliosis using image processing.

Science.gov (United States)

Anitha, H; Prabhu, G K

2012-02-01

Scoliosis is a 3-D deformity of spinal column, characterized by both lateral curvature and vertebral rotation. The disease can be caused by congenital, developmental, or degenerative problems; but most cases of scoliosis actually have no known cause, and this is known as idiopathic scoliosis. Vertebral rotation has become increasingly prominent in the study of scoliosis and the most deformed vertebra is named as apical vertebra. Apical vertebral deformity demonstrates significance in both preoperative and postoperative assessment, providing better appreciation of the impact of bracing or surgical interventions. Precise measurement of apical vertebral rotation in terms of grading is most valuable for the determination of reference value in normal and pathological conditions for better understanding of scoliosis. Routine quantitative evaluation of vertebral rotation is difficult and error prone due to limitations of observer characteristic and specific imaging property. This paper proposes automatic identification of the apical vertebra and its parameter that depends on the objective criteria of measurement using active contour models. The proposed technique is more accurate and is a reliable measurement compared to manual and computer-assisted system.

Automatically sweeping dual-channel boxcar integrator

International Nuclear Information System (INIS)

Keefe, D.J.; Patterson, D.R.

1978-01-01

An automatically sweeping dual-channel boxcar integrator has been developed to automate the search for a signal that repeatedly follows a trigger pulse by a constant or slowly varying time delay when that signal is completely hidden in random electrical noise and dc-offset drifts. The automatically sweeping dual-channel boxcar integrator improves the signal-to-noise ratio and eliminates dc-drift errors in the same way that a conventional dual-channel boxcar integrator does, but, in addition, automatically locates the hidden signal. When the signal is found, its time delay is displayed with 100-ns resolution, and its peak value is automatically measured and displayed. This relieves the operator of the tedious, time-consuming, and error-prone search for the signal whenever the time delay changes. The automatically sweeping boxcar integrator can also be used as a conventional dual-channel boxcar integrator. In either mode, it can repeatedly integrate a signal up to 990 times and thus make accurate measurements of the signal pulse height in the presence of random noise, dc offsets, and unsynchronized interfering signals

Price strategy and pricing strategy: terms and content identification

Directory of Open Access Journals (Sweden)

Panasenko Tetyana

2015-11-01

Full Text Available The article is devoted to the terminology and content identification of seemingly identical concepts "price strategy" and "pricing strategy". The article contains evidence that the price strategy determines the direction, principles and procedure of implementing the company price policy and pricing strategy creates a set of rules and practical methods of price formation in accordance with the pricing strategy of the company.

What Automaticity Deficit? Activation of Lexical Information by Readers with Dyslexia in a Rapid Automatized Naming Stroop-Switch Task

Science.gov (United States)

Jones, Manon W.; Snowling, Margaret J.; Moll, Kristina

2016-01-01

Reading fluency is often predicted by rapid automatized naming (RAN) speed, which as the name implies, measures the automaticity with which familiar stimuli (e.g., letters) can be retrieved and named. Readers with dyslexia are considered to have less "automatized" access to lexical information, reflected in longer RAN times compared with…

Applications of radio frequency identification systems in the mining industry

Energy Technology Data Exchange (ETDEWEB)

Hind, D J [Davis Derby Ltd., Derby (United Kingdom)

1994-01-01

Radio Frequency Identification Systems (RFID) are one of the automatic data capture technologies taking over from bar codes and magnetic swipe cards in many applications involving automatic hands free operation in arduous environments. RFID systems are based on the use of miniature radio transponders carrying encoded electronic data that is used to uniquely identify the identity of transponders. The paper reviews the types of system available and compares the various techniques involved in the different systems. The various types of transponder are described including the latest state of the art passive read/write high performance types. The problems involved in designing and certifying a system for use in hazardous areas are described, with particular reference to the problems of inadvertent detonator ignition by radio systems. Applications of RFID systems in the mining industry are described, covering applications both on the surface and underground. 1 ref., 10 figs.

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

Science.gov (United States)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.

Automatic visual monitoring of welding procedure in stainless steel kegs

Science.gov (United States)

Leo, Marco; Del Coco, Marco; Carcagnì, Pierluigi; Spagnolo, Paolo; Mazzeo, Pier Luigi; Distante, Cosimo; Zecca, Raffaele

2018-05-01

In this paper a system for automatic visual monitoring of welding process, in dry stainless steel kegs for food storage, is proposed. In the considered manufacturing process the upper and lower skirts are welded to the vessel by means of Tungsten Inert Gas (TIG) welding. During the process several problems can arise: 1) residuals on the bottom 2) darker weld 3) excessive/poor penetration and 4) outgrowths. The proposed system deals with all the four aforementioned problems and its inspection performances have been evaluated by using a large set of kegs demonstrating both the reliability in terms of defect detection and the suitability to be introduced in the manufacturing system in terms of computational costs.

14 CFR 29.1329 - Automatic pilot system.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Automatic pilot system. 29.1329 Section 29... pilot system. (a) Each automatic pilot system must be designed so that the automatic pilot can— (1) Be sufficiently overpowered by one pilot to allow control of the rotorcraft; and (2) Be readily and positively...

14 CFR 27.1329 - Automatic pilot system.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Automatic pilot system. 27.1329 Section 27... pilot system. (a) Each automatic pilot system must be designed so that the automatic pilot can— (1) Be sufficiently overpowered by one pilot to allow control of the rotorcraft; and (2) Be readily and positively...

3D automatic exposure control for 64-detector row CT: Radiation dose reduction in chest phantom study

Energy Technology Data Exchange (ETDEWEB)

Matsumoto, Keiko, E-mail: palm_kei@yahoo.co.jp [Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo (Japan); Department of Radiology, Yamanashi University, Shimokato, Yamanashi (Japan); Ohno, Yoshiharu; Koyama, Hisanobu; Kono, Atsushi [Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo (Japan); Inokawa, Hiroyasu [Toshiba Medical Systems, Ohtawara, Tochigi (Japan); Onishi, Yumiko [Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo (Japan); Nogami, Munenobu [Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo (Japan); Division of Image-Based Medicine, Institute of Biomedical Research and Innovation, Kobe, Hyogo (Japan); Takenaka, Daisuke [Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo (Japan); Araki, Tsutomu [Department of Radiology, Yamanashi University, Shimokato, Yamanashi (Japan); Sugimura, Kazuro [Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Hyogo (Japan)

2011-03-15

Purpose: The purpose of this study was to determine the utility of three-dimensional (3D) automatic exposure control (AEC) for low-dose CT examination in a chest phantom study. Materials and methods: A chest CT phantom including simulated focal ground-glass opacities (GGOs) and nodules was scanned with a 64-detector row CT with and without AEC. Performance of 3D AEC included changing targeted standard deviations (SDs) of image noise from scout view. To determine the appropriate targeted SD number for identification, the capability of overall identification with the CT protocol adapted to each of the targeted SDs was compared with that obtained with CT without AEC by means of receiver operating characteristic analysis. Results: When targeted SD values equal to or higher than 250 were used, areas under the curve (Azs) of nodule identification with CT protocol using AEC were significantly smaller than that for CT protocol without AEC (p < 0.05). When targeted SD numbers at equal to or more than 180 were adapted, Azs of CT protocol with AEC had significantly smaller than that without AEC (p < 0.05). Conclusion: This phantom study shows 3D AEC is useful for low-dose lung CT examination, and can reduce the radiation dose while maintaining good identification capability and good image quality.

Automatic differentiation algorithms in model analysis

NARCIS (Netherlands)

Huiskes, M.J.

2002-01-01

Title: Automatic differentiation algorithms in model analysis
Author: M.J. Huiskes
Date: 19 March, 2002

In this thesis automatic differentiation algorithms and derivative-based methods

Automatic learning-based beam angle selection for thoracic IMRT

International Nuclear Information System (INIS)

Amit, Guy; Marshall, Andrea; Purdie, Thomas G.; Jaffray, David A.; Levinshtein, Alex; Hope, Andrew J.; Lindsay, Patricia; Pekar, Vladimir

2015-01-01

Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume

Unisampo/shaman/linssi Automatic gamma-spectrum pipeline for nuclear emergency preparedness

International Nuclear Information System (INIS)

Zhang Weihua; Kurt Ungar; Pertti Aainio; Jarmo Ala-Heikkila; Harri Toivonen; Teemu Siiskonen; Arto Isolankila; Antero Kuusi

2005-01-01

Linux System for Spectral Information (LINSSI) is an SQL database and established under Linux. It is being developed in collaboration with the Radiation Physics Group of Helsinki University of Technology (RPG/HUT), Finnish National Data Centre (FiNDC), Aerosol Laboratory of the Finnish Radiation and Nuclear Safety Authority (ASL/STUK) and Radiation Protection Bureau of Health Canada (RPB/HC). The database is for environmental radiation monitoring and nuclear emergency preparedness purposes. It is designed not only for storage of information but it is also a platform for interfacing different analysis tools. The structure of database has been published and described at website http://www.hut.fi/Units/AES/projects/radphys/linssi/. It is created as a transparent database structure which could be used for different applications. Thus, other companies and organization are encouraged to provide software to handle and share the information in the database, both in the form of input and output. In January 2004, first LINSSI database released at STUK is compatible with UniSampo/Shaman. Unisampo is a peak analysis software with some identification capabilities; Shaman is the genuine nuclide identification software and also for activity calculation and Linssi is a MySQL database. Now the system is mainly focus on Gamma-ray spectrometry. After a short period of testing, this automatic pipeline becomes operational at PRB in April 2004. Currently daily Gamma spectrum information from all CTBT radionuclide monitoring stations have been processing automatically; at this moment more than 20 thousand cases have been stored in database. A www-based user interface, zero time calculation, station statistic analysis tool and ARR report scripts have been developed. In recent System-wide Performance Test (SPT) of CTBT, the pipeline played an important role at Canadian nuclear data center. With this system we can very easily report the automated, also the reviewed results to IDC based on

An online ID identification system for liquefied-gas cylinder plant

Science.gov (United States)

He, Jin; Ding, Zhenwen; Han, Lei; Zhang, Hao

2017-11-01

An automatic ID identification system for gas cylinders' online production was developed based on the production conditions and requirements of the Technical Committee for Standardization of Gas Cylinders. A cylinder ID image acquisition system was designed to improve the image contrast of ID regions on gas cylinders against the background. Then the ID digits region was located by the CNN template matching algorithm. Following that, an adaptive threshold method based on the analysis of local average grey value and standard deviation was proposed to overcome defects of non-uniform background in the segmentation results. To improve the single digit identification accuracy, two BP neural networks were trained respectively for the identification of all digits and the easily confusable digits. If the single digit was classified as one of confusable digits by the former BP neural network, it was further tested by the later one, and the later result was taken as the final identification result of this single digit. At last, the majority voting was adopted to decide the final identification result for the 6-digit cylinder ID. The developed system was installed on a production line of a liquefied-petroleum-gas cylinder plant and worked in parallel with the existing weighing step on the line. Through the field test, the correct identification rate for single ID digit was 94.73%, and none of the tested 2000 cylinder ID was misclassified through the majority voting.

Automatic writer identification using connected-component contours and edge-based features of uppercase western script

NARCIS (Netherlands)

Schomaker, L; Bulacu, M

In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO(3)s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected

Automatized near-real-time short-term Probabilistic Volcanic Hazard Assessment of tephra dispersion before eruptions: BET_VHst for Vesuvius and Campi Flegrei during recent exercises

Science.gov (United States)

Selva, Jacopo; Costa, Antonio; Sandri, Laura; Rouwet, Dmtri; Tonini, Roberto; Macedonio, Giovanni; Marzocchi, Warner

2015-04-01

Probabilistic Volcanic Hazard Assessment (PVHA) represents the most complete scientific contribution for planning rational strategies aimed at mitigating the risk posed by volcanic activity at different time scales. The definition of the space-time window for PVHA is related to the kind of risk mitigation actions that are under consideration. Short temporal intervals (days to weeks) are important for short-term risk mitigation actions like the evacuation of a volcanic area. During volcanic unrest episodes or eruptions, it is of primary importance to produce short-term tephra fallout forecast, and frequently update it to account for the rapidly evolving situation. This information is obviously crucial for crisis management, since tephra may heavily affect building stability, public health, transportations and evacuation routes (airports, trains, road traffic) and lifelines (electric power supply). In this study, we propose a methodology named BET_VHst (Selva et al. 2014) for short-term PVHA of volcanic tephra dispersal based on automatic interpretation of measures from the monitoring system and physical models of tephra dispersal from all possible vent positions and eruptive sizes based on frequently updated meteorological forecasts. The large uncertainty at all the steps required for the analysis, both aleatory and epistemic, is treated by means of Bayesian inference and statistical mixing of long- and short-term analyses. The BET_VHst model is here presented through its implementation during two exercises organized for volcanoes in the Neapolitan area: MESIMEX for Mt. Vesuvius, and VUELCO for Campi Flegrei. References Selva J., Costa A., Sandri L., Macedonio G., Marzocchi W. (2014) Probabilistic short-term volcanic hazard in phases of unrest: a case study for tephra fallout, J. Geophys. Res., 119, doi: 10.1002/2014JB011252

The interaction of short-term and long-term memory in phonetic category formation

Science.gov (United States)

Harnsberger, James D.

2002-05-01

This study examined the role that short-term memory capacity plays in the relationship between novel stimuli (e.g., non-native speech sounds, native nonsense words) and phonetic categories in long-term memory. Thirty native speakers of American English were administered five tests: categorial AXB discrimination using nasal consonants from Malayalam; categorial identification, also using Malayalam nasals, which measured the influence of phonetic categories in long-term memory; digit span; nonword span, a short-term memory measure mediated by phonetic categories in long-term memory; and paired-associate word learning (word-word and word-nonword pairs). The results showed that almost all measures were significantly correlated with one another. The strongest predictor for the discrimination and word-nonword learning results was nonword (r=+0.62) and digit span (r=+0.51), respectively. When the identification test results were partialed out, only nonword span significantly correlated with discrimination. The results show a strong influence of short-term memory capacity on the encoding of phonetic detail within phonetic categories and suggest that long-term memory representations regulate the capacity of short-term memory to preserve information for subsequent encoding. The results of this study will also be discussed with regards to resolving the tension between episodic and abstract models of phonetic category structure.

Automatic identification of optimal marker genes for phenotypic and taxonomic groups of microorganisms.

Directory of Open Access Journals (Sweden)

Elad Segev

Full Text Available Finding optimal markers for microorganisms important in the medical, agricultural, environmental or ecological fields is of great importance. Thousands of complete microbial genomes now available allow us, for the first time, to exhaustively identify marker proteins for groups of microbial organisms. In this work, we model the biological task as the well-known mathematical "hitting set" problem, solving it based on both greedy and randomized approximation algorithms. We identify unique markers for 17 phenotypic and taxonomic microbial groups, including proteins related to the nitrite reductase enzyme as markers for the non-anammox nitrifying bacteria group, and two transcription regulation proteins, nusG and yhiF, as markers for the Archaea and Escherichia/Shigella taxonomic groups, respectively. Additionally, we identify marker proteins for three subtypes of pathogenic E. coli, which previously had no known optimal markers. Practically, depending on the completeness of the database this algorithm can be used for identification of marker genes for any microbial group, these marker genes may be prime candidates for the understanding of the genetic basis of the group's phenotype or to help discover novel functions which are uniquely shared among a group of microbes. We show that our method is both theoretically and practically efficient, while establishing an upper bound on its time complexity and approximation ratio; thus, it promises to remain efficient and permit the identification of marker proteins that are specific to phenotypic or taxonomic groups, even as more and more bacterial genomes are being sequenced.

Design and implementation of microcontroller-based automatic sequence counting and switching system

Directory of Open Access Journals (Sweden)

Joshua ABOLARINWA

2015-05-01

Full Text Available Technological advancement and its influence on human being have been on the increase in recent time. Major areas of such influence, include monitoring and control activities. In order to keep track of human movement in and out of a particular building, there is the need for an automatic counting system. Therefore, in this paper, we present the design and implementation of a microcontroller-based automatic sequence counting and switching system. This system was designed and developed to save cost, time, energy, and to achieve seamless control in the event of switching on or off of electrical appliances within a building. Top-down modular design approach was used in conjunction with the versatility of microcontroller. The system is able to monitor, sequentially count the number of entry and exit of people through an entrance, afterwards, automatically control any electrical device connected to it. From various tests and measurements obtained, there are comparative benefits derived from the deployment of this system in terms of simplicity and accuracy over similar system that is not microcontroller-based. Therefore, this system can be deployed at commercial quantity with wide range of applications in homes, offices and other public places.

Impact of a radio-frequency identification system and information interchange on clearance processes for cargo at border posts

Directory of Open Access Journals (Sweden)

Ernest Bhero

2015-11-01

Full Text Available Background: Improved operational efficiency is important to role players in cross-border logistics and trade corridors. Cargo owners and cargo forwarders have been particularly concerned about long delays in the processing and clearing of cargo at border posts. Field studies suggest that these delays are due to a combination of factors, such as a lack of optimum system configurations and non-optimised human-dependent operations, which make the operations prone to corruption and other malpractices. Objectives: This article presents possible strategies for improving some of the operations in this sector. The research hinges on two key questions: (1 what is the impact of information interchange between stakeholders on the cargo transit time and (2 how will cargo transit time be impacted upon by automatic identification of cargo and the status of cargo seals on arriving vehicles at the border? Method: The use of information communication systems enabled by automatic identification systems (incorporating radio-frequency identification technology is suggested. Results: Results obtained by the described simulation model indicate that improvements of up to 82% with regard to transit time are possible using these techniques. Conclusion: The findings therefore demonstrate how operations at border posts can be improved through the use of appropriate technology and configuration of the operations.

Automatic intelligent cruise control

OpenAIRE

Stanton, NA; Young, MS

2006-01-01

This paper reports a study on the evaluation of automatic intelligent cruise control (AICC) from a psychological perspective. It was anticipated that AICC would have an effect upon the psychology of driving—namely, make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but might reduce the workload and make driving might less stressful. Drivers were asked to drive in a driving simulator under manual and automatic inte...

Screening local Lactobacilli from Iran in terms of production of lactic acid and identification of superior strains

Directory of Open Access Journals (Sweden)

Fatemeh Soleimanifard

2015-12-01

Full Text Available Introduction: Lactobacilli are a group of lactic acid bacteria that their final product of fermentation is lactic acid. The objective of this research is selection of local Lactobacilli producing L (+ lactic acid. Materials and methods: In this research the local strains were screened based on the ability to produce lactic acid. The screening was performed in two stages. The first stage was the titration method and the second stage was the enzymatic method. The superior strains obtained from titration method were selected to do enzymatic test. Finally, the superior strains in the second stage (enzymatic which had the ability to produce L(+ lactic acid were identified by biochemical tests. Then, molecular identification of strains was performed by using 16S rRNA sequencing. Results: In this study, the ability of 79 strains of local Lactobacilli in terms of production of lactic acid was studied. The highest and lowest rates of lactic acid production was 34.8 and 12.4 mg/g. Superior Lactobacilli in terms of production of lactic acid ability of producing had an optical isomer L(+, the highest levels of L(+ lactic acid were with 3.99 and the lowest amount equal to 1.03 mg/g. The biochemical and molecular identification of superior strains showed that strains are Lactobacillus paracasei. Then the sequences of 16S rRNA of superior strains were reported in NCBI with accession numbers KF735654، KF735655، KJ508201and KJ508202. Discussion and conclusion: The amounts of lactic acid production by local Lactobacilli were very different and producing some of these strains on available reports showed more products. The results of this research suggest the use of superior strains of Lactobacilli for production of pure L(+ lactic acid.

Detection and Identification of People at a Critical Infrastructure Facilities of Trafic Buildings

Directory of Open Access Journals (Sweden)

Rastislav PIRNÍK

2014-12-01

Full Text Available This paper focuses on identification of persons entering objects of crucial infrastructure and subsequent detection of movement in parts of objects. It explains some of the technologies and approaches to processing specific image information within existing building apparatus. The article describes the proposed algorithm for detection of persons. It brings a fresh approach to detection of moving objects (groups of persons involved in enclosed areas focusing on securing freely accessible places in buildings. Based on the designed algorithm of identification with presupposed utilisation of 3D application, motion trajectory of persons in delimited space can be automatically identified. The application was created in opensource software tool using the OpenCV library.

Automatic radioxenon analyzer for CTBT monitoring

International Nuclear Information System (INIS)

Bowyer, T.W.; Abel, K.H.; Hensley, W.K.

1996-12-01

Over the past 3 years, with support from US DOE's NN-20 Comprehensive Test Ban Treaty (CTBT) R ampersand D program, PNNL has developed and demonstrated a fully automatic analyzer for collecting and measuring the four Xe radionuclides, 131m Xe(11.9 d), 133m Xe(2.19 d), 133 Xe (5.24 d), and 135 Xe(9.10 h), in the atmosphere. These radionuclides are important signatures in monitoring for compliance to a CTBT. Activity ratios permit discriminating radioxenon from nuclear detonation and that from nuclear reactor operations, nuclear fuel reprocessing, or medical isotope production and usage. In the analyzer, Xe is continuously and automatically separated from the atmosphere at flow rates of about 7 m 3 /h on sorption bed. Aliquots collected for 6-12 h are automatically analyzed by electron-photon coincidence spectrometry to produce sensitivities in the range of 20-100 μBq/m 3 of air, about 100-fold better than with reported laboratory-based procedures for short time collection intervals. Spectral data are automatically analyzed and the calculated radioxenon concentrations and raw gamma- ray spectra automatically transmitted to data centers

Semi-automatic system for UV images analysis of historical musical instruments

Science.gov (United States)

Dondi, Piercarlo; Invernizzi, Claudia; Licchelli, Maurizio; Lombardi, Luca; Malagodi, Marco; Rovetta, Tommaso

2015-06-01

The selection of representative areas to be analyzed is a common problem in the study of Cultural Heritage items. UV fluorescence photography is an extensively used technique to highlight specific surface features which cannot be observed in visible light (e.g. restored parts or treated with different materials), and it proves to be very effective in the study of historical musical instruments. In this work we propose a new semi-automatic solution for selecting areas with the same perceived color (a simple clue of similar materials) on UV photos, using a specifically designed interactive tool. The proposed method works in two steps: (i) users select a small rectangular area of the image; (ii) program automatically highlights all the areas that have the same color of the selected input. The identification is made by the analysis of the image in HSV color model, the most similar to the human perception. The achievable result is more accurate than a manual selection, because it can detect also points that users do not recognize as similar due to perception illusion. The application has been developed following the rules of usability, and Human Computer Interface has been improved after a series of tests performed by expert and non-expert users. All the experiments were performed on UV imagery of the Stradivari violins collection stored by "Museo del Violino" in Cremona.

Automatic Assessment of Global Craniofacial Differences between Crouzon mice and Wild-type mice in terms of the Cephalic Index

DEFF Research Database (Denmark)

Ólafsdóttir, Hildur; Oubel, Estanislao; Frangi, Alejandro F.

2006-01-01

of landmark matching is limited using only affine transformations, the errors were considered acceptable. The automatic estimation of the cephalic index was in full agreement with the gold standard measurements. Discriminant analysis of the three scaling parameters resulted in a good classification...

Automatic plasma control in magnetic traps

International Nuclear Information System (INIS)

Samojlenko, Y.; Chuyanov, V.

1984-01-01

Hot plasma is essentially in thermodynamic non-steady state. Automatic plasma control basically means monitoring deviations from steady state and producing a suitable magnetic or electric field which brings the plasma back to its original state. Briefly described are two systems of automatic plasma control: control with a magnetic field using a negative impedance circuit, and control using an electric field. It appears that systems of automatic plasma stabilization will be an indispensable component of the fusion reactor and its possibilities will in many ways determine the reactor economy. (Ha)

Word Processing in Dyslexics: An Automatic Decoding Deficit?

Science.gov (United States)

Yap, Regina; Van Der Leu, Aryan

1993-01-01

Compares dyslexic children with normal readers on measures of phonological decoding and automatic word processing. Finds that dyslexics have a deficit in automatic phonological decoding skills. Discusses results within the framework of the phonological deficit and the automatization deficit hypotheses. (RS)

Design and implementation of an identification system in construction site safety for proactive accident prevention.

Science.gov (United States)

Yang, Huanjia; Chew, David A S; Wu, Weiwei; Zhou, Zhipeng; Li, Qiming

2012-09-01

Identifying accident precursors using real-time identity information has great potential to improve safety performance in construction industry, which is still suffering from day to day records of accident fatality and injury. Based on the requirements analysis for identifying precursor and the discussion of enabling technology solutions for acquiring and sharing real-time automatic identification information on construction site, this paper proposes an identification system design for proactive accident prevention to improve construction site safety. Firstly, a case study is conducted to analyze the automatic identification requirements for identifying accident precursors in construction site. Results show that it mainly consists of three aspects, namely access control, training and inspection information and operation authority. The system is then designed to fulfill these requirements based on ZigBee enabled wireless sensor network (WSN), radio frequency identification (RFID) technology and an integrated ZigBee RFID sensor network structure. At the same time, an information database is also designed and implemented, which includes 15 tables, 54 queries and several reports and forms. In the end, a demonstration system based on the proposed system design is developed as a proof of concept prototype. The contributions of this study include the requirement analysis and technical design of a real-time identity information tracking solution for proactive accident prevention on construction sites. The technical solution proposed in this paper has a significant importance in improving safety performance on construction sites. Moreover, this study can serve as a reference design for future system integrations where more functions, such as environment monitoring and location tracking, can be added. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multiple Sclerosis Identification Based on Fractional Fourier Entropy and a Modified Jaya Algorithm

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Shui-Hua Wang

2018-04-01

Full Text Available Aim: Currently, identifying multiple sclerosis (MS by human experts may come across the problem of “normal-appearing white matter”, which causes a low sensitivity. Methods: In this study, we presented a computer vision based approached to identify MS in an automatic way. This proposed method first extracted the fractional Fourier entropy map from a specified brain image. Afterwards, it sent the features to a multilayer perceptron trained by a proposed improved parameter-free Jaya algorithm. We used cost-sensitivity learning to handle the imbalanced data problem. Results: The 10 × 10-fold cross validation showed our method yielded a sensitivity of 97.40 ± 0.60%, a specificity of 97.39 ± 0.65%, and an accuracy of 97.39 ± 0.59%. Conclusions: We validated by experiments that the proposed improved Jaya performs better than plain Jaya algorithm and other latest bioinspired algorithms in terms of classification performance and training speed. In addition, our method is superior to four state-of-the-art MS identification approaches.

Deliberation versus automaticity in decision making: Which presentation format features facilitate automatic decision making?

Directory of Open Access Journals (Sweden)

Anke Soellner

2013-05-01

Full Text Available The idea of automatic decision making approximating normatively optimal decisions without necessitating much cognitive effort is intriguing. Whereas recent findings support the notion that such fast, automatic processes explain empirical data well, little is known about the conditions under which such processes are selected rather than more deliberate stepwise strategies. We investigate the role of the format of information presentation, focusing explicitly on the ease of information acquisition and its influence on information integration processes. In a probabilistic inference task, the standard matrix employed in prior research was contrasted with a newly created map presentation format and additional variations of both presentation formats. Across three experiments, a robust presentation format effect emerged: Automatic decision making was more prevalent in the matrix (with high information accessibility, whereas sequential decision strategies prevailed when the presentation format demanded more information acquisition effort. Further scrutiny of the effect showed that it is not driven by the presentation format as such, but rather by the extent of information search induced by a format. Thus, if information is accessible with minimal need for information search, information integration is likely to proceed in a perception-like, holistic manner. In turn, a moderate demand for information search decreases the likelihood of behavior consistent with the assumptions of automatic decision making.

46 CFR 63.25-1 - Small automatic auxiliary boilers.

Science.gov (United States)

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Small automatic auxiliary boilers. 63.25-1 Section 63.25... AUXILIARY BOILERS Requirements for Specific Types of Automatic Auxiliary Boilers § 63.25-1 Small automatic auxiliary boilers. Small automatic auxiliary boilers defined as having heat-input ratings of 400,000 Btu/hr...

Deep Arm/Ear-ECG Image Learning for Highly Wearable Biometric Human Identification.

Science.gov (United States)

Zhang, Qingxue; Zhou, Dian

2018-01-01

In this study, to advance smart health applications which have increasing security/privacy requirements, we propose a novel highly wearable ECG-based user identification system, empowered by both non-standard convenient ECG lead configurations and deep learning techniques. Specifically, to achieve a super wearability, we suggest situating all the ECG electrodes on the left upper-arm, or behind the ears, and successfully obtain weak but distinguishable ECG waveforms. Afterwards, to identify individuals from weak ECG, we further present a two-stage framework, including ECG imaging and deep feature learning/identification. In the former stage, the ECG heartbeats are projected to a 2D state space, to reveal heartbeats' trajectory behaviors and produce 2D images by a split-then-hit method. In the second stage, a convolutional neural network is introduced to automatically learn the intricate patterns directly from the ECG image representations without heavy feature engineering, and then perform user identification. Experimental results on two acquired datasets using our wearable prototype, show a promising identification rate of 98.4% (single-arm-ECG) and 91.1% (ear-ECG), respectively. To the best of our knowledge, it is the first study on the feasibility of using single-arm-ECG/ear-ECG for user identification purpose, which is expected to contribute to pervasive ECG-based user identification in smart health applications.

Computerization of reporting and data storage using automatic coding method in the department of radiology

Energy Technology Data Exchange (ETDEWEB)

Lee, Byung Hee; Lee, Kyung Sang; Kim, Woo Ho; Han, Joon Koo; Choi, Byung Ihn; Han, Man Chung [College of Medicine, Seoul National Univ., Seoul (Korea, Republic of)

1990-10-15

The authors developed a computer program for use in printing report as well as data storage and retrieval in the Radiology department. This program used IBM PC AT and was written in dBASE III plus language. The automatic coding method of the ACR code, developed by Kim et al was applied in this program, and the framework of this program is the same as that developed for the surgical pathology department. The working sheet, which contained the name card for X-ray film identification and the results of previous radiologic studies, were printed during registration. The word precessing function was applied for issuing the formal report of radiologic study, and the data storage was carried out during the typewriting of the report. Two kinds of data files were stored in the hard disk ; the temporary file contained full information and the permanent file contained patient's identification data, and ACR code. Searching of a specific case was performed by chart number, patients name, date of study, or ACR code within a second. All the cases were arranged by ACR codes of procedure code, anatomy code, and pathology code. Every new data was copied to the diskette after daily work automatically, with which data could be restored in case of hard diskette failure. The main advantage of this program with comparison to the larger computer system is its low price. Based on the experience in the Seoul District Armed Forces General Hospital, we assume that this program provides solution to various problems in the radiology department where a large computer system with well designed software is not available.

Cross recurrence quantification for cover song identification

Energy Technology Data Exchange (ETDEWEB)

Serra, Joan; Serra, Xavier; Andrzejak, Ralph G [Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, 08018 Barcelona (Spain)], E-mail: joan.serraj@upf.edu

2009-09-15

There is growing evidence that nonlinear time series analysis techniques can be used to successfully characterize, classify, or process signals derived from real-world dynamics even though these are not necessarily deterministic and stationary. In the present study, we proceed in this direction by addressing an important problem our modern society is facing, the automatic classification of digital information. In particular, we address the automatic identification of cover songs, i.e. alternative renditions of a previously recorded musical piece. For this purpose, we here propose a recurrence quantification analysis measure that allows the tracking of potentially curved and disrupted traces in cross recurrence plots (CRPs). We apply this measure to CRPs constructed from the state space representation of musical descriptor time series extracted from the raw audio signal. We show that our method identifies cover songs with a higher accuracy as compared to previously published techniques. Beyond the particular application proposed here, we discuss how our approach can be useful for the characterization of a variety of signals from different scientific disciplines. We study coupled Roessler dynamics with stochastically modulated mean frequencies as one concrete example to illustrate this point.

Cross recurrence quantification for cover song identification

International Nuclear Information System (INIS)

Serra, Joan; Serra, Xavier; Andrzejak, Ralph G

2009-01-01

There is growing evidence that nonlinear time series analysis techniques can be used to successfully characterize, classify, or process signals derived from real-world dynamics even though these are not necessarily deterministic and stationary. In the present study, we proceed in this direction by addressing an important problem our modern society is facing, the automatic classification of digital information. In particular, we address the automatic identification of cover songs, i.e. alternative renditions of a previously recorded musical piece. For this purpose, we here propose a recurrence quantification analysis measure that allows the tracking of potentially curved and disrupted traces in cross recurrence plots (CRPs). We apply this measure to CRPs constructed from the state space representation of musical descriptor time series extracted from the raw audio signal. We show that our method identifies cover songs with a higher accuracy as compared to previously published techniques. Beyond the particular application proposed here, we discuss how our approach can be useful for the characterization of a variety of signals from different scientific disciplines. We study coupled Roessler dynamics with stochastically modulated mean frequencies as one concrete example to illustrate this point.

The Development of Automatic Sequences for the RF and Cryogenic Systems at the Spallation Neutron Source

International Nuclear Information System (INIS)

Gurd, Pamela; Casagrande, Fabio; Mccarthy, Michael; Strong, William; Ganni, Venkatarao

2005-01-01

Automatic sequences both ease the task of operating a complex machine and ensure procedural consistency. At the Spallation Neutron Source project (SNS), a set of automatic sequences have been developed to perform the start up and shut down of the high power RF systems. Similarly, sequences have been developed to perform backfill, pump down, automatic valve control and energy management in the cryogenic system. The sequences run on Linux soft input-output controllers (IOCs), which are similar to ordinary EPICS (Experimental Physics and Industrial Control System) IOCs in terms of data sharing with other EPICS processes, but which share a Linux processor with other such processors. Each sequence waits for a command from an operator console and starts the corresponding set of instructions, allowing operators to follow the sequences either from an overview screen or from detail screens. We describe each system and our operational experience with it.

49 CFR 236.825 - System, automatic train control.

Science.gov (United States)

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false System, automatic train control. 236.825 Section..., INSPECTION, MAINTENANCE, AND REPAIR OF SIGNAL AND TRAIN CONTROL SYSTEMS, DEVICES, AND APPLIANCES Definitions § 236.825 System, automatic train control. A system so arranged that its operation will automatically...

Automatic validation of numerical solutions

DEFF Research Database (Denmark)

Stauning, Ole

1997-01-01

This thesis is concerned with ``Automatic Validation of Numerical Solutions''. The basic theory of interval analysis and self-validating methods is introduced. The mean value enclosure is applied to discrete mappings for obtaining narrow enclosures of the iterates when applying these mappings...... differential equations, but in this thesis, we describe how to use the methods for enclosing iterates of discrete mappings, and then later use them for discretizing solutions of ordinary differential equations. The theory of automatic differentiation is introduced, and three methods for obtaining derivatives...... are described: The forward, the backward, and the Taylor expansion methods. The three methods have been implemented in the C++ program packages FADBAD/TADIFF. Some examples showing how to use the three metho ds are presented. A feature of FADBAD/TADIFF not present in other automatic differentiation packages...

Automaticity of walking: functional significance, mechanisms, measurement and rehabilitation strategies

Directory of Open Access Journals (Sweden)

David J Clark

2015-05-01

Full Text Available Automaticity is a hallmark feature of walking in adults who are healthy and well-functioning. In the context of walking, ‘automaticity’ refers to the ability of the nervous system to successfully control typical steady state walking with minimal use of attention-demanding executive control resources. Converging lines of evidence indicate that walking deficits and disorders are characterized in part by a shift in the locomotor control strategy from healthy automaticity to compensatory executive control. This is potentially detrimental to walking performance, as an executive control strategy is not optimized for locomotor control. Furthermore, it places excessive demands on a limited pool of executive reserves. The result is compromised ability to perform basic and complex walking tasks and heightened risk for adverse mobility outcomes including falls. Strategies for rehabilitation of automaticity are not well defined, which is due to both a lack of systematic research into the causes of impaired automaticity and to a lack of robust neurophysiological assessments by which to gauge automaticity. These gaps in knowledge are concerning given the serious functional implications of compromised automaticity. Therefore, the objective of this article is to advance the science of automaticity of walking by consolidating evidence and identifying gaps in knowledge regarding: a functional significance of automaticity; b neurophysiology of automaticity; c measurement of automaticity; d mechanistic factors that compromise automaticity; and e strategies for rehabilitation of automaticity.

The Use of Automatic Indexing for Authority Control.

Science.gov (United States)

Dillon, Martin; And Others

1981-01-01

Uses an experimental system for authority control on a collection of bibliographic records to demonstrate the resemblance between thesaurus-based automatic indexing and automatic authority control. Details of the automatic indexing system are given, results discussed, and the benefits of the resemblance examined. Included are a rules appendix and…

30 CFR 77.1401 - Automatic controls and brakes.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic controls and brakes. 77.1401 Section... MINES Personnel Hoisting § 77.1401 Automatic controls and brakes. Hoists and elevators shall be equipped with overspeed, overwind, and automatic stop controls and with brakes capable of stopping the elevator...

30 CFR 57.19006 - Automatic hoist braking devices.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic hoist braking devices. 57.19006 Section 57.19006 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND... Hoisting Hoists § 57.19006 Automatic hoist braking devices. Automatic hoists shall be provided with devices...

30 CFR 56.19006 - Automatic hoist braking devices.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Automatic hoist braking devices. 56.19006 Section 56.19006 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND... Hoisting Hoists § 56.19006 Automatic hoist braking devices. Automatic hoists shall be provided with devices...

Development of the automatic control rod operation system for JOYO. Verification of automatic control rod operation guide system

International Nuclear Information System (INIS)

Terakado, Tsuguo; Suzuki, Shinya; Kawai, Masashi; Aoki, Hiroshi; Ohkubo, Toshiyuki

1999-10-01

The automatic control rod operation system was developed to control the JOYO reactor power automatically in all operation modes(critical approach, cooling system heat up, power ascent, power descent), development began in 1989. Prior to applying the system, verification tests of the automatic control rod operation guide system was conducted during 32nd duty cycles of JOYO' from Dec. 1997 to Feb. 1998. The automatic control rod operation guide system consists of the control rod operation guide function and the plant operation guide function. The control rod operation guide function provides information on control rod movement and position, while the plant operation guide function provide guidance for plant operations corresponding to reactor power changes(power ascent or power descent). Control rod insertion or withdrawing are predicted by fuzzy algorithms. (J.P.N.)

Robust uncertainty evaluation for system identification on distributed wireless platforms

Science.gov (United States)

Crinière, Antoine; Döhler, Michael; Le Cam, Vincent; Mevel, Laurent

2016-04-01

Health monitoring of civil structures by system identification procedures from automatic control is now accepted as a valid approach. These methods provide frequencies and modeshapes from the structure over time. For a continuous monitoring the excitation of a structure is usually ambient, thus unknown and assumed to be noise. Hence, all estimates from the vibration measurements are realizations of random variables with inherent uncertainty due to (unknown) process and measurement noise and finite data length. The underlying algorithms are usually running under Matlab under the assumption of large memory pool and considerable computational power. Even under these premises, computational and memory usage are heavy and not realistic for being embedded in on-site sensor platforms such as the PEGASE platform. Moreover, the current push for distributed wireless systems calls for algorithmic adaptation for lowering data exchanges and maximizing local processing. Finally, the recent breakthrough in system identification allows us to process both frequency information and its related uncertainty together from one and only one data sequence, at the expense of computational and memory explosion that require even more careful attention than before. The current approach will focus on presenting a system identification procedure called multi-setup subspace identification that allows to process both frequencies and their related variances from a set of interconnected wireless systems with all computation running locally within the limited memory pool of each system before being merged on a host supervisor. Careful attention will be given to data exchanges and I/O satisfying OGC standards, as well as minimizing memory footprints and maximizing computational efficiency. Those systems are built in a way of autonomous operations on field and could be later included in a wide distributed architecture such as the Cloud2SM project. The usefulness of these strategies is illustrated on

Developing a Speaker Identification System for the DARPA RATS Project