Idaho Explosives Detection System

International Nuclear Information System (INIS)

Reber, Edward L.; Blackwood, Larry G.; Edwards, Andrew J.; Jewell, J. Keith; Rohde, Kenneth W.; Seabury, Edward H.; Klinger, Jeffery B.

2005-01-01

The Idaho Explosives Detection System was developed at the Idaho National Laboratory (INL) to respond to threats imposed by delivery trucks potentially carrying explosives into military bases. A full-scale prototype system has been built and is currently undergoing testing. The system consists of two racks, one on each side of a subject vehicle. Each rack includes a neutron generator and an array of NaI detectors. The two neutron generators are pulsed and synchronized. A laptop computer controls the entire system. The control software is easily operable by minimally trained staff. The system was developed to detect explosives in a medium size truck within a 5-min measurement time. System performance was successfully demonstrated with explosives at the INL in June 2004 and at Andrews Air Force Base in July 2004

Idaho Explosives Detection System

Energy Technology Data Exchange (ETDEWEB)

Reber, Edward L. [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States)]. E-mail: reber@inel.gov; Blackwood, Larry G. [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States); Edwards, Andrew J. [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States); Jewell, J. Keith [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States); Rohde, Kenneth W. [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States); Seabury, Edward H. [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States); Klinger, Jeffery B. [Idaho National Laboratory, 2525 N. Freemont Ave., Idaho Falls, ID 83415-2114 (United States)

2005-12-15

The Idaho Explosives Detection System was developed at the Idaho National Laboratory (INL) to respond to threats imposed by delivery trucks potentially carrying explosives into military bases. A full-scale prototype system has been built and is currently undergoing testing. The system consists of two racks, one on each side of a subject vehicle. Each rack includes a neutron generator and an array of NaI detectors. The two neutron generators are pulsed and synchronized. A laptop computer controls the entire system. The control software is easily operable by minimally trained staff. The system was developed to detect explosives in a medium size truck within a 5-min measurement time. System performance was successfully demonstrated with explosives at the INL in June 2004 and at Andrews Air Force Base in July 2004.

Advanced training systems

Science.gov (United States)

Savely, Robert T.; Loftin, R. Bowen

1990-01-01

Training is a major endeavor in all modern societies. Common training methods include training manuals, formal classes, procedural computer programs, simulations, and on-the-job training. NASA's training approach has focussed primarily on on-the-job training in a simulation environment for both crew and ground based personnel. NASA must explore new approaches to training for the 1990's and beyond. Specific autonomous training systems are described which are based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground based support personnel that show an alternative to current training systems. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer Aided Training (ICAT) systems would provide much of the same experience that could be gained from the best on-the-job training.

Computer-aided detection of masses in full-field digital mammography using screen-film mammograms for training

International Nuclear Information System (INIS)

Kallenberg, Michiel; Karssemeijer, Nico

2008-01-01

It would be of great value when available databases of screen-film mammography (SFM) images can be used to train full-field digital mammography (FFDM) computer-aided detection (CAD) systems, as compilation of new databases is costly. In this paper, we investigate this possibility. Firstly, we develop a method that converts an FFDM image into an SFM-like representation. In this conversion method, we establish a relation between exposure and optical density by simulation of an automatic exposure control unit. Secondly, we investigate the effects of using the SFM images as training samples compared to training with FFDM images. Our FFDM database consisted of 266 cases, of which 102 were biopsy-proven malignant masses and 164 normals. The images were acquired with systems of two different manufacturers. We found that, when we trained our FFDM CAD system with a small number of images, training with FFDM images, using a five-fold crossvalidation procedure, outperformed training with SFM images. However, when the full SFM database, consisting of 348 abnormal cases (including 204 priors) and 810 normal cases, was used for training, SFM training outperformed FFDMA training. These results show that an existing CAD system for detection of masses in SFM can be used for FFDM images without retraining.

Adaptive skin detection based on online training

Science.gov (United States)

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

2007-11-01

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

Can surgical simulation be used to train detection and classification of neural networks?

Science.gov (United States)

Zisimopoulos, Odysseas; Flouty, Evangello; Stacey, Mark; Muscroft, Sam; Giataganas, Petros; Nehme, Jean; Chow, Andre; Stoyanov, Danail

2017-10-01

Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors' knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems.

Detection of Illicit Drugs by Trained Honeybees (Apis mellifera.

Directory of Open Access Journals (Sweden)

Matthias Schott

Full Text Available Illegal drugs exacerbate global social challenges such as substance addiction, mental health issues and violent crime. Police and customs officials often rely on specially-trained sniffer dogs, which act as sensitive biological detectors to find concealed illegal drugs. However, the dog "alert" is no longer sufficient evidence to allow a search without a warrant or additional probable cause because cannabis has been legalized in two US states and is decriminalized in many others. Retraining dogs to recognize a narrower spectrum of drugs is difficult and training new dogs is time consuming, yet there are no analytical devices with the portability and sensitivity necessary to detect substance-specific chemical signatures. This means there is currently no substitute for sniffer dogs. Here we describe an insect screening procedure showing that the western honeybee (Apis mellifera can sense volatiles associated with pure samples of heroin and cocaine. We developed a portable electroantennographic device for the on-site measurement of volatile perception by these insects, and found a positive correlation between honeybee antennal responses and the concentration of specific drugs in test samples. Furthermore, we tested the ability of honeybees to learn the scent of heroin and trained them to show a reliable behavioral response in the presence of a highly-diluted scent of pure heroin. Trained honeybees could therefore be used to complement or replace the role of sniffer dogs as part of an automated drug detection system. Insects are highly sensitive to volatile compounds and provide an untapped resource for the development of biosensors. Automated conditioning as presented in this study could be developed as a platform for the practical detection of illicit drugs using insect-based sensors.

Detection of Illicit Drugs by Trained Honeybees (Apis mellifera).

Science.gov (United States)

Schott, Matthias; Klein, Birgit; Vilcinskas, Andreas

2015-01-01

Illegal drugs exacerbate global social challenges such as substance addiction, mental health issues and violent crime. Police and customs officials often rely on specially-trained sniffer dogs, which act as sensitive biological detectors to find concealed illegal drugs. However, the dog "alert" is no longer sufficient evidence to allow a search without a warrant or additional probable cause because cannabis has been legalized in two US states and is decriminalized in many others. Retraining dogs to recognize a narrower spectrum of drugs is difficult and training new dogs is time consuming, yet there are no analytical devices with the portability and sensitivity necessary to detect substance-specific chemical signatures. This means there is currently no substitute for sniffer dogs. Here we describe an insect screening procedure showing that the western honeybee (Apis mellifera) can sense volatiles associated with pure samples of heroin and cocaine. We developed a portable electroantennographic device for the on-site measurement of volatile perception by these insects, and found a positive correlation between honeybee antennal responses and the concentration of specific drugs in test samples. Furthermore, we tested the ability of honeybees to learn the scent of heroin and trained them to show a reliable behavioral response in the presence of a highly-diluted scent of pure heroin. Trained honeybees could therefore be used to complement or replace the role of sniffer dogs as part of an automated drug detection system. Insects are highly sensitive to volatile compounds and provide an untapped resource for the development of biosensors. Automated conditioning as presented in this study could be developed as a platform for the practical detection of illicit drugs using insect-based sensors.

System and Method for Outlier Detection via Estimating Clusters

Science.gov (United States)

Iverson, David J. (Inventor)

2016-01-01

An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

A feasibility study of stateful automaton packet inspection for streaming application detection systems

Science.gov (United States)

Tseng, Kuo-Kun; Lo, Jiao; Liu, Yiming; Chang, Shih-Hao; Merabti, Madjid; Ng, Felix, C. K.; Wu, C. H.

2017-10-01

The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.

The effects of virtual reality displays on visual attention and detection of signals performance for main control room training

International Nuclear Information System (INIS)

Lin Shiaufeng; Lin Chiuhsiang Joe; Wang Rouwen; Yang Lichen; Yang Chihwei; Cheng Tsungchieh; Wang Jyhgang

2011-01-01

The nuclear power plant (NPP) mainly serve the purpose to provide low-cost and stable electricity for the people, but this purpose must be dependent upon the premise of 'safety first.' The reason for this is that the occurrence of nuclear power plant accidents could cause catastrophic damage to the people, property, society, and the environment. Therefore, training in superior and high reliability system is very important in accident prevention. In recent years, the Virtual Reality (VR) technology advances very fast as well as the technology for e-learning environment. VR systems have been applied for education, safety training of NPP and flying simulators. In particular, VR is an interactive and reactive technology; it allows users to interact and navigate with objects in the virtual environment. Development of VR and simulation techniques contributes to an accurate and immersive training environment for NPP operators. Main Control Room (MCR) training simulator based on VR is a more cost effective and efficient alternative to traditional simulator based training methods. The VR simulation for MCR training is a complex task. Since VR not only reinforces the visual presentation of the training materials but also provides ways to interact with the training system, it becomes more flexible and possibly more powerful in the training system. In the VR training system, the MCR operators may use just one display to view the wide range of the real world displays. The field of view (FOV) will be different from the real MCR environment in which many displays exist for the operators to view. Thus operator's immersion and visual attention will be reduced. This is the problem of MCR virtual training compared with the traditional simulator based training systems. Therefore, improving the operator's visual attention and the detection of signals in VR training system is a very important issue. This investigation intends to contribute in assessing benefits of visual attention and

System tuning and measurement error detection testing

International Nuclear Information System (INIS)

Krejci, Petr; Machek, Jindrich

2008-09-01

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

Research on the Filtering Algorithm in Speed and Position Detection of Maglev Trains

Directory of Open Access Journals (Sweden)

Chunhui Dai

2011-07-01

Full Text Available This paper introduces in brief the traction system of a permanent magnet electrodynamic suspension (EDS train. The synchronous traction mode based on long stators and track cable is described. A speed and position detection system is recommended. It is installed on board and is used as the feedback end. Restricted by the maglev train’s structure, the permanent magnet electrodynamic suspension (EDS train uses the non-contact method to detect its position. Because of the shake and the track joints, the position signal sent by the position sensor is always aberrant and noisy. To solve this problem, a linear discrete track-differentiator filtering algorithm is proposed. The filtering characters of the track-differentiator (TD and track-differentiator group are analyzed. The four series of TD are used in the signal processing unit. The result shows that the track-differentiator could have a good effect and make the traction system run normally.

A Cage-Based Training System for Non-Human Primates

Directory of Open Access Journals (Sweden)

Michaela D Curry

2017-07-01

Full Text Available Non-human primates (NHPs are widely-used experimental models in neurophysiological studies. Training on cognitive tasks prior to collecting neurophysiological data is an inseparable part of much of the research conducted using NHPs. Any improvement in the training method that reduces stress to the animal, increases the speed of training or improves performance on the task is of great potential value. We have designed, built and successfully utilized a fully portable cage-mountable system to train rhesus monkeys (Macaca mulatta. The flexibility and portability of both the animal interface and the control unit of this system would allow it to be used for a large variety of behavioral paradigms. Aside from experimental use, our system could potentially be used as a source of animal enrichment. We present the behavioral data collected using this method to train a visual working memory and a change detection task. Utilizing the in-cage training system allows the animal greater control over when and how long it chooses to work, rather than imposing a training schedule based on the availability of the experimenter. Using this method the animal learned to perform both behavioral tasks in a short amount of time. In some cases the animal would use the training system without the need for any water restriction. In addition to allowing voluntary, self-paced engagement with the task, this method has the advantage of being less disruptive to the monkey's social interactions, and presumably eliminating some of the stress occasioned by relocating for chair training. Although this system has the potential to ease and expedite the behavioral training of NHPs on a variety of tasks, here we provide only a demonstration of our cage-based training system using one NHP.

Integrated training support system for PWR operator training simulator

International Nuclear Information System (INIS)

Sakaguchi, Junichi; Komatsu, Yasuki

1999-01-01

The importance of operator training using operator training simulator has been recognized intensively. Since 1986, we have been developing and providing many PWR simulators in Japan. We also have developed some training support systems connected with the simulator and the integrated training support system to improve training effect and to reduce instructor's workload. This paper describes the concept and the effect of the integrated training support system and of the following sub-systems. We have PES (Performance Enhancement System) that evaluates training performance automatically by analyzing many plant parameters and operation data. It can reduce the deviation of training performance evaluation between instructors. PEL (Parameter and Event data Logging system), that is the subset of PES, has some data-logging functions. And we also have TPES (Team Performance Enhancement System) that is used aiming to improve trainees' ability for communication between operators. Trainee can have conversation with virtual trainees that TPES plays automatically. After that, TPES automatically display some advice to be improved. RVD (Reactor coolant system Visual Display) displays the distributed hydraulic-thermal condition of the reactor coolant system in real-time graphically. It can make trainees understand the inside plant condition in more detail. These sub-systems have been used in a training center and have contributed the improvement of operator training and have gained in popularity. (author)

Road Anomalies Detection System Evaluation.

Science.gov (United States)

Silva, Nuno; Shah, Vaibhav; Soares, João; Rodrigues, Helena

2018-06-21

Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.

An FPGA-Based People Detection System

Directory of Open Access Journals (Sweden)

James J. Clark

2005-05-01

Full Text Available This paper presents an FPGA-based system for detecting people from video. The system is designed to use JPEG-compressed frames from a network camera. Unlike previous approaches that use techniques such as background subtraction and motion detection, we use a machine-learning-based approach to train an accurate detector. We address the hardware design challenges involved in implementing such a detector, along with JPEG decompression, on an FPGA. We also present an algorithm that efficiently combines JPEG decompression with the detection process. This algorithm carries out the inverse DCT step of JPEG decompression only partially. Therefore, it is computationally more efficient and simpler to implement, and it takes up less space on the chip than the full inverse DCT algorithm. The system is demonstrated on an automated video surveillance application and the performance of both hardware and software implementations is analyzed. The results show that the system can detect people accurately at a rate of about 2.5 frames per second on a Virtex-II 2V1000 using a MicroBlaze processor running at 75 MHz, communicating with dedicated hardware over FSL links.

An intention driven hand functions task training robotic system.

Science.gov (United States)

Tong, K Y; Ho, S K; Pang, P K; Hu, X L; Tam, W K; Fung, K L; Wei, X J; Chen, P N; Chen, M

2010-01-01

A novel design of a hand functions task training robotic system was developed for the stroke rehabilitation. It detects the intention of hand opening or hand closing from the stroke person using the electromyography (EMG) signals measured from the hemiplegic side. This training system consists of an embedded controller and a robotic hand module. Each hand robot has 5 individual finger assemblies capable to drive 2 degrees of freedom (DOFs) of each finger at the same time. Powered by the linear actuator, the finger assembly achieves 55 degree range of motion (ROM) at the metacarpophalangeal (MCP) joint and 65 degree range of motion (ROM) at the proximal interphalangeal (PIP) joint. Each finger assembly can also be adjusted to fit for different finger length. With this task training system, stroke subject can open and close their impaired hand using their own intention to carry out some of the daily living tasks.

Hybrid feature selection for supporting lightweight intrusion detection systems

Science.gov (United States)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

Training organizational supervisors to detect and prevent cyber insider threats: two approaches

Directory of Open Access Journals (Sweden)

Dee H. Andrews

2013-05-01

Full Text Available Cyber insider threat is intentional theft from, or sabotage of, a cyber system by someone within the organization. This article explores the use of advanced cognitive and instructional principles to accelerate learning in organizational supervisors to mitigate the cyber threat. It examines the potential advantage of using serious games to engage supervisors. It also posits two systematic instructional approaches for this training challenge – optimal path modelling and a competency-based approach. The paper concludes by discussing challenges of evaluating training for seldom occurring real world phenomena, like detecting a cyber-insider threat.

Early Wheel Train Damage Detection Using Wireless Sensor Network Antenna

Science.gov (United States)

Fazilah, A. F. M.; Azemi, S. N.; Azremi, A. A. H.; Soh, P. J.; Kamarudin, L. M.

2018-03-01

Antenna for a wireless sensor network for early wheel trains damage detection has successfully developed and fabricated with the aim to minimize the risk and increase the safety guaranty for train. Current antenna design is suffered in gain and big in size. For the sensor, current existing sensor only detect when the wheel malfunction. Thus, a compact microstrip patch antenna with operating frequency at 2.45GHz is design with high gain of 4.95dB will attach to the wireless sensor device. Simulation result shows that the antenna is working at frequency 2.45GHz and the return loss at -34.46dB are in a good agreement. The result also shows the good radiation pattern and almost ideal VSWR which is 1.04. The Arduino Nano, LM35DZ and ESP8266-07 Wi-Fi module is applied to the core system with capability to sense the temperature and send the data wirelessly to the cloud. An android application has been created to monitor the temperature reading based on the real time basis. The mainly focuses for the future improvement is by minimize the size of the antenna in order to make in more compact. In addition, upgrade an android application that can collect the raw data from cloud and make an alarm system to alert the loco pilot.

Robust nonhomogeneous training samples detection method for space-time adaptive processing radar using sparse-recovery with knowledge-aided

Science.gov (United States)

Li, Zhihui; Liu, Hanwei; Zhang, Yongshun; Guo, Yiduo

2017-10-01

The performance of space-time adaptive processing (STAP) may degrade significantly when some of the training samples are contaminated by the signal-like components (outliers) in nonhomogeneous clutter environments. To remove the training samples contaminated by outliers in nonhomogeneous clutter environments, a robust nonhomogeneous training samples detection method using the sparse-recovery (SR) with knowledge-aided (KA) is proposed. First, the reduced-dimension (RD) overcomplete spatial-temporal steering dictionary is designed with the prior knowledge of system parameters and the possible target region. Then, the clutter covariance matrix (CCM) of cell under test is efficiently estimated using a modified focal underdetermined system solver (FOCUSS) algorithm, where a RD overcomplete spatial-temporal steering dictionary is applied. Third, the proposed statistics are formed by combining the estimated CCM with the generalized inner products (GIP) method, and the contaminated training samples can be detected and removed. Finally, several simulation results validate the effectiveness of the proposed KA-SR-GIP method.

The ALICE analysis train system

CERN Document Server

Zimmermann, Markus

2015-01-01

In the ALICE experiment hundreds of users are analyzing big datasets on a Grid system. High throughput and short turn-around times are achieved by a centralized system called the LEGO trains. This system combines analysis from different users in so-called analysis trains which are then executed within the same Grid jobs thereby reducing the number of times the data needs to be read from the storage systems. The centralized trains improve the performance, the usability for users and the bookkeeping in comparison to single user analysis. The train system builds upon the already existing ALICE tools, i.e. the analysis framework as well as the Grid submission and monitoring infrastructure. The entry point to the train system is a web interface which is used to configure the analysis and the desired datasets as well as to test and submit the train. Several measures have been implemented to reduce the time a train needs to finish and to increase the CPU efficiency.

Education and training support system

International Nuclear Information System (INIS)

Kubota, Rhuji; Iyadomi, Motomi.

1996-01-01

In order to train the specialist such as operator or maintenance stuff of large scale plant such as nuclear power plant or thermal power plant, a high grade teaching and training support system is required as well as in training pilot of aeroplane. The specialist in such large scale plant is also a researcher in the field of machinery, electricity and physics at first, and is grown up a expert operator or maintenance stuff through learning of CAI system or OTJ used training material for teaching tool in addition of training used operating or maintenance training device imitating actual plant after acquiring determined knowledges by receiving fundamental education on nuclear and thermal power plants. In this paper, the teaching and training support systems of the nuclear and thermal power plants for a system supporting such teaching and training, respectively, were introduced. (G.K.)

Radiologists' Training, Experience, and Attitudes About Elder Abuse Detection.

Science.gov (United States)

Rosen, Tony; Bloemen, Elizabeth M; Harpe, Jasmin; Sanchez, Allen M; Mennitt, Kevin W; McCarthy, Thomas J; Nicola, Refky; Murphy, Kieran; LoFaso, Veronica M; Flomenbaum, Neal; Lachs, Mark S

2016-12-01

Elder abuse is underrecognized, and identification of subtle cases requires a high index of suspicion among all health care providers. Because many geriatric injury victims undergo radiographic imaging, diagnostic radiologists may be well positioned to identify injury patterns suggestive of abuse. Little is known about radiologists' experience with elder abuse. Our goal was to describe knowledge, attitudes, training, and practice experience in elder abuse detection among diagnostic radiologists. We conducted 19 interviews with diagnostic radiologists at a large urban academic medical center using a semistructured format. Data from these sessions were coded and analyzed to identify themes. Only two radiologists reported any formal or informal training in elder abuse detection. All subjects believed they had missed cases of elder abuse. Even experienced radiologists reported never having received a request from a referring physician to assess images for evidence suggestive of elder abuse. All subjects reported a desire for additional elder abuse training. Also, subjects identified radiographic findings or patterns potentially suggestive of elder abuse, including high-energy injuries such as upper rib fractures, injuries in multiple stages of healing, and injuries inconsistent with reported mechanism. Radiologists are uniquely positioned to identify elder abuse. Though training in detection is currently lacking, providers expressed a desire for increased knowledge. In addition, radiologists were able to identify radiographic findings suggestive of elder abuse. On the basis of these findings, we plan to conduct additional studies to define pathognomonic injury patterns and to explore how to empower radiologists to incorporate detection into their practice.

Radiologists’ Training, Experience, and Attitudes About Elder Abuse Detection

Science.gov (United States)

Rosen, Tony; Bloemen, Elizabeth M.; Harpe, Jasmin; Sanchez, Allen M.; Mennitt, Kevin W.; McCarthy, Thomas J.; Nicola, Refky; Murphy, Kieran; LoFaso, Veronica M.; Flomenbaum, Neal; Lachs, Mark S.

2017-01-01

OBJECTIVE Elder abuse is underrecognized, and identification of subtle cases requires a high index of suspicion among all health care providers. Because many geriatric injury victims undergo radiographic imaging, diagnostic radiologists may be well positioned to identify injury patterns suggestive of abuse. Little is known about radiologists’ experience with elder abuse. Our goal was to describe knowledge, attitudes, training, and practice experience in elder abuse detection among diagnostic radiologists. SUBJECTS AND METHODS We conducted 19 interviews with diagnostic radiologists at a large urban academic medical center using a semistructured format. Data from these sessions were coded and analyzed to identify themes. RESULTS Only two radiologists reported any formal or informal training in elder abuse detection. All subjects believed they had missed cases of elder abuse. Even experienced radiologists reported never having received a request from a referring physician to assess images for evidence suggestive of elder abuse. All subjects reported a desire for additional elder abuse training. Also, subjects identified radiographic findings or patterns potentially suggestive of elder abuse, including high-energy injuries such as upper rib fractures, injuries in multiple stages of healing, and injuries inconsistent with reported mechanism. CONCLUSION Radiologists are uniquely positioned to identify elder abuse. Though training in detection is currently lacking, providers expressed a desire for increased knowledge. In addition, radiologists were able to identify radiographic findings suggestive of elder abuse. On the basis of these findings, we plan to conduct additional studies to define pathognomonic injury patterns and to explore how to empower radiologists to incorporate detection into their practice. PMID:27732066

Moving Sources Detection System

International Nuclear Information System (INIS)

Coulon, Romain; Kondrasovs, Vladimir; Boudergui, Karim; Normand, Stephane

2013-06-01

To monitor radioactivity passing through a pipe or in a given container such as a train or a truck, radiation detection systems are commonly employed. These detectors could be used in a network set along the source track to increase the overall detection efficiency. However detection methods are based on counting statistics analysis. The method usually implemented consists in trigging an alarm when an individual signal rises over a threshold initially estimated in regards to the natural background signal. The detection efficiency is then proportional to the number of detectors in use, due to the fact that each sensor is taken as a standalone sensor. A new approach is presented in this paper taking into account the temporal periodicity of the signals taken by all distributed sensors as a whole. This detection method is not based only on counting statistics but also on the temporal series analysis aspect. Therefore, a specific algorithm is then developed in our lab for this kind of applications and shows a significant improvement, especially in terms of detection efficiency and false alarms reduction. We also plan on extracting information from the source vector. This paper presents the theoretical approach and some preliminary results obtain in our laboratory. (authors)

Ionizing radiation detection meter systems usability evaluation. Technical memorandum

International Nuclear Information System (INIS)

Severs, Y.; Hughes, R.; Tack, D.; Bossi, L.L.M.

2002-12-01

In support of the Canadian Forces Nuclear Detection, Identification and Dosimetry project a usability trial of three Ionizing Radiation Detection Meter Systems (IRDMS) was conducted 18-22 June 2001 at Connaught Ranges. The systems evaluated: System 1: ANPDR 77 Operational System with PDR 77 Alpha/Beta probes and GPS (Global Positioning System) Training System; System 2: ADM 300C Operational System with ABP 100 Alpha/Beta probes and GPS Training System, and System 3: RAM R200 Operational System with PA 100M and RG12 Alpha/Beta probes and GPS Training System. Twelve military personnel (Private to Captain) determined compliance with the bid evaluation criteria. The counter-balanced study, based on a Latin square design, was divided into two assessment phases, an operational phase and a training system phase, which rotated three groups (of four participants each) concurrently through each IRDMS. Groups were trained in set-up, maintenance and operation of each bid IRDMS prior to evaluation. The operational evaluation consisted of a test/maintenance stand, an indoor/outdoor operational stand, and an indoor,/outdoor training system stand. Participants rated the utility and usability of each system, by measuring case of use/maintenance under a range of relevant operational and clothing conditions, compatibility with soldier tasks, compatibility with clothing, compatibility with equipment and operational environments, and case of learning (including an assessment of initial and refresher training implications). A 7-point Likert-like acceptability rating scale, which covered a range from completely unacceptable (1) to completely acceptable (7), was used to evaluate the measures. The combined weighted mean scores were 584.3 for System 1 (70 o /b), 682.0 for System 2 (81 %) and 756.9 for System 3 (90%) out of a total possible score of 840. Participants reported mean scores for System 1 between barely unacceptable and borderline for both indoor and outdoor operations. System 2

Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.

Science.gov (United States)

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu

2017-10-01

We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing.

Training Requirements and Training Delivery in the Total Army School System

National Research Council Canada - National Science Library

Winkler, John

1999-01-01

This report analyzes training requirements and school delivery of training in the Total Army School System, focusing on the system's ability to meet its training requirements in Reserve Component Training Institutions...

Sustainable training for customs officer involved in illicit nuclear trafficking detection: national solutions

International Nuclear Information System (INIS)

Paredes Gilisman, Jorge Luis; Lopez Forteza, Yamil

2008-01-01

Full text: The illicit nuclear trafficking detection capabilities demand adequate training, cooperation and equipment. Often customs personnel changing takes place in our countries. A sustainable training strategy should be implemented for avoiding forfeit on detection capabilities. Cuba, not excluded from this particular, designed an Action Plan to provide Customs authorities with basic tools for their own training. The Nuclear Regulatory Authority developed three main addresses: initial training, development of e-tools and preparation of train-of-trainers. Experiences, outcomes and challenges are shown in the present paper. In a simple, quick and not expensive way answer has been given to a national sustainable training strategy. (author)

Novel vehicle detection system based on stacked DoG kernel and AdaBoost

Science.gov (United States)

Kang, Hyun Ho; Lee, Seo Won; You, Sung Hyun

2018-01-01

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)–based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles—of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions. PMID:29513727

Automated detection of heuristics and biases among pathologists in a computer-based system.

Science.gov (United States)

Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

2013-08-01

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.

Automatically controlled training systems

International Nuclear Information System (INIS)

Milashenko, A.; Afanasiev, A.

1990-01-01

This paper reports that the computer system for NPP personnel training was developed for training centers in the Soviet Union. The system should be considered as the first step in training, taking into account that further steps are to be devoted to part-task and full scope simulator training. The training room consists of 8-12 IBM PC/AT personal computers combined into a network. A trainee accesses the system in a dialor manner. Software enables the instructor to determine the trainee's progress in different subjects of the program. The quality of any trainee preparedness may be evaluated by Knowledge Control operation. Simplified dynamic models are adopted for separate areas of the program. For example, the system of neutron flux monitoring has a dedicated model. Currently, training, requalification and support of professional qualifications of nuclear power plant operators is being emphasized. A significant number of emergency situations during work are occurring due to operator errors. Based on data from September-October 1989, more than half of all unplanned drops in power and stoppages of power plants were due to operator error. As a comparison, problems due to equipment malfunction accounted for no more than a third of the total. The role of personnel, especially of the operators, is significant during normal operations, since energy production costs as well as losses are influenced by the capability of the staff. These facts all point to the importance of quality training of personnel

The effect of internal audit effectiveness, auditor responsibility and training in fraud detection

Directory of Open Access Journals (Sweden)

George Drogalas

2017-12-01

Full Text Available The purpose of this study is to explore the relationship between internal audit effectiveness, internal auditor’s responsibility, training and fraud detection. During the last decade internal auditing has become an integral part of modern businesses since it is capable of detecting errors or offences which lead to fraud. In order to investigate the above relationship, we conducted a survey of companies listed in the Athens Stock Exchange. We used factor analysis to validate the survey instrument and to construct our variables measuring fraud detection, internal audit effectiveness, auditor responsibility and training. We used regression analysis to test for significance between the constructed variables. Our analysis shows that audit effectiveness, auditor responsibility and auditor training affect positively and significantly the detection of fraud. Our results highlight the importance of internal audit in detecting accounting fraud and the need of companies to invest on internal audit processes and training in order to achieve enhanced corporate performance. Finally, our research stresses the importance of internal audit and fraud detection for companies which operate in countries which are in a period of economic crisis.

Basis scheme of personnel training system

International Nuclear Information System (INIS)

Rerucha, F.; Odehnal, J.

1998-01-01

Basic scheme of the training system for NPP personnel of CEZ-EDU personnel training system is described in detail. This includes: specific training both basic and periodic, and professional training meaning specialized and continuous training. The following schemes are shown: licence acquisition and authorisation for PWR-440 Control Room Personnel; upgrade training for job positions of Control Room personnel; maintaining and refresh training; module training for certificate acquisition of servicing shift and operating personnel

Systems and methods for selective detection and imaging in coherent Raman microscopy by spectral excitation shaping

Science.gov (United States)

Xie, Xiaoliang Sunney; Freudiger, Christian; Min, Wei

2016-03-15

A microscopy imaging system is disclosed that includes a light source system, a spectral shaper, a modulator system, an optics system, an optical detector and a processor. The light source system is for providing a first train of pulses and a second train of pulses. The spectral shaper is for spectrally modifying an optical property of at least some frequency components of the broadband range of frequency components such that the broadband range of frequency components is shaped producing a shaped first train of pulses to specifically probe a spectral feature of interest from a sample, and to reduce information from features that are not of interest from the sample. The modulator system is for modulating a property of at least one of the shaped first train of pulses and the second train of pulses at a modulation frequency. The optical detector is for detecting an integrated intensity of substantially all optical frequency components of a train of pulses of interest transmitted or reflected through the common focal volume. The processor is for detecting a modulation at the modulation frequency of the integrated intensity of substantially all of the optical frequency components of the train of pulses of interest due to the non-linear interaction of the shaped first train of pulses with the second train of pulses as modulated in the common focal volume, and for providing an output signal for a pixel of an image for the microscopy imaging system.

Anomaly detection in an automated safeguards system using neural networks

International Nuclear Information System (INIS)

Whiteson, R.; Howell, J.A.

1992-01-01

An automated safeguards system must be able to detect an anomalous event, identify the nature of the event, and recommend a corrective action. Neural networks represent a new way of thinking about basic computational mechanisms for intelligent information processing. In this paper, we discuss the issues involved in applying a neural network model to the first step of this process: anomaly detection in materials accounting systems. We extend our previous model to a 3-tank problem and compare different neural network architectures and algorithms. We evaluate the computational difficulties in training neural networks and explore how certain design principles affect the problems. The issues involved in building a neural network architecture include how the information flows, how the network is trained, how the neurons in a network are connected, how the neurons process information, and how the connections between neurons are modified. Our approach is based on the demonstrated ability of neural networks to model complex, nonlinear, real-time processes. By modeling the normal behavior of the processes, we can predict how a system should be behaving and, therefore, detect when an abnormality occurs

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

Science.gov (United States)

Horowitz-Kraus, Tzipi

2016-05-01

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

A case-oriented web-based training system for breast cancer diagnosis.

Science.gov (United States)

Huang, Qinghua; Huang, Xianhai; Liu, Longzhong; Lin, Yidi; Long, Xingzhang; Li, Xuelong

2018-03-01

Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. We aim to provide a web-based breast ultrasound database for online training inexperienced radiologists and giving computer-assisted diagnostic information for detection and classification of the breast tumor. We introduce a web database which stores breast ultrasound images from breast cancer patients as well as their diagnostic information. A web-based training system using a feature scoring scheme based on Breast Imaging Reporting and Data System (BI-RADS) US lexicon was designed. A computer-aided diagnosis (CAD) subsystem was developed to assist the radiologists to make scores on the BI-RADS features for an input case. The training system possesses 1669 scored cases, where 412 cases are benign and 1257 cases are malignant. It was tested by 31 users including 12 interns, 11 junior radiologists, and 8 experienced senior radiologists. This online training system automatically creates case-based exercises to train and guide the newly employed or resident radiologists for the diagnosis of breast cancer using breast ultrasound images based on the BI-RADS. After the trainings, the interns and junior radiologists show significant improvement in the diagnosis of the breast tumor with ultrasound imaging (p-value  .05). The online training system can improve the capabilities of early-career radiologists in distinguishing between the benign and malignant lesions and reduce the misdiagnosis of breast cancer in a quick, convenient and effective manner. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Adenoma detection rate varies greatly during colonoscopy training

NARCIS (Netherlands)

van Doorn, Sascha C.; Klanderman, Robert B.; Hazewinkel, Yark; Fockens, Paul; Dekker, Evelien

2015-01-01

The adenoma detection rate (ADR) is considered the most important quality indicator for colonoscopy and varies widely among colonoscopists. It is unknown whether the ADR of gastroenterology consultants can already be predicted during their colonoscopy training. To evaluate the ADR of fellows in

Enhancing international radiation/nuclear detection training opportunities

Energy Technology Data Exchange (ETDEWEB)

Williams, Thomas L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bersell, Bridget M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Booker, Paul M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Anderson, Gerald E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Leitch, Rosalyn M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Meagher, John B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Siefken, Rob R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Spracklen, James L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-09-23

The United States has worked domestically to develop and provide radiological and nuclear detection training and education initiatives aimed at interior law enforcement, but the international community has predominantly focused efforts at border and customs officials. The interior law enforcement officials of a State play a critical role in maintaining an effective national-level nuclear detection architecture. To meet this vital need, DNDO was funded by the U.S. Department of State (DOS) to create and deliver a 1-week course at the International Law Enforcement Academy (ILEA) in Budapest, Hungary to inform interior law enforcement personnel of the overall mission, and to provide an understanding of how the participants can combat the threats of radiological and nuclear terrorism through detection efforts. Two courses, with approximately 20 students in each course, were delivered in fiscal year (FY) 2013, two were delivered in FY 2014 and FY 2015, and as of this report’s writing more are planned in FY 2016. However, while the ILEA courses produced measurable success, DNDO requested Pacific Northwest National Laboratory (PNNL) research potential avenues to further increase the course impact.In a multi-phased approach, PNNL researched and analyzed several possible global training locations and venues, and other possible ways to increase the impact of the course using an agreed-to data-gathering format.

Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Institute of Scientific and Technical Information of China (English)

Lin Chen; Yong Deng; Weihua Luo; Zhen Wang; Shaoqun Zeng

2009-01-01

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with phys-iological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgrnent. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.

Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection

Science.gov (United States)

Tautz-Weinert, J.; Watson, S. J.

2016-09-01

Effective condition monitoring techniques for wind turbines are needed to improve maintenance processes and reduce operational costs. Normal behaviour modelling of temperatures with information from other sensors can help to detect wear processes in drive trains. In a case study, modelling of bearing and generator temperatures is investigated with operational data from the SCADA systems of more than 100 turbines. The focus is here on automated training and testing on a farm level to enable an on-line system, which will detect failures without human interpretation. Modelling based on linear combinations, artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines and Gaussian process regression is compared. The selection of suitable modelling inputs is discussed with cross-correlation analyses and a sensitivity study, which reveals that the investigated modelling techniques react in different ways to an increased number of inputs. The case study highlights advantages of modelling with linear combinations and artificial neural networks in a feedforward configuration.

Smart Sensor-Based Motion Detection System for Hand Movement Training in Open Surgery.

Science.gov (United States)

Sun, Xinyao; Byrns, Simon; Cheng, Irene; Zheng, Bin; Basu, Anup

2017-02-01

We introduce a smart sensor-based motion detection technique for objective measurement and assessment of surgical dexterity among users at different experience levels. The goal is to allow trainees to evaluate their performance based on a reference model shared through communication technology, e.g., the Internet, without the physical presence of an evaluating surgeon. While in the current implementation we used a Leap Motion Controller to obtain motion data for analysis, our technique can be applied to motion data captured by other smart sensors, e.g., OptiTrack. To differentiate motions captured from different participants, measurement and assessment in our approach are achieved using two strategies: (1) low level descriptive statistical analysis, and (2) Hidden Markov Model (HMM) classification. Based on our surgical knot tying task experiment, we can conclude that finger motions generated from users with different surgical dexterity, e.g., expert and novice performers, display differences in path length, number of movements and task completion time. In order to validate the discriminatory ability of HMM for classifying different movement patterns, a non-surgical task was included in our analysis. Experimental results demonstrate that our approach had 100 % accuracy in discriminating between expert and novice performances. Our proposed motion analysis technique applied to open surgical procedures is a promising step towards the development of objective computer-assisted assessment and training systems.

Analysis of System Training Impact for Major Defense Acquisition Programs (MDAPs): Training Systems Acquisition

Science.gov (United States)

2012-07-01

Training Systems Acquisition IDA Document D-4648 Log: H 12-001032 July 2012 Approved for public release; distribution is unlimited...Background The Patriot system began because of the need to replace an aging and limited air defense system in the 1970s, the Nike -Hercules, and...simulation technology, embedded training and distributed learning (DoD Instruction 1322.26), and instrumentation systems that provide “anytime, anyplace

Training Capability Data for Dismounted Soldier Training System

Science.gov (United States)

2015-06-01

Virtual Squad Training System ( VSTS ). Like some of its predecessors, VSTS included a combination of man-wearable, tethered, and desktop interfaces...Simulator Bayonet w/Omni Directional Treadmill TRAC-WSMR Soldier Station Soldier Visualization Station V-IMTS SVS2-DI, DAGGERS, ASWETS VSTS Dismounted...Simulation, VSTS – Virtual Squad Training System 4 and microphone. The VSMM utilizes radio frequency identification (RFID) tags and hand sensors to

Machine-learning-based real-bogus system for the HSC-SSP moving object detection pipeline

Science.gov (United States)

Lin, Hsing-Wen; Chen, Ying-Tung; Wang, Jen-Hung; Wang, Shiang-Yu; Yoshida, Fumi; Ip, Wing-Huen; Miyazaki, Satoshi; Terai, Tsuyoshi

2018-01-01

Machine-learning techniques are widely applied in many modern optical sky surveys, e.g., Pan-STARRS1, PTF/iPTF, and the Subaru/Hyper Suprime-Cam survey, to reduce human intervention in data verification. In this study, we have established a machine-learning-based real-bogus system to reject false detections in the Subaru/Hyper-Suprime-Cam Strategic Survey Program (HSC-SSP) source catalog. Therefore, the HSC-SSP moving object detection pipeline can operate more effectively due to the reduction of false positives. To train the real-bogus system, we use stationary sources as the real training set and "flagged" data as the bogus set. The training set contains 47 features, most of which are photometric measurements and shape moments generated from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ˜96% with a false positive rate (fpr) ˜1% or tpr ˜99% at fpr ˜5%. Therefore, we conclude that stationary sources are decent real training samples, and using photometry measurements and shape moments can reject false positives effectively.

Statistical Hypothesis Testing using CNN Features for Synthesis of Adversarial Counterexamples to Human and Object Detection Vision Systems

Energy Technology Data Exchange (ETDEWEB)

Raj, Sunny [Univ. of Central Florida, Orlando, FL (United States); Jha, Sumit Kumar [Univ. of Central Florida, Orlando, FL (United States); Pullum, Laura L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ramanathan, Arvind [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-05-01

Validating the correctness of human detection vision systems is crucial for safety applications such as pedestrian collision avoidance in autonomous vehicles. The enormous space of possible inputs to such an intelligent system makes it difficult to design test cases for such systems. In this report, we present our tool MAYA that uses an error model derived from a convolutional neural network (CNN) to explore the space of images similar to a given input image, and then tests the correctness of a given human or object detection system on such perturbed images. We demonstrate the capability of our tool on the pre-trained Histogram-of-Oriented-Gradients (HOG) human detection algorithm implemented in the popular OpenCV toolset and the Caffe object detection system pre-trained on the ImageNet benchmark. Our tool may serve as a testing resource for the designers of intelligent human and object detection systems.

A pilot study of dentists' assessment of caries detection and staging systems applied to early caries: PEARL Network findings.

Science.gov (United States)

Thompson, Van P; Schenkel, Andrew B; Penugonda, Bapanaiah; Wolff, Mark S; Zeller, Gregory G; Wu, Hongyu; Vena, Don; Grill, Ashley C; Curro, Frederick A

2016-01-01

The International Caries Detection and Assessment System (ICDAS II) and the Caries Classification System (CCS) are caries stage description systems proposed for adoption into clinical practice. This pilot study investigated clinicians' training in and use of these systems for detection of early caries and recommendations for individual tooth treatment. Patient participants (N = 8) with a range of noncavitated lesions (CCS ranks 2 and 4 and ICDAS II ranks 2-4) identified by a team of calibrated examiners were recruited from the New York University College of Dentistry clinic. Eighteen dentists-8 from the Practitioners Engaged in Applied Research and Learning (PEARL) Network and 10 recruited from the Academy of General Dentistry-were randomly assigned to 1 of 3 groups: 5 dentists used only visual-tactile (VT) examination, 7 were trained in the ICDAS II, and 6 were trained in the CCS. Lesion stage for each tooth was determined by the ICDAS II and CCS groups, and recommended treatment was decided by all groups. Teeth were assessed both with and without radiographs. Caries was detected in 92.7% (95% CI, 88%-96%) of the teeth by dentists with CCS training, 88.8% (95% CI, 84%-92%) of the teeth by those with ICDAS II training, and 62.3% (95% CI, 55%-69%) of teeth by the VT group. Web-based training was acceptable to all dentists in the CCS group (6 of 6) but fewer of the dentists in the ICDAS II group (5 of 7). The modified CCS translated clinically to more accurate caries detection, particularly compared to detection by untrained dentists (VT group). Moreover, the CCS was more accepted than was the ICDAS II, but dentists in both groups were open to the application of these systems. Agreement on caries staging requires additional training prior to a larger validation study.

Khmelnitsky NPP personnel training system improvement

International Nuclear Information System (INIS)

Sapronov, V.G.; Issupov, V.I.

1996-01-01

Khmelnitsky nuclear power plant personnel training system improvement is described, including creation of Training center, development of training courses based on SAT methodology, development of training hardware

Developing a Webfires Training System

Science.gov (United States)

2017-06-01

8  Figure 2.  Waterfall Process Model. ...........................................................................11  Figure 3.  Spiral ...training system (WFTS). The third chapter in this section provides an overview of the purpose and methodology of the future training system. Chapter...Waterfall Process Model. b. Spiral Model The second systems engineering process model is the spiral process model. According to Blanchard and Fabrycky

Microwave Radiometers for Fire Detection in Trains: Theory and Feasibility Study

Directory of Open Access Journals (Sweden)

Federico Alimenti

2016-06-01

Full Text Available This paper introduces the theory of fire detection in moving vehicles by microwave radiometers. The system analysis is discussed and a feasibility study is illustrated on the basis of two implementation hypotheses. The basic idea is to have a fixed radiometer and to look inside the glass windows of the wagon when it passes in front of the instrument antenna. The proposed sensor uses a three-pixel multi-beam configuration that allows an image to be formed by the movement of the train itself. Each pixel is constituted by a direct amplification microwave receiver operating at 31.4 GHz. At this frequency, the antenna can be a 34 cm offset parabolic dish, whereas a 1 K brightness temperature resolution is achievable with an overall system noise figure of 6 dB, an observation bandwidth of 2 GHz and an integration time of 1 ms. The effect of the detector noise is also investigated and several implementation hypotheses are discussed. The presented study is important since it could be applied to the automatic fire alarm in trains and moving vehicles with dielectric wall/windows.

Robust fault detection for the dynamics of high-speed train with multi-source finite frequency interference.

Science.gov (United States)

Bai, Weiqi; Dong, Hairong; Yao, Xiuming; Ning, Bin

2018-04-01

This paper proposes a composite fault detection scheme for the dynamics of high-speed train (HST), using an unknown input observer-like (UIO-like) fault detection filter, in the presence of wind gust and operating noises which are modeled as disturbance generated by exogenous system and unknown multi-source disturbance within finite frequency domain. Using system input and system output measurements, the fault detection filter is designed to generate the needed residual signals. In order to decouple disturbance from residual signals without truncating the influence of faults, this paper proposes a method to partition the disturbance into two parts. One subset of the disturbance does not appear in residual dynamics, and the influence of the other subset is constrained by H ∞ performance index in a finite frequency domain. A set of detection subspaces are defined, and every different fault is assigned to its own detection subspace to guarantee the residual signals are diagonally affected promptly by the faults. Simulations are conducted to demonstrate the effectiveness and merits of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Can the error detection mechanism benefit from training the working memory? A comparison between dyslexics and controls--an ERP study.

Directory of Open Access Journals (Sweden)

Tzipi Horowitz-Kraus

Full Text Available BACKGROUND: Based on the relationship between working memory and error detection, we investigated the capacity of adult dyslexic readers' working memory to change as a result of training, and the impact of training on the error detection mechanism. METHODOLOGY: 27 dyslexics and 34 controls, all university students, participated in the study. ERP methodology and behavioral measures were employed prior to, immediately after, and 6 months after training. The CogniFit Personal Coach Program, which consists of 24 sessions of direct training of working memory skills, was used. FINDINGS: Both groups of readers gained from the training program but the dyslexic readers gained significantly more. In the dyslexic group, digit span increased from 9.84+/-3.15 to 10.79+/-3.03. Working memory training significantly increased the number of words per minute read correctly by 14.73%. Adult brain activity changed as a result of training, evidenced by an increase in both working memory capacity and the amplitude of the Error-related Negativity (ERN component (24.71%. When ERN amplitudes increased, the percentage of errors on the Sternberg tests decreased. CONCLUSIONS: We suggest that by expanding the working memory capacity, larger units of information are retained in the system, enabling more effective error detection. The crucial functioning of the central-executive as a sub-component of the working memory is also discussed.

A System of Driving Fatigue Detection Based on Machine Vision and Its Application on Smart Device

Directory of Open Access Journals (Sweden)

Wanzeng Kong

2015-01-01

Full Text Available Driving fatigue is one of the most important factors in traffic accidents. In this paper, we proposed an improved strategy and practical system to detect driving fatigue based on machine vision and Adaboost algorithm. Kinds of face and eye classifiers are well trained by Adaboost algorithm in advance. The proposed strategy firstly detects face efficiently by classifiers of front face and deflected face. Then, candidate region of eye is determined according to geometric distribution of facial organs. Finally, trained classifiers of open eyes and closed eyes are used to detect eyes in the candidate region quickly and accurately. The indexes which consist of PERCLOS and duration of closed-state are extracted in video frames real time. Moreover, the system is transplanted into smart device, that is, smartphone or tablet, due to its own camera and powerful calculation performance. Practical tests demonstrated that the proposed system can detect driver fatigue with real time and high accuracy. As the system has been planted into portable smart device, it could be widely used for driving fatigue detection in daily life.

Tongue motor training support system.

Science.gov (United States)

Sasaki, Makoto; Onishi, Kohei; Nakayama, Atsushi; Kamata, Katsuhiro; Stefanov, Dimitar; Yamaguchi, Masaki

2014-01-01

In this paper, we introduce a new tongue-training system that can be used for improvement of the tongue's range of motion and muscle strength after dysphagia. The training process is organized in game-like manner. Initially, we analyzed surface electromyography (EMG) signals of the suprahyoid muscles of five subjects during tongue-training motions. This test revealed that four types tongue training motions and a swallowing motion could be classified with 93.5% accuracy. Recognized EMG signals during tongue motions were designed to allow control of a mouse cursor via intentional tongue motions. Results demonstrated that simple PC games could be played by tongue motions, achieving in this way efficient, enjoyable and pleasant tongue training. Using the proposed method, dysphagia patients can choose games that suit their preferences and/or state of mind. It is expected that the proposed system will be an efficient tool for long-term tongue motor training and maintaining patients' motivation.

Development of NPP personnel training system in Ukraine

Energy Technology Data Exchange (ETDEWEB)

Tarykin, V. [Operation Personnel Training Department, Khmelnitsky NPP, Training Center, Neteshin 30100, Khmelnitsky region (Ukraine)]. E-mail: tarykinv@ukr.net

2005-07-01

Modern personnel training and retraining system is a guarantee of NPPs safe reliable operation. Since the time when independence of Ukraine was proclaimed personnel training system was created directly at NPPs. This system is based on the latest legislation framework, developed subject to IAEA recommendations, gained international experience in the field of personnel training in view of increased demands to personnel qualification. Training Centers, formed at each plant, form one of the main components of NPP personnel training. Personnel training at Training Centers is performed in accordance with standard programmes. Simulator training base was created by joint efforts of specialists from the USA, Russia and Ukraine. Establishing manager training system and replacement reserves for National Nuclear Energy Generating Company 'ENERGOATOM' (NNEGC 'ENERGOATOM') managerial personnel, including training programme and training materials development, teacher selection and training, is under way. (author)

Selection of Dogs for Land Mine and Booby Trap Detection Training. Volume I

Science.gov (United States)

1976-09-01

Sarcoptes scabier, the 12 causes of demodectic and sarcoptic mange , respectively, may be speci- fically diagnosed by microscopic examination of skin scrapings...8217 UNCLASSIFIED 10 - SELECTION OF DOGS FOR LAND MINE AND BOOBY TRAP DETECTION TRAINING (U) FINAL TECHNICAL REPORT VOLUME i by Daniel S. Mitchell...1 ...... I " SELECTION OF DOGS k- FOR LAND MINE AND OOlBY TRAP DETECTION TRAINING * Contract -3C p t DAA1WC.LYA by , /ODaniel S

Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

Science.gov (United States)

Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

2014-11-01

A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

Approach to training the trainer at the Bell System Training Center

International Nuclear Information System (INIS)

Housley, E.A.; Stevenson, J.L.

1981-01-01

The major activity of the Bell System Training Center is to develop and deliver technical training. Experts in various technical areas are selected as course developers or instructors, usually on rotational assignments. Through a series of workshops, described in this paper, combined with coaching, use of job aids and working with more experienced peers, they become competent developers or instructors. There may be similarities between the mission of the Bell System Training Center and other contexts where criticality of job performance and technical subject matter are training characteristics

Development and utilization of simulator training replay system

International Nuclear Information System (INIS)

Suzuki, Koichi; Noji, Kunio

1998-01-01

The BWR Operator Training Center Corporation (BTC) has introduced an advanced training system called the Simulator Training Replay System. The intention of introducing this system is to enhance the effectiveness of simulator training synthetically by means of; (i) sufficient analytical pre- and post-studies in the classroom, thus, enabling instructors to use the classroom as a means of explanation and discussion with an optimized system which is closely correlated with the full-scope simulator and (ii) sufficient practical operation training using a full-scope simulator without excessive suppression of time. With this system, operational data and video images during simulator training can be reproduced in the classroom. Instructors use this system with their trainees before and after simulator training for pre- and post-studies in the classroom. (author)

FeO "Orange Arc" Emission Detected in Optical Spectrum of Leonid Persistent Trains

Science.gov (United States)

Jenniskens, Peter; Lacey, Matt; Allan, Beverly J.; Self, Daniel E.; Plane, John M. C.; DeVincenzi, Donald L. (Technical Monitor)

2000-01-01

We report the detection of a broad continuum emission dominating the visual spectrum of a Leonid persistent train. A comparison with laboratory spectra of FeO 1 "orange arc" emission at I mbar shows a general agreement of the band position and shape. The detection of FeO confirms the classical mechanism of metal atom catalyzed recombination of ozone and oxygen atoms as the driving force behind optical emission from persistent trains. Sodium and iron atoms are now confirmed catalysts.

Detecting suicidality among adolescent outpatients: evaluation of trained clinicians' suicidality assessment against a structured diagnostic assessment made by trained raters.

Science.gov (United States)

Holi, Matti Mikael; Pelkonen, Mirjami; Karlsson, Linnea; Tuisku, Virpi; Kiviruusu, Olli; Ruuttu, Titta; Marttunen, Mauri

2008-12-31

Accurate assessment of suicidality is of major importance. We aimed to evaluate trained clinicians' ability to assess suicidality against a structured assessment made by trained raters. Treating clinicians classified 218 adolescent psychiatric outpatients suffering from a depressive mood disorder into three classes: 1-no suicidal ideation, 2-suicidal ideation, no suicidal acts, 3-suicidal or self-harming acts. This classification was compared with a classification with identical content derived from the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-PL) made by trained raters. The convergence was assessed by kappa- and weighted kappa tests. The clinicians' classification to class 1 (no suicidal ideation) was 85%, class 2 (suicidal ideation) 50%, and class 3 (suicidal acts) 10% concurrent with the K-SADS evaluation (gamma2 = 37.1, df 4, p = 0.000). Weighted kappa for the agreement of the measures was 0.335 (CI = 0.198-0.471, p < 0.0001). The clinicians under-detected suicidal and self-harm acts, but over-detected suicidal ideation. There was only a modest agreement between the trained clinicians' suicidality evaluation and the K-SADS evaluation, especially concerning suicidal or self-harming acts. We suggest a wider use of structured scales in clinical and research settings to improve reliable detection of adolescents with suicidality.

Early tube leak detection system for steam boiler at KEV power plant

Directory of Open Access Journals (Sweden)

Ismail Firas B.

2016-01-01

Full Text Available Tube leakage in boilers has been a major contribution to trips which eventually leads to power plant shut downs. Training of network and developing artificial neural network (ANN models are essential in fault detection in critically large systems. This research focusses on the ANN modelling through training and validation of real data acquired from a sub-critical boiler unit. The artificial neural network (ANN was used to develop a compatible model and to evaluate the working properties and behaviour of boiler. The training and validation of real data has been applied using the feed-forward with back-propagation (BP. The right combination of number of neurons, number of hidden layers, training algorithms and training functions was run to achieve the best ANN model with lowest error. The ANN was trained and validated using real site data acquired from a coal fired power plant in Malaysia. The results showed that the Neural Network (NN with one hidden layers performed better than two hidden layer using feed-forward back-propagation network. The outcome from this study give us the best ANN model which eventually allows for early detection of boiler tube leakages, and forecast of a trip before the real shutdown. This will eventually reduce shutdowns in power plants.

Automated Error Detection in Physiotherapy Training.

Science.gov (United States)

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

2018-01-01

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

Extended attention span training system

Science.gov (United States)

Pope, Alan T.; Bogart, Edward H.

1991-01-01

Attention Deficit Disorder (ADD) is a behavioral disorder characterized by the inability to sustain attention long enough to perform activities such as schoolwork or organized play. Treatments for this disorder include medication and brainwave biofeedback training. Brainwave biofeedback training systems feed back information to the trainee showing him how well he is producing the brainwave pattern that indicates attention. The Extended Attention Span Training (EAST) system takes the concept a step further by making a video game more difficult as the player's brainwaves indicate that attention is waning. The trainee can succeed at the game only by maintaining an adequate level of attention. The EAST system is a modification of a biocybernetic system that is currently being used to assess the extent to which automated flight management systems maintain pilot engagement. This biocybernetic system is a product of a program aimed at developing methods to evaluate automated flight deck designs for compatibility with human capabilities. The EAST technology can make a contribution in the fields of medical neuropsychology and neurology, where the emphasis is on cautious, conservative treatment of youngsters with attention disorders.

Virtual-Reality training system for nuclear security

International Nuclear Information System (INIS)

Nonaka, Nobuyuki

2012-01-01

At the Integrated Support Center for Nuclear Nonproliferation and Nuclear Security (ISCN) of the Japan Atomic Energy Agency, the virtual reality (VR) training system is under development for providing a practical training environment to implement experience-oriented and interactive lessons on nuclear security for wide range of participants in human resource development assistance program mainly to Asian emerging nuclear-power countries. This system electrically recreates and visualizes nuclear facilities and training conditions in stereoscopic (3D) view on a large-scale display (CAVE system) as virtual reality training facility (VR facility) and it provides training participants with effective environments to learn installation and layout of security equipment in the facility testing and verifying visually the protection performances under various situations such as changes in day-night lighting and weather conditions, which may lead to practical exercise in the design and evaluation of the physical protection system. This paper introduces basic concept of the system and outline of training programs as well as featured aspects in using the VR technology for the nuclear security. (author)

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...

TRAINING SYSTEM OF FUTURE SPECIALISTS: QUALITY CONTROL

Directory of Open Access Journals (Sweden)

Vladimir A. Romanov

2015-01-01

Full Text Available The aim of the investigation is development of innovative strategy of quality control training of engineers and skilled workers (hereinafter – future specialists in educational professional organizations on the principles of social partnership.Methods. Theoretic: theoretic and methodological analysis, polytheoretic synthesis, modeling. Empirical: research and generalization of the system, process and competence – based approaches experience, experiment, observation, surveys, expert evaluation, SWOT-analysis as a method of strategic planning which is to identify the internal and external factors (socio-cultural of the organization surrounding.Results. The strategy of the development of the process of quality control training in educational professional organizations and a predictive model of the system of quality control training for future engineers and workers have been created on the analysis and synthesis of a quantitative specification of the quality, the obtained experience and success in control training of future specialists in educational professional organizations in recent economic and educational conditions.Scientific novelty. There has been built a predicative model of quality control training of future specialists to meet modern standards and the principles of social partnership; the control algorithm of the learning process, developed in accordance with the standards (international of quality ISO in the implementation of the quality control systems of the process approach (matrix-based responsibility, competence and remit of those responsible for the education process in the educational organization, the «problem» terms and diagnostic tools for assessing the quality of professional training of future specialists. The perspective directions of innovation in the control of the quality of future professionals training have been determined; the parameters of a comprehensive analysis of the state of the system to ensure the

Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains

Science.gov (United States)

Malvestio, Irene; Kreuz, Thomas; Andrzejak, Ralph G.

2017-08-01

The detection of directional couplings between dynamics based on measured spike trains is a crucial problem in the understanding of many different systems. In particular, in neuroscience it is important to assess the connectivity between neurons. One of the approaches that can estimate directional coupling from the analysis of point processes is the nonlinear interdependence measure L . Although its efficacy has already been demonstrated, it still needs to be tested under more challenging and realistic conditions prior to an application to real data. Thus, in this paper we use the Hindmarsh-Rose model system to test the method in the presence of noise and for different spiking regimes. We also examine the influence of different parameters and spike train distances. Our results show that the measure L is versatile and robust to various types of noise, and thus suitable for application to experimental data.

Delivering Training for Highly Demanding Information Systems

Science.gov (United States)

Norton, Andrew Lawrence; Coulson-Thomas, Yvette May; Coulson-Thomas, Colin Joseph; Ashurst, Colin

2012-01-01

Purpose: There is a lack of research covering the training requirements of organisations implementing highly demanding information systems (HDISs). The aim of this paper is to help in the understanding of appropriate training requirements for such systems. Design/methodology/approach: This research investigates the training delivery within a…

Development of cyber training system for nuclear fields

International Nuclear Information System (INIS)

Kim, Young Taek; Park, Jong Kyun; Lee, Eui Jin; Lee, Han Young; Choi, Nan Young

2002-02-01

This report describes on technical contents related cyber training system construct on KAERI Nuclear Training Center, and on using cases of cyber education in domestic and foreign countries. Also realtime training system through the internet and cyber training management system for atomic fields is developed. All users including trainee, course managers and lecturers can use new technical for create new paradigm

Study on a Footwork Training and Testing System

Directory of Open Access Journals (Sweden)

Qi Hu

2018-02-01

Full Text Available In the sport science fields, for a long time there are various attempts to explore more advanced technology in order to collect kinds of information concerned during athletes training and matches. In the paper, a footwork training and testing system has been developed by adopting the advanced technology of Wireless Sensor Network (WSN. The system is comprised of some wireless senor nodes and gateways, system control software and so on. By means of the system, the daily footwork training methods and modes will be simulated to automatically guide the training of the athletes, at the same time the training data concerned will be automatically recorded, including moving velocity, moving frequency and success average, moving exercise duration and so on, and it is facilitate to evaluate digitally the training and testing effects for coaches and athletes. The system will bring about an auxiliary means in sport science training and research, make coaches and researchers have more options for the technical and information forms, and provide the technology foundation for synchronizing and intermingling the training and testing smoothly.

Multipass Channel Estimation and Joint Multiuser Detection and Equalization for MIMO Long-Code DS/CDMA Systems

Directory of Open Access Journals (Sweden)

Buzzi Stefano

2006-01-01

Full Text Available The problem of joint channel estimation, equalization, and multiuser detection for a multiantenna DS/CDMA system operating over a frequency-selective fading channel and adopting long aperiodic spreading codes is considered in this paper. First of all, we present several channel estimation and multiuser data detection schemes suited for multiantenna long-code DS/CDMA systems. Then, a multipass strategy, wherein the data detection and the channel estimation procedures exchange information in a recursive fashion, is introduced and analyzed for the proposed scenario. Remarkably, this strategy provides, at the price of some attendant computational complexity increase, excellent performance even when very short training sequences are transmitted, and thus couples together the conflicting advantages of both trained and blind systems, that is, good performance and no wasted bandwidth, respectively. Space-time coded systems are also considered, and it is shown that the multipass strategy provides excellent results for such systems also. Likewise, it is also shown that excellent performance is achieved also when each user adopts the same spreading code for all of its transmit antennas. The validity of the proposed procedure is corroborated by both simulation results and analytical findings. In particular, it is shown that adopting the multipass strategy results in a remarkable reduction of the channel estimation mean-square error and of the optimal length of the training sequence.

Improved training for target detection using Fukunaga-Koontz transform and distance classifier correlation filter

Science.gov (United States)

Elbakary, M. I.; Alam, M. S.; Aslan, M. S.

2008-03-01

In a FLIR image sequence, a target may disappear permanently or may reappear after some frames and crucial information such as direction, position and size related to the target are lost. If the target reappears at a later frame, it may not be tracked again because the 3D orientation, size and location of the target might be changed. To obtain information about the target before disappearing and to detect the target after reappearing, distance classifier correlation filter (DCCF) is trained manualy by selecting a number of chips randomly. This paper introduces a novel idea to eliminates the manual intervention in training phase of DCCF. Instead of selecting the training chips manually and selecting the number of the training chips randomly, we adopted the K-means algorithm to cluster the training frames and based on the number of clusters we select the training chips such that a training chip for each cluster. To detect and track the target after reappearing in the field-ofview ,TBF and DCCF are employed. The contduced experiemnts using real FLIR sequences show results similar to the traditional agorithm but eleminating the manual intervention is the advantage of the proposed algorithm.

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

Directory of Open Access Journals (Sweden)

Min-Joo Kang

Full Text Available A novel intrusion detection system (IDS using a deep neural network (DNN is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN, therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN bus.

Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

Science.gov (United States)

Kang, Min-Joo; Kang, Je-Won

2016-01-01

A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects: task training system for stroke rehabilitation.

Science.gov (United States)

Ho, N S K; Tong, K Y; Hu, X L; Fung, K L; Wei, X J; Rong, W; Susanto, E A

2011-01-01

An exoskeleton hand robotic training device is specially designed for persons after stroke to provide training on their impaired hand by using an exoskeleton robotic hand which is actively driven by their own muscle signals. It detects the stroke person's intention using his/her surface electromyography (EMG) signals from the hemiplegic side and assists in hand opening or hand closing functional tasks. The robotic system is made up of an embedded controller and a robotic hand module which can be adjusted to fit for different finger length. Eight chronic stroke subjects had been recruited to evaluate the effects of this device. The preliminary results showed significant improvement in hand functions (ARAT) and upper limb functions (FMA) after 20 sessions of robot-assisted hand functions task training. With the use of this light and portable robotic device, stroke patients can now practice more easily for the opening and closing of their hands at their own will, and handle functional daily living tasks at ease. A video is included together with this paper to give a demonstration of the hand robotic system on chronic stroke subjects and it will be presented in the conference. © 2011 IEEE

Reduction in training time of a deep learning model in detection of lesions in CT

Science.gov (United States)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

Training-induced improvement of response selection and error detection in aging assessed by task switching: Effects of cognitive, physical and relaxation training

Directory of Open Access Journals (Sweden)

Patrick Darius Gajewski

2012-05-01

Full Text Available Cognitive control functions decline with increasing age. One of them is response selection that forms the link between the goals and the motor system and is therefore crucial for performance outcomes in cognitive tasks. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in electrophysiological brain activity, as measured in event-related potentials (ERPs. 141 healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength-training, cognitive training (paper-pencil and computer-aided, relaxation and wellness (social control group and a no-contact control group that did not receive any intervention. Training sessions took place twice a week for 90 minutes for a period of 4 months.The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task-sets in working memory and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials (ERP which showed higher amplitudes in a number of potentials associated with response selection (N2, allocation of cognitive resources (P3b and error detection (Ne.Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

Rapid Object Detection Systems, Utilising Deep Learning and Unmanned Aerial Systems (uas) for Civil Engineering Applications

Science.gov (United States)

Griffiths, D.; Boehm, J.

2018-05-01

With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks (CNNs) for applied engineering purposes. Three CNNs are trained on 275 UAS-derived and freely available online images for object detection of 3m2 segments of railway track. These includes two models based on the Faster RCNN object detection algorithm (Resnet and Incpetion-Resnet) as well as the novel onestage Focal Loss network architecture (Retinanet). Model performance was assessed with respect to three accuracy metrics. The first two consisted of Intersection over Union (IoU) with thresholds 0.5 and 0.1. The last assesses accuracy based on the proportion of track covered by object detection proposals against total track length. In under six hours of training (and two hours of manual labelling) the models detected 91.3 %, 83.1 % and 75.6 % of track in the 500 test images acquired from the UAS survey Retinanet, Resnet and Inception-Resnet respectively. We then discuss the potential for such applications of such systems within the engineering field for a range of scenarios.

Electric system training with programmable controllers

International Nuclear Information System (INIS)

Benson, M.B.

1989-01-01

A power system simulator (PSS) for training system operators has been opened at the Pacific Gas and Electric Training Center at San Ramon, California. The simulator was designed as an instructional aid and is part of a larger, more comprehensive operating training facility. It has the capability of duplicating both routine and emergency situations for transmission and distribution lines, power plants, and substations. Modeled after nuclear plant simulators, the PSS utilizes state-of-the-art technology and is believed to be on the leading edge of power system simulators. The new operator training facility covers 10,000 ft/sup 2/ and is divided into four classrooms, two labs, three simulated dispatch centers, and various administrative offices. Ten full- and part-time instructors are on staff to train the over 900 system, power plant, agency, and trainee personnel. The simulator is considered the heart of the complex and covers over half of the available floor space. It is divided into two large rooms and further separated by the dispatch centers. The indoor room represents the high-voltage transmission and generating stations, the outdoor room is for both the lower-voltage distribution system and simulated physical equipment. In each room, full-size control boards (equipped with actual relay protection and automatic schemes) are arranged into various stations and lines

Survey on multisensory feedback virtual reality dental training systems.

Science.gov (United States)

Wang, D; Li, T; Zhang, Y; Hou, J

2016-11-01

Compared with traditional dental training methods, virtual reality training systems integrated with multisensory feedback possess potentials advantages. However, there exist many technical challenges in developing a satisfactory simulator. In this manuscript, we systematically survey several current dental training systems to identify the gaps between the capabilities of these systems and the clinical training requirements. After briefly summarising the components, functions and unique features of each system, we discuss the technical challenges behind these systems including the software, hardware and user evaluation methods. Finally, the clinical requirements of an ideal dental training system are proposed. Future research/development areas are identified based on an analysis of the gaps between current systems and clinical training requirements. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Training Effectiveness Evaluation (TEE) of the Advanced Fire Fighting Training System. Focus on the Trained Person.

Science.gov (United States)

Cordell, Curtis C.; And Others

A training effectiveness evaluation of the Navy Advanced Fire Fighting Training System was conducted. This system incorporates simulated fires as well as curriculum materials and instruction. The fires are non-pollutant, computer controlled, and installed in a simulated shipboard environment. Two teams of 15 to 16 persons, with varying amounts of…

PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET

Directory of Open Access Journals (Sweden)

S. Devaraju

2014-04-01

Full Text Available Intrusion Detection Systems are challenging task for finding the user as normal user or attack user in any organizational information systems or IT Industry. The Intrusion Detection System is an effective method to deal with the kinds of problem in networks. Different classifiers are used to detect the different kinds of attacks in networks. In this paper, the performance of intrusion detection is compared with various neural network classifiers. In the proposed research the four types of classifiers used are Feed Forward Neural Network (FFNN, Generalized Regression Neural Network (GRNN, Probabilistic Neural Network (PNN and Radial Basis Neural Network (RBNN. The performance of the full featured KDD Cup 1999 dataset is compared with that of the reduced featured KDD Cup 1999 dataset. The MATLAB software is used to train and test the dataset and the efficiency and False Alarm Rate is measured. It is proved that the reduced dataset is performing better than the full featured dataset.

Awareness Trainings and Detecting Jihadists among Asylum Seekers: A Case Study from the Netherlands

NARCIS (Netherlands)

van Wijk, J.; Bolhuis, M.P.

2017-01-01

Dutch frontline professionals who work with asylum seekers receive awareness training to assist them in identifying possible signs of jihadist convictions. During these training sessions, they are provided with a complex, ambiguous, and multi-interpretable advice on how to detect such convictions.

In-situ trainable intrusion detection system

Energy Technology Data Exchange (ETDEWEB)

Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob; Potok, Thomas E.

2016-11-15

A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such that the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.

How to Deal with Revolutions in Train Control Systems

Directory of Open Access Journals (Sweden)

Hideo Nakamura

2016-09-01

Full Text Available Train control systems ensure the safety of railways. This paper begins with a summary of the typical train control systems in Japan and Europe. Based on this summary, the author then raises the following question regarding current train control systems: What approach should be adopted in order to enhance the functionality, safety, and reliability of train control systems and assist in commercial operations on railways? Next, the author provides a desirable architecture that is likely to assist with the development of new train control systems based on current information and communication technologies. A new unified train control system (UTCS is proposed that is effective in enhancing the robustness and competitiveness of a train control system. The ultimate architecture of the UTCS will be only composed of essential elements such as point machines and level crossing control devices in the field. Finally, a processing method of the UTCS is discussed.

Deception Detection in a Computer-Mediated Environment: Gender, Trust, and Training Issues

National Research Council Canada - National Science Library

Dziubinski, Monica

2003-01-01

.... This research draws on communication and deception literature to develop a conceptual model proposing relationships between deception detection abilities in a computer-mediated environment, gender, trust, and training...

Knowledge society training system

International Nuclear Information System (INIS)

Ceclan, Mihail; Ionescu, Tudor Basarab; Ceclan, Rodica Elena; Tatar, Florin; Tiron, Cristian; Georgescu, Luisa Maria

2005-01-01

The paper aims to present the results of the Cernavoda NPP Training Department modernization project. In order to achieve a knowledge society training system, in the first stage of the project a Computer Based Training (CBT) or E-Learning software platform and several CBT objects/courses have been implemented. The conceived solution is called CBTCenter which is a complete E-Learning and CBT system, offering a variety of teaching and learning tools and services to its users. CBT and/or E-Learning always mean two things: a software platform and content authoring. Ideally, a software platform should be able to import any type of flat documentation and integrate it into a structured database which keeps track of pedagogically meaningful information like the student's progress in studying materials, tests and quizzes, grades, etc. At the same time, the materials, the study and the tests have to be organized around certain objectives which play the role of guidelines during the entire educational activity. An example of such a course which has been successfully integrated into CBTCenter is Labour safety - code name BB-001. The implementation of the CBT technology at NPP Cernavoda Training Department has brought several advantages: the technology improves overall communication between all individuals which take part in the educational process; the classroom space problem has been considerably reduced; students can access training materials from their own desk using the NPP intranet; the logistics problems will decrease with the conversion of more and more conventional courses and materials into CBT objects/courses. (authors)

Study on training of nuclear power system operators

International Nuclear Information System (INIS)

Guo Lifeng; Zhou Gang; Yu Lei

2012-01-01

In order to satisfy new requirements about operators of nuclear power system, which are brought up by development and changes of social environment, science and technology, we do research on and make analysis of the problem of operator training. This paper focuses on development and changes of operator training system and content, mentality training, application of new technology to training, feedback of experience and so on. Analysis showed that the content of operator training is also confronted with some new requirements. So we bring up the new requirements to the operator, such as mentality training, cognizance ability training, adaptability training of special environment and endurance training. Besides, it is important for perfecting operator cultivation mechanism and improving training effect to feed back experience and apply new technology. So the trainer must improve training content and cultivation mechanism continuously. (authors)

Dependability analysis of the data communication system in train control system

Institute of Scientific and Technical Information of China (English)

无

2009-01-01

Communication based train control (CBTC) system is based on mobile communication and overcomes fixed blocks in order to increase track utilization and train safety. The data communication system (DCS) between trains and wayside equipment is a crucial factor for the safe and efficient operation of CBTC system. The dependability under various transmission conditions needs to be modeled and evaluated. In this paper,a stochastic reward net (SRN) model for DCS based IEEE 802.11 standard was developed,which captures all relevant failure and failure recovery behavior system aspects in a concise way. We compared the reliability,availability for DCS with and without access point (AP) and antenna redundant configuration. We also quantitatively evaluated and compared the frame loss probability for three DCS configurations with different train velocities and train numbers in one radio cell. Fixed-point iteration was adopted to simplify the analysis. Numerical results showed the significant improvement of the reliability,availability and the frame loss probability index for the full redundant configuration.

An integrated logit model for contamination event detection in water distribution systems.

Science.gov (United States)

Housh, Mashor; Ostfeld, Avi

2015-05-15

The problem of contamination event detection in water distribution systems has become one of the most challenging research topics in water distribution systems analysis. Current attempts for event detection utilize a variety of approaches including statistical, heuristics, machine learning, and optimization methods. Several existing event detection systems share a common feature in which alarms are obtained separately for each of the water quality indicators. Unifying those single alarms from different indicators is usually performed by means of simple heuristics. A salient feature of the current developed approach is using a statistically oriented model for discrete choice prediction which is estimated using the maximum likelihood method for integrating the single alarms. The discrete choice model is jointly calibrated with other components of the event detection system framework in a training data set using genetic algorithms. The fusing process of each indicator probabilities, which is left out of focus in many existing event detection system models, is confirmed to be a crucial part of the system which could be modelled by exploiting a discrete choice model for improving its performance. The developed methodology is tested on real water quality data, showing improved performances in decreasing the number of false positive alarms and in its ability to detect events with higher probabilities, compared to previous studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

The computer aided education and training system for accident management

International Nuclear Information System (INIS)

Yoneyama, Mitsuru; Kubota, Ryuji; Fujiwara, Tadashi; Sakuma, Hitoshi

1999-01-01

The education and training system for Accident Management was developed by the Japanese BWR group and Hitachi Ltd. The education and training system is composed of two systems. One is computer aided instruction (CAI) education system and the education and training system with computer simulations. Both systems are designed to be executed on personal computers. The outlines of the CAI education system and the education and training system with simulator are reported below. These systems provides plant operators and technical support center staff with the effective education and training for accident management. (author)

Development of plant status display system for on-site educational training system

International Nuclear Information System (INIS)

Yoshimura, Seiichi; Fujimoto, Junzo; Okamoto, Hisatake; Tsunoda, Ryohei; Watanabe, Takao; Masuko, Jiro.

1986-01-01

The purpose of this system is to make easy the comprehension of the facility and dynamics of nuclear power plants. This report describes the tendency and future position of how the educational training system should be, and furthermore describes the experiment. Main results are as follows. 1. The present status and the future tendency of educational training system for nuclear power plant operators. CAI (Computer Assisted Instruction) system has following characteristics. (1) It is easy to introduce plant specific characteristics to the educational training. (2) It is easy to execute the detailed training for the compensation of the full-scale simulator. 2. Plant status display system for on-site educational training system. The fundamental function of the system is as follows. (1) It has 2 CRT displays and voice output devices. (2) It has easy manupulation type of man-machine interface. (3) It has the function for the evaluation of the training results. 3. The effectiveness of this system. The effectiveness evaluation test has been carried out by using this system actually. (1) This system has been proved to be essentially effective and some improvements for the future utilization has been pointed out. (2) It should be faster when the CRT displayes are changed, and it should have the explanation function when the plant transients are displayed. (author)

Fault detection of flywheel system based on clustering and principal component analysis

Directory of Open Access Journals (Sweden)

Wang Rixin

2015-12-01

Full Text Available Considering the nonlinear, multifunctional properties of double-flywheel with closed-loop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the multifunctional flywheels. At the first step of the proposed algorithm, clustering is taken as feature recognition to check the instructions of “integrated power and attitude control” system, such as attitude control, energy storage or energy discharge. These commands will ask the flywheel system to work in different operation modes. Therefore, the relationship of parameters in different operations can define the cluster structure of training data. Ordering points to identify the clustering structure (OPTICS can automatically identify these clusters by the reachability-plot. K-means algorithm can divide the training data into the corresponding operations according to the reachability-plot. Finally, the last step of proposed model is used to define the relationship of parameters in each operation through the principal component analysis (PCA method. Compared with the PCA model, the proposed approach is capable of identifying the new clusters and learning the new behavior of incoming data. The simulation results show that it can effectively detect the faults in the multifunctional flywheels system.

A study of the transferability of influenza case detection systems between two large healthcare systems.

Science.gov (United States)

Ye, Ye; Wagner, Michael M; Cooper, Gregory F; Ferraro, Jeffrey P; Su, Howard; Gesteland, Per H; Haug, Peter J; Millett, Nicholas E; Aronis, John M; Nowalk, Andrew J; Ruiz, Victor M; López Pineda, Arturo; Shi, Lingyun; Van Bree, Rudy; Ginter, Thomas; Tsui, Fuchiang

2017-01-01

This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance. Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, pdetection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the accuracy of the NLP parser.

THE ARCHITECTURE OF MULTI-COMPONENT DISTRIBUTED HYBRID EXPERT TRAINING SYSTEM

Directory of Open Access Journals (Sweden)

Оleh Shevchuk

2016-09-01

Full Text Available The paper reports on the design of a multi-component architecture of distributed hybrid expert training system that can be used for the study of knowledge base of both internal and external expert systems and artificial intelligence systems that are distributed on Internet servers and other computer networks. Expert training system is based on three groups of basic principles: cybernetic, reflecting experience of previous research of systems of artificial intelligence, expert training systems; pedagogical, determining the principles, on which pedagogical design and use of expert training systems are based; psychological, determining preconditious and understanding of pupils psychics, on which the processes of design and use of expert training systems in professional training of future specialists are based.It accounts for the efficient training through the distributed knowledge via the Internet, which greatly increases the didactic capabilities of the system.

Sample Selection for Training Cascade Detectors

OpenAIRE

V?llez, Noelia; Deniz, Oscar; Bueno, Gloria

2015-01-01

Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represent anything except the object of interest. In this respect, the negative set typically contains orders of magnitude more images than the positive set. However, imbalanced training databases lead to biased classifiers. In this paper, we focus our a...

Training Requirements and Information Management System

Energy Technology Data Exchange (ETDEWEB)

Cillan, T.F.; Hodgson, M.A.

1992-05-01

This is the software user's guide for the Training Requirements and Information Management System. This guide defines and describes the software operating procedures as they apply to the end user of the software program. This guide is intended as a reference tool for the user who already has an indepth knowledge of the Training Requirements and Information Management System functions and data reporting requirement.

An augmented reality home-training system based on the mirror training and imagery approach.

Science.gov (United States)

Trojan, Jörg; Diers, Martin; Fuchs, Xaver; Bach, Felix; Bekrater-Bodmann, Robin; Foell, Jens; Kamping, Sandra; Rance, Mariela; Maaß, Heiko; Flor, Herta

2014-09-01

Mirror training and movement imagery have been demonstrated to be effective in treating several clinical conditions, such as phantom limb pain, stroke-induced hemiparesis, and complex regional pain syndrome. This article presents an augmented reality home-training system based on the mirror and imagery treatment approaches for hand training. A head-mounted display equipped with cameras captures one hand held in front of the body, mirrors this hand, and displays it in real time in a set of four different training tasks: (1) flexing fingers in a predefined sequence, (2) moving the hand into a posture fitting into a silhouette template, (3) driving a "Snake" video game with the index finger, and (4) grasping and moving a virtual ball. The system records task performance and transfers these data to a central server via the Internet, allowing monitoring of training progress. We evaluated the system by having 7 healthy participants train with it over the course of ten sessions of 15-min duration. No technical problems emerged during this time. Performance indicators showed that the system achieves a good balance between relatively easy and more challenging tasks and that participants improved significantly over the training sessions. This suggests that the system is well suited to maintain motivation in patients, especially when it is used for a prolonged period of time.

Computer aided training system development

International Nuclear Information System (INIS)

Midkiff, G.N.

1987-01-01

The first three phases of Training System Development (TSD) -- job and task analysis, curriculum design, and training material development -- are time consuming and labor intensive. The use of personal computers with a combination of commercial and custom-designed software resulted in a significant reduction in the man-hours required to complete these phases for a Health Physics Technician Training Program at a nuclear power station. This paper reports that each step in the training program project involved the use of personal computers: job survey data were compiled with a statistical package, task analysis was performed with custom software designed to interface with a commercial database management program. Job Performance Measures (tests) were generated by a custom program from data in the task analysis database, and training materials were drafted, edited, and produced using commercial word processing software

Neural Network Based Intrusion Detection System for Critical Infrastructures

Energy Technology Data Exchange (ETDEWEB)

Todd Vollmer; Ondrej Linda; Milos Manic

2009-07-01

Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

Science.gov (United States)

Goense, J B M; Ratnam, R

2003-10-01

An important problem in sensory processing is deciding whether fluctuating neural activity encodes a stimulus or is due to variability in baseline activity. Neurons that subserve detection must examine incoming spike trains continuously, and quickly and reliably differentiate signals from baseline activity. Here we demonstrate that a neural integrator can perform continuous signal detection, with performance exceeding that of trial-based procedures, where spike counts in signal- and baseline windows are compared. The procedure was applied to data from electrosensory afferents of weakly electric fish (Apteronotus leptorhynchus), where weak perturbations generated by small prey add approximately 1 spike to a baseline of approximately 300 spikes s(-1). The hypothetical postsynaptic neuron, modeling an electrosensory lateral line lobe cell, could detect an added spike within 10-15 ms, achieving near ideal detection performance (80-95%) at false alarm rates of 1-2 Hz, while trial-based testing resulted in only 30-35% correct detections at that false alarm rate. The performance improvement was due to anti-correlations in the afferent spike train, which reduced both the amplitude and duration of fluctuations in postsynaptic membrane activity, and so decreased the number of false alarms. Anti-correlations can be exploited to improve detection performance only if there is memory of prior decisions.

Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

Science.gov (United States)

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

2018-02-01

This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

Intrusion detection system elements

International Nuclear Information System (INIS)

Eaton, M.J.; Mangan, D.L.

1980-09-01

This report highlights elements required for an intrusion detection system and discusses problems which can be encountered in attempting to make the elements effective. Topics discussed include: sensors, both for exterior detection and interior detection; alarm assessment systems, with the discussion focused on video assessment; and alarm reporting systems, including alarm communication systems and dislay/console considerations. Guidance on careful planning and design of a new or to-be-improved system is presented

Field Tests of a Tractor Rollover Detection and Emergency Notification System.

Science.gov (United States)

Liu, B; Koc, A B

2015-04-01

The objective of this research was to assess the feasibility of a rollover detection and emergency notification system for farm tractors using field tests. The emergency notification system was developed based on a tractor stability model and implemented on a mobile electronic device with the iOS operating system. A complementary filter was implemented to combine the data from the accelerometer and gyroscope sensors to improve their accuracies in calculating the roll and pitch angles and the roll and pitch rates. The system estimates a stability index value during tractor operation, displays feedback messages when the stability index is lower than a preset threshold value, and transmits emergency notification messages when an overturn happens. Ten tractor rollover tests were conducted on a field track. The developed system successfully monitored the stability of the tractor during all of the tests. The iOS application was able to detect rollover accidents and transmit emergency notifications in the form of a phone call and email when an accident was detected. The system can be a useful tool for training and education in safe tractor operation. The system also has potential for stability monitoring and emergency notification of other on-road and off-road motorized vehicles.

Automatic Pedestrian Crossing Detection and Impairment Analysis Based on Mobile Mapping System

Science.gov (United States)

Liu, X.; Zhang, Y.; Li, Q.

2017-09-01

Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians' lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

AUTOMATIC PEDESTRIAN CROSSING DETECTION AND IMPAIRMENT ANALYSIS BASED ON MOBILE MAPPING SYSTEM

Directory of Open Access Journals (Sweden)

X. Liu

2017-09-01

Full Text Available Pedestrian crossing, as an important part of transportation infrastructures, serves to secure pedestrians’ lives and possessions and keep traffic flow in order. As a prominent feature in the street scene, detection of pedestrian crossing contributes to 3D road marking reconstruction and diminishing the adverse impact of outliers in 3D street scene reconstruction. Since pedestrian crossing is subject to wearing and tearing from heavy traffic flow, it is of great imperative to monitor its status quo. On this account, an approach of automatic pedestrian crossing detection using images from vehicle-based Mobile Mapping System is put forward and its defilement and impairment are analyzed in this paper. Firstly, pedestrian crossing classifier is trained with low recall rate. Then initial detections are refined by utilizing projection filtering, contour information analysis, and monocular vision. Finally, a pedestrian crossing detection and analysis system with high recall rate, precision and robustness will be achieved. This system works for pedestrian crossing detection under different situations and light conditions. It can recognize defiled and impaired crossings automatically in the meanwhile, which facilitates monitoring and maintenance of traffic facilities, so as to reduce potential traffic safety problems and secure lives and property.

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

Science.gov (United States)

Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

2018-04-01

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

PERFORMANCE COMPARISON OF INTRUSION DETECTION SYSTEM USING VARIOUS TECHNIQUES – A REVIEW

Directory of Open Access Journals (Sweden)

S. Devaraju

2013-09-01

Full Text Available Nowadays, the security has become a critical part of any organization or industry information systems. The Intrusion Detection System is an effective method to deal with the new kind of threats such as DoS, Porbe, R2L and U2R. In this paper, we analyze the various approaches such as Hidden Semi Markov Model, Conditional Random Fields and Layered Approach, Bayesian classification, Data Mining techniques, Clustering Algorithms such as K-Means and Fuzzy c-Means, Back Propagation Neural Network, SOM Neural Network, Rough Set Neural Network Algorithm, Genetic Algorithm, Pattern Matching, Principle Component Analysis, Linear Discriminant Analysis, Independent Component Analysis, Multivariate Statistical Analysis, SOM/PSO algorithm etc. The performance is measured for two different datasets using various approaches. The datasets are trained and tested for identifying the new attacks that will affect the hosts or networks. The well known KDD Cup 1999 or DARPA 1999 dataset has been used to improve the accuracy and performance. The four groups of attacks are identified as Probe, DoS, U2R and R2L. The dataset used for training set is 494,021 and testing set is 311,028. The aim is to improve the detection rate and performance of the proposed system.

Object detection system based on multimodel saliency maps

Science.gov (United States)

Guo, Ya'nan; Luo, Chongfan; Ma, Yide

2017-03-01

Detection of visually salient image regions is extensively applied in computer vision and computer graphics, such as object detection, adaptive compression, and object recognition, but any single model always has its limitations to various images, so in our work, we establish a method based on multimodel saliency maps to detect the object, which intelligently absorbs the merits of various individual saliency detection models to achieve promising results. The method can be roughly divided into three steps: in the first step, we propose a decision-making system to evaluate saliency maps obtained by seven competitive methods and merely select the three most valuable saliency maps; in the second step, we introduce heterogeneous PCNN algorithm to obtain three prime foregrounds; and then a self-designed nonlinear fusion method is proposed to merge these saliency maps; at last, the adaptive improved and simplified PCNN model is used to detect the object. Our proposed method can constitute an object detection system for different occasions, which requires no training, is simple, and highly efficient. The proposed saliency fusion technique shows better performance over a broad range of images and enriches the applicability range by fusing different individual saliency models, this proposed system is worthy enough to be called a strong model. Moreover, the proposed adaptive improved SPCNN model is stemmed from the Eckhorn's neuron model, which is skilled in image segmentation because of its biological background, and in which all the parameters are adaptive to image information. We extensively appraise our algorithm on classical salient object detection database, and the experimental results demonstrate that the aggregation of saliency maps outperforms the best saliency model in all cases, yielding highest precision of 89.90%, better recall rates of 98.20%, greatest F-measure of 91.20%, and lowest mean absolute error value of 0.057, the value of proposed saliency evaluation

Nucleic acid detection system and method for detecting influenza

Science.gov (United States)

Cai, Hong; Song, Jian

2015-03-17

The invention provides a rapid, sensitive and specific nucleic acid detection system which utilizes isothermal nucleic acid amplification in combination with a lateral flow chromatographic device, or DNA dipstick, for DNA-hybridization detection. The system of the invention requires no complex instrumentation or electronic hardware, and provides a low cost nucleic acid detection system suitable for highly sensitive pathogen detection. Hybridization to single-stranded DNA amplification products using the system of the invention provides a sensitive and specific means by which assays can be multiplexed for the detection of multiple target sequences.

Training system of knowledge society

International Nuclear Information System (INIS)

Ceclan, M.; Ionescu, T.B.; Ceclan, Rodica Elena; Tatar, Florin; Tiron, C.; Georgescu, Luisa Maria

2005-01-01

Full text: The paper aims at presenting the results of Cernavoda NPP Training Department modernization project. In order to achieve a training system of knowledge society in the first stage of the project a Computer Based Training (CBT) or E-Learning platform and several CBT objects/courses were worked out. The conceived E-Learning solution is called CBT Center and it is a complete system offering a variety of teaching and learning services to its users. CBT and/or E-Learning always mean two things: a software platform and content authoring. Ideally, a software platform should be able to import any type of flat documentation and integrate it into a structured database which keeps track of pedagogically meaningful information like the student's progress in studying materials, tests and quiz, marks, etc. At the same time, the materials, the study and the tests have to be organized around certain objectives which play the role of guidelines during the entire educational activity. An example of such a course which has been successfully integrated into CBT Center is the 'Thermodynamics'. CBT technology implementation at NPP Cernavoda Training Department has brought several advantages: the technology improves overall communication between all individuals which are part of the educational process; there is no space problem any more; students can access training materials from their own desk using the NPP intranet; the logistics problem will decrease, while more and more disciplines will be transformed as CBT objects. (authors)

A study of the transferability of influenza case detection systems between two large healthcare systems.

Directory of Open Access Journals (Sweden)

Ye Ye

Full Text Available This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD that use clinical notes from emergency department (ED to detect influenza cases.A BCD uses natural language processing (NLP to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC and Intermountain Healthcare in Utah (BCDIH. At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source institution, development parser, application (target institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance.Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92. When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p<0.01, and BCDIH discriminations declined more (from 0.93 to 0.87, p<0.0001. We attributed the BCDIH decline to the lower recall of the IH parser on UPMC notes. The ANOVA analysis showed five significant factors: development parser, application institution, application parser, BN transfer, and classification task.We demonstrated high influenza case detection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the

π0 detection system

International Nuclear Information System (INIS)

Suzuki, Yoichiro

1977-01-01

A π-zero meson detection system used for the measurement of charge exchange reaction is described. The detection of π-zero is made by observing the coincidence events of two gamma-ray emission following the decay of π-zero meson. The angles of the emitted gamma-rays are detected with a wire spark chamber system, and the energies of the gamma-rays are measured with hodoscope type lead glass Cherenkov counters. In front of the π-zero counter system, a lead converter is set, and the incident gamma-rays convert to electron positron pairs, which can be detected with the wire spark chambers. The system is a multi-track detection system. The high voltage pulser of the wire spark chamber system is a charge line thyratron pulser, and the chamber itself is a transmission line type. Read-out can be made by a mag-line system. Wave forms and efficiencies were measured. The three-track efficiency was about 90% by the condenser method and 95% by the charge line method. (Kato, T.)

Pre-trained convolutional neural networks as feature extractors for tuberculosis detection.

Science.gov (United States)

Lopes, U K; Valiati, J F

2017-10-01

It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died, most of them in developing countries. Many of those deaths could have been prevented if the disease had been detected at an earlier stage, but the most advanced diagnosis methods are still cost prohibitive for mass adoption. One of the most popular tuberculosis diagnosis methods is the analysis of frontal thoracic radiographs; however, the impact of this method is diminished by the need for individual analysis of each radiography by properly trained radiologists. Significant research can be found on automating diagnosis by applying computational techniques to medical images, thereby eliminating the need for individual image analysis and greatly diminishing overall costs. In addition, recent improvements on deep learning accomplished excellent results classifying images on diverse domains, but its application for tuberculosis diagnosis remains limited. Thus, the focus of this work is to produce an investigation that will advance the research in the area, presenting three proposals to the application of pre-trained convolutional neural networks as feature extractors to detect the disease. The proposals presented in this work are implemented and compared to the current literature. The obtained results are competitive with published works demonstrating the potential of pre-trained convolutional networks as medical image feature extractors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Portable modular detection system

Science.gov (United States)

Brennan, James S [Rodeo, CA; Singh, Anup [Danville, CA; Throckmorton, Daniel J [Tracy, CA; Stamps, James F [Livermore, CA

2009-10-13

Disclosed herein are portable and modular detection devices and systems for detecting electromagnetic radiation, such as fluorescence, from an analyte which comprises at least one optical element removably attached to at least one alignment rail. Also disclosed are modular detection devices and systems having an integrated lock-in amplifier and spatial filter and assay methods using the portable and modular detection devices.

Design of an Autonomous Social Orienting Training System (ASOTS) for Young Children With Autism.

Science.gov (United States)

Zheng, Zhi; Fu, Qiang; Zhao, Huan; Swanson, Amy R; Weitlauf, Amy S; Warren, Zachary E; Sarkar, Nilanjan

2017-06-01

Social communication is among the core areas of impairment for children with Autism Spectrum Disorders (ASD). The training of social orientation is important for improving social communication of children with ASD. In recent years, technology-assisted ASD intervention had gained momentum due to its potential advantages in terms of precision, sustainability, flexibility and cost. In this paper, we propose a closed-loop autonomous computer system, named ASOTS, for training social orientation skills to young children with ASD. This system is designed to detect and track a child's attention in response to social orientation bids and help the child towards appropriate social orientation when needed. Response to name, an important social orientation skill, was used to demonstrate the functionality of the proposed system. Ten toddlers with ASD participated in a pilot user study to show whether the system could be used on young children who have been diagnosed with ASD. Another pilot user study with 10 TD infants tested whether this system has a potential to be applied for early detection for infants who were younger than the age when ASD diagnoses can be done. This was done intentionally to separately demonstrate utility and functionality for the clinical population of interest and to demonstrate functionality beyond current clinical identification capacity (i.e., infants). The results showed that the proposed system and the protocol were well tolerated by both groups, successfully captured young children's attention, and elicited the desired behavior.

Information Systems and Management Training.

Science.gov (United States)

Curry, B.; Smith, D. G.

1991-01-01

A case study of a South Wales manufacturer illustrates the need for companies to adopt an integrated strategy for computerization and information systems. Lack of management training blending computing and business skills can have a crippling effect on system development and organizational health. (SK)

Battling the challenges of training nurses to use information systems through theory-based training material design

NARCIS (Netherlands)

M. Galani (Malatsi); P. Yu (Ping); G.W.C. Paas (Fred); P. Chandler (Paul)

2014-01-01

textabstractThe attempts to train nurses to effectively use information systems have had mixed results. One problem is that training materials are not adequately designed to guide trainees to gradually learn to use a system without experiencing a heavy cognitive load. This is because training design

Astro. A multimedia System for training of personnel

International Nuclear Information System (INIS)

Garate Abenza, M.; Mercade Seijas, O.; Munoz, J.F.; Ruiz-Andino, J.L.

1994-01-01

ASTRO is an integrated software package used to train system operators and is directly applicable to all types of power-generation plant operator training. The following are its salient characteristics: - Installed in work stations with multimedia capabilities a user-friendly interface - Covers various types of instruction on theory, procedure and maintenance allowing the execution of trainee-customized courses. - Includes all the phases of the teaching-learning task: compilation or creation and adaptation of course design information, execution and evaluation. - Combines the capabilities of traditional teaching tools, focusing basically on theoretical training, with the power of necessary real-time simulators for the assimilation of operation and maintenance procedures. Moreover, it provides the capacity to extract information instantly from the simulated system, without existing the simulation process. - It is run on inexpensive platforms (work stations) as compared to the traditional system of simulator training or training at site. (Author)

Microcontroller based driver alertness detection systems to detect drowsiness

Science.gov (United States)

Adenin, Hasibah; Zahari, Rahimi; Lim, Tiong Hoo

2018-04-01

The advancement of embedded system for detecting and preventing drowsiness in a vehicle is a major challenge for road traffic accident systems. To prevent drowsiness while driving, it is necessary to have an alert system that can detect a decline in driver concentration and send a signal to the driver. Studies have shown that traffc accidents usually occur when the driver is distracted while driving. In this paper, we have reviewed a number of detection systems to monitor the concentration of a car driver and propose a portable Driver Alertness Detection System (DADS) to determine the level of concentration of the driver based on pixelated coloration detection technique using facial recognition. A portable camera will be placed at the front visor to capture facial expression and the eye activities. We evaluate DADS using 26 participants and have achieved 100% detection rate with good lighting condition and a low detection rate at night.

Leak Detection in Heat Exchangers and Underground Pipelines Using Radiotracers. Material for Education and On-The-Job Training for Practitioners of Radiotracer Technology

International Nuclear Information System (INIS)

2009-01-01

The International Atomic Energy Agency plays a major role in facilitating the transfer of radiotracer technology to developing Member States. The use of radiotracer techniques is well established in many Member States; some hundred radiotracer and end user specialists have been trained in radiotracer techniques and their applications; nearly 50 radiotracer laboratories have been working in this field. The training of radiotracer practitioners is vital for the provision of quality services to industry. Leak detection using radiotracer techniques is probably one of the most widespread applications of radiotracers in industrial troubleshooting. Radiotracer techniques are the most competitive for online leak inspection of heat exchangers and buried pipelines. Radiotracers help in early detection of leaks in heat exchangers and underground transporting pipelines, thus saving money, reducing shutdown time, ensuring safe operation and protecting the environment from pollution. The training course series on leak detection in heat exchangers and underground pipelines using radiotracers addresses the needs of the radiotracer groups and their end users. Besides training purposes, this material will assist radiotracer groups in establishing their quality control and accreditation systems. This training course material is based on lecture notes and practical work delivered by many experts in IAEA-supported activities. In particular, the Technical Cooperation Projects implemented under the Regional Cooperative Agreement (RCA) of the IAEA Member States in the Asia and the Pacific Region have been successful in transferring and implementing radiotracer techniques for leak detection to many end users from oil and gas production, oil refineries and the petrochemical industry. The experience obtained in the RCA Region is presented in the training material illustrated with many case studies carried out in several RCA Member States. Lectures and case studies were reviewed by a number

Phantom-based interactive simulation system for dental treatment training.

Science.gov (United States)

Sae-Kee, Bundit; Riener, Robert; Frey, Martin; Pröll, Thomas; Burgkart, Rainer

2004-01-01

In this paper, we propose a new interactive simulation system for dental treatment training. The system comprises a virtual reality environment and a force-torque measuring device to enhance the capabilities of a passive phantom of tooth anatomy in dental treatment training processes. The measuring device is connected to the phantom, and provides essential input data for generating the graphic animations of physical behaviors such as drilling and bleeding. The animation methods of those physical behaviors are also presented. This system is not only able to enhance interactivity and accessibility of the training system compared to conventional methods but it also provides possibilities of recording, evaluating, and verifying the training results.

An Intelligent System for Aggression De-escalation Training

NARCIS (Netherlands)

Bosse, T.; Gerritsen, C.; de Man, J.

2016-01-01

Artificial Intelligence techniques are increasingly being used to develop smart training applications for professionals in various domains. This paper presents an intelligent training system that enables professionals in the public domain to practice their aggression de-escalation skills. The system

Development of training system to prevent accidents during decommissioning of nuclear facilities

International Nuclear Information System (INIS)

Jeong, Kwanseong; Moon, Jeikwon; Choi, Byungseon; Hyun, Dongjun; Lee, Jonghwan; Kim, Ikjune; Kim, Geunho; Seo, Jaeseok

2014-01-01

Decommissioning workers need familiarization with working environments because working environment is under high radioactivity and work difficulty during decommissioning of nuclear facilities. On-the-job training of decommissioning works could effectively train decommissioning workers but this training approach could consume much costs and poor modifications of scenarios. The efficiency of virtual training system could be much better than that of physical training system. This paper was intended to develop the training system to prevent accidents for decommissioning of nuclear facilities. The requirements for the training system were drawn. The data management modules for the training system were designed. The training system of decommissioning workers was developed on the basis of virtual reality which is flexibly modified. The visualization and measurement in the training system were real-time done according as changes of the decommissioning scenario. It can be concluded that this training system enables the subject to improve his familiarization about working environments and to prevent accidents during decommissioning of nuclear facilities

Development of training system to prevent accidents during decommissioning of nuclear facilities

Energy Technology Data Exchange (ETDEWEB)

Jeong, Kwanseong; Moon, Jeikwon; Choi, Byungseon; Hyun, Dongjun; Lee, Jonghwan; Kim, Ikjune; Kim, Geunho; Seo, Jaeseok [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2014-05-15

Decommissioning workers need familiarization with working environments because working environment is under high radioactivity and work difficulty during decommissioning of nuclear facilities. On-the-job training of decommissioning works could effectively train decommissioning workers but this training approach could consume much costs and poor modifications of scenarios. The efficiency of virtual training system could be much better than that of physical training system. This paper was intended to develop the training system to prevent accidents for decommissioning of nuclear facilities. The requirements for the training system were drawn. The data management modules for the training system were designed. The training system of decommissioning workers was developed on the basis of virtual reality which is flexibly modified. The visualization and measurement in the training system were real-time done according as changes of the decommissioning scenario. It can be concluded that this training system enables the subject to improve his familiarization about working environments and to prevent accidents during decommissioning of nuclear facilities.

Incipient Transient Detection in Reactor Systems: Experimental and Theoretical Investigation

Energy Technology Data Exchange (ETDEWEB)

Lefteri H. Tsoukalas; S.T. Revankar; X Wang; R. Sattuluri

2005-09-27

The main goal of this research was to develop a method for detecting reactor system transients at the earliest possible time through a comprehensive experimental, testing and benchmarking program. This approach holds strong promise for developing new diagnostic technologies that are non-intrusive, generic and highly portable across different systems. It will help in the design of new generation nuclear power reactors, which utilize passive safety systems with a reliable and non-intrusive multiphase flow diagnostic system to monitor the function of the passive safety systems. The main objective of this research was to develop an improved fuzzy logic based detection method based on a comprehensive experimental testing program to detect reactor transients at the earliest possible time, practically at their birth moment. A fuzzy logic and neural network based transient identification methodology and implemented in a computer code called PROTREN was considered in this research and was compared with SPRT (Sequentially Probability Ratio Testing) decision and Bayesian inference. The project involved experiment, theoretical modeling and a thermal-hydraulic code assessment. It involved graduate and undergraduate students participation providing them with exposure and training in advanced reactor concepts and safety systems. In this final report, main tasks performed during the project period are summarized and the selected results are presented. Detailed descriptions for the tasks and the results are presented in previous yearly reports (Revankar et al 2003 and Revankar et al 2004).

Generalized Detectability for Discrete Event Systems

Science.gov (United States)

Shu, Shaolong; Lin, Feng

2011-01-01

In our previous work, we investigated detectability of discrete event systems, which is defined as the ability to determine the current and subsequent states of a system based on observation. For different applications, we defined four types of detectabilities: (weak) detectability, strong detectability, (weak) periodic detectability, and strong periodic detectability. In this paper, we extend our results in three aspects. (1) We extend detectability from deterministic systems to nondeterministic systems. Such a generalization is necessary because there are many systems that need to be modeled as nondeterministic discrete event systems. (2) We develop polynomial algorithms to check strong detectability. The previous algorithms are based on observer whose construction is of exponential complexity, while the new algorithms are based on a new automaton called detector. (3) We extend detectability to D-detectability. While detectability requires determining the exact state of a system, D-detectability relaxes this requirement by asking only to distinguish certain pairs of states. With these extensions, the theory on detectability of discrete event systems becomes more applicable in solving many practical problems. PMID:21691432

Prioritizing Training To Maximize Results: The 3 Box System.

Science.gov (United States)

Kearns, Paul

2003-01-01

Considers fundamentals of effective training and focuses on the evaluation of training. Describes the 3 Box System, which provides a framework for discussing: (1) basic training needs and priorities; (2) added value training, including ROI (return on investment); evaluation; and (3) prioritizing training budgets. (LRW)

Virtual reality negotiation training system with virtual cognitions

NARCIS (Netherlands)

Ding, D.; Burger, F.; Brinkman, W.P.; Neerincx, M.A.

2017-01-01

A number of negotiation training systems have been developed to improve people’s performance in negotiation. They mainly focus on the skills development, and less on negotiation understanding and improving self-efficacy. We propose a virtual reality negotiation training system that exposes users to

GESAT: System for management and evaluation of training programs

International Nuclear Information System (INIS)

Arjona, O.; Venegas, M.; Rodriguez, L.; Lopez, M.

1997-01-01

This paper describe the criteria considered to design the GESAT system, the elements considered to select the relational model, selection of the database language and the main features and possibilities of this system. GESAT allow the management of training programs based on the Systematic Approach to Training. Include the information related with all SAT phases, the results of the job analysis, training plans design, development of materials, training implementation, and the subsequent evaluation

Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation

Directory of Open Access Journals (Sweden)

Iwan Setyawan

2011-12-01

Full Text Available Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.

Management and supervisory training: Changing the culture/system

International Nuclear Information System (INIS)

Martin, L.F.

1991-01-01

Professional development training courses, and a unique promoting appraisal system have been combined in the form of a training matrix and are being used as a culture change agent. This training and system modification is currently being implemented within the Nuclear Materials Processing Division of the Savannah River Site. It is designed to help solve the systems problems of managers and supervisors while enabling subordinates to develop themselves professionally, and starts with a promoting appraisal between a manager and a subordinate. These easy to apply appraisals are becoming an integral part of the business system, and result in giving a manager greater control over business change and greater influence over the work each employee accomplishes

A general-purpose development environment for intelligent computer-aided training systems

Science.gov (United States)

Savely, Robert T.

1990-01-01

Space station training will be a major task, requiring the creation of large numbers of simulation-based training systems for crew, flight controllers, and ground-based support personnel. Given the long duration of space station missions and the large number of activities supported by the space station, the extension of space shuttle training methods to space station training may prove to be impractical. The application of artificial intelligence technology to simulation training can provide the ability to deliver individualized training to large numbers of personnel in a distributed workstation environment. The principal objective of this project is the creation of a software development environment which can be used to build intelligent training systems for procedural tasks associated with the operation of the space station. Current NASA Johnson Space Center projects and joint projects with other NASA operational centers will result in specific training systems for existing space shuttle crew, ground support personnel, and flight controller tasks. Concurrently with the creation of these systems, a general-purpose development environment for intelligent computer-aided training systems will be built. Such an environment would permit the rapid production, delivery, and evolution of training systems for space station crew, flight controllers, and other support personnel. The widespread use of such systems will serve to preserve task and training expertise, support the training of many personnel in a distributed manner, and ensure the uniformity and verifiability of training experiences. As a result, significant reductions in training costs can be realized while safety and the probability of mission success can be enhanced.

VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

Science.gov (United States)

Feng, Lichen; Li, Zunchao; Wang, Yuanfa

2018-02-01

Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.

Energy Systems Training Programs and Certifications Survey White Paper

Energy Technology Data Exchange (ETDEWEB)

Cox, Daryl [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Nimbalkar, Sachin U. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wenning, Thomas J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Thirumaran, Kiran [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Guo, Wei [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2017-02-01

Compressed air system, industrial refrigeration system, chilled water system, pump system, fan system, steam system, process heating system, and combined heat and power system are the major industrial energy systems. By helping enhance knowledge and skills of workforce, training and certification programs on these systems are essential to improve energy efficiency of manufacturing facilities. A literature survey of currently available training and certification programs on these systems was conducted.

The vocational education and training system in Denmark

DEFF Research Database (Denmark)

Cort, Pia; Wiborg, Susanne

2009-01-01

Analysis of developments in vocational education and training systems in Australia, Canada, Denmark, France, Germany, Korea, Mexico, Morocco, the UK and the US.......Analysis of developments in vocational education and training systems in Australia, Canada, Denmark, France, Germany, Korea, Mexico, Morocco, the UK and the US....

Web-based home rehabilitation gaming system for balance training

Directory of Open Access Journals (Sweden)

Oleh Kachmar

2014-06-01

Full Text Available Currently, most systems for virtual rehabilitation and motor training require quite complex and expensive hardware and can be used only in clinical settings. Now, a low-cost rehabilitation game training system has been developed for patients with movement disorders; it is suitable for home use under the distant supervision of a therapist. It consists of a patient-side application installed on a home computer and the virtual rehabilitation Game Server in the Internet. System can work with different input gaming devices connected through USB or Bluetooth, such as a Nintendo Wii balance board, a Nintendo Wii remote, a MS Kinect sensor, and custom made rehabilitation gaming devices based on a joystick. The same games can be used with all training devices. Assessment of the Home Rehabilitation Gaming System for balance training was performed on six patients with Cerebral Palsy, who went through daily training sessions for two weeks. Preliminary results showed balance improvement in patients with Cerebral Palsy after they had completed home training courses. Further studies are needed to establish medical requirements and evidence length.

Signal discrimination of ULF electromagnetic data with using singular spectrum analysis – an attempt to detect train noise

Directory of Open Access Journals (Sweden)

S. Saito

2011-07-01

Full Text Available Electromagnetic phenomena associated with crustal activities have been reported in a wide frequency range (DC-HF. In particular, ULF electromagnetic phenomena are the most promising among them because of the deeper skin depth. However, ULF geoelctromagnetic data are a superposition of signals of different origins. They originated from interactions between the geomagnetic field and the solar wind, leak current by a DC-driven train (train noise, precipitation, and so on. In general, the intensity of electromagnetic signals associated with crustal activity is smaller than the above variations. Therefore, in order to detect a smaller signal, signal discrimination such as noise reduction or identification of noises is very important. In this paper, the singular spectrum analysis (SSA has been performed to detect the DC-driven train noise in geoelectric potential difference data. The aim of this paper is to develop an effective algorithm for the DC-driven train noise detection.

Portable detection system of vegetable oils based on laser induced fluorescence

Science.gov (United States)

Zhu, Li; Zhang, Yinchao; Chen, Siying; Chen, He; Guo, Pan; Mu, Taotao

2015-11-01

Food safety, especially edible oils, has attracted more and more attention recently. Many methods and instruments have emerged to detect the edible oils, which include oils classification and adulteration. It is well known than the adulteration is based on classification. Then, in this paper, a portable detection system, based on laser induced fluorescence, is proposed and designed to classify the various edible oils, including (olive, rapeseed, walnut, peanut, linseed, sunflower, corn oils). 532 nm laser modules are used in this equipment. Then, all the components are assembled into a module (100*100*25mm). A total of 700 sets of fluorescence data (100 sets of each type oil) are collected. In order to classify different edible oils, principle components analysis and support vector machine have been employed in the data analysis. The training set consisted of 560 sets of data (80 sets of each oil) and the test set consisted of 140 sets of data (20 sets of each oil). The recognition rate is up to 99%, which demonstrates the reliability of this potable system. With nonintrusive and no sample preparation characteristic, the potable system can be effectively applied for food detection.

Unmanned Aerial System Four-Dimensional Gunnery Training Device Development

Science.gov (United States)

2017-10-01

Aerial System (UAS) Four-Dimensional Gunnery Training Device: Training Effectiveness Assessment (James & Miller, in press). 31 Technical ...Research Product 2018-05 Unmanned Aerial System Four-Dimensional Gunnery Training Device Development David R. James...for the Department of the Army by Northrop Grumman Corporation. Technical review by Thomas Rhett Graves, Ph.D., U.S. Army Research Institute

Interior intrusion detection systems

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, J.R.; Matter, J.C. (Sandia National Labs., Albuquerque, NM (United States)); Dry, B. (BE, Inc., Barnwell, SC (United States))

1991-10-01

The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs.

Interior intrusion detection systems

International Nuclear Information System (INIS)

Rodriguez, J.R.; Matter, J.C.; Dry, B.

1991-10-01

The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs

Developing an Automated Machine Learning Marine Oil Spill Detection System with Synthetic Aperture Radar

Science.gov (United States)

Pinales, J. C.; Graber, H. C.; Hargrove, J. T.; Caruso, M. J.

2016-02-01

Previous studies have demonstrated the ability to detect and classify marine hydrocarbon films with spaceborne synthetic aperture radar (SAR) imagery. The dampening effects of hydrocarbon discharges on small surface capillary-gravity waves renders the ocean surface "radar dark" compared with the standard wind-borne ocean surfaces. Given the scope and impact of events like the Deepwater Horizon oil spill, the need for improved, automated and expedient monitoring of hydrocarbon-related marine anomalies has become a pressing and complex issue for governments and the extraction industry. The research presented here describes the development, training, and utilization of an algorithm that detects marine oil spills in an automated, semi-supervised manner, utilizing X-, C-, or L-band SAR data as the primary input. Ancillary datasets include related radar-borne variables (incidence angle, etc.), environmental data (wind speed, etc.) and textural descriptors. Shapefiles produced by an experienced human-analyst served as targets (validation) during the training portion of the investigation. Training and testing datasets were chosen for development and assessment of algorithm effectiveness as well as optimal conditions for oil detection in SAR data. The algorithm detects oil spills by following a 3-step methodology: object detection, feature extraction, and classification. Previous oil spill detection and classification methodologies such as machine learning algorithms, artificial neural networks (ANN), and multivariate classification methods like partial least squares-discriminant analysis (PLS-DA) are evaluated and compared. Statistical, transform, and model-based image texture techniques, commonly used for object mapping directly or as inputs for more complex methodologies, are explored to determine optimal textures for an oil spill detection system. The influence of the ancillary variables is explored, with a particular focus on the role of strong vs. weak wind forcing.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2017-10-01

Full Text Available Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD, is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor based on the observations of the researchers about the difference between real (live and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR camera-based finger-vein recognition system using convolutional neural network (CNN to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA for dimensionality reduction of feature space and support vector machine (SVM for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared

Spoof Detection for Finger-Vein Recognition System Using NIR Camera.

Science.gov (United States)

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-10-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN

virtX - a computer based system for training the intrasurgical use of mobile image intensifier systems

Directory of Open Access Journals (Sweden)

Pretschner, Dietrich Peter

2006-11-01

Full Text Available Background and objectives: Currently the correct intrasurgical positioning and adjustment of mobile X-ray image intensifiers (C-arm can be learned theoretically through the use of textbooks, the practical training with the device itself suffers from the lack of visual feedback, i.e. radiographs corresponding to the adjustment of the C-arm. This leads to the question, whether the training of correct operation and adjustment of a C-arm in different operation scenarios can be supported by a C-arm simulation system being part of a CBT system (Computer Based Training. Methods: In co-operation with physicians from accident surgery and radiology the computer-based training system virtX was developed. virtX confronts the user with different exercises of C-arm adjustment and evaluates their execution and the results. These tasks can be created with the help of an authoring tool and can be accomplished by the trainee in different modes: a pure virtual mode and a combined virtual-real mode. In the pure virtual mode the user controls the virtual C-arm in a virtual operating theatre via the graphic-interactive virtX user interface. In the virtual-real mode however the position and orientation of a real C-arm are detected and mapped onto the virtual C-arm. At any time during the completion of an exercise the user can produce a close-to-reality, virtual radiograph and can control all parameters, like the positions of the apertures, X-ray intensity, etc. virtX was used on a three-day course for OR personnel with 120 participants and evaluated using questionnaires.Results: 79 of the participants returned a questionnaire. The average age of the 62 female and 15 male participants (two n.s. was 34 ± 9 years, their professional experience was 8.3 ± 7.6 years. 18 persons (23% indicated to work occasionally with a C-arm, 61 (77% worked regularly with it. Over 83% of the interviewed participants considered virtX a useful addition to the conventional C-arm training

Single particle detecting telescope system

International Nuclear Information System (INIS)

Yamamoto, I.; Tomiyama, T.; Iga, Y.; Komatsubara, T.; Kanada, M.; Yamashita, Y.; Wada, T.; Furukawa, S.

1981-01-01

We constructed the single particle detecting telescope system for detecting a fractionally charged particle. The telescope consists of position detecting counters, wall-less multi-cell chambers, single detecting circuits and microcomputer system as data I/0 processor. Especially, a frequency of double particle is compared the case of the single particle detecting with the case of an ordinary measurement

A Role of the Parasympathetic Nervous System in Cognitive Training.

Science.gov (United States)

Lin, Feng; Heffner, Kathi L; Ren, Ping; Tadin, Duje

2017-01-01

Vision-based speed of processing (VSOP) training can result in broad cognitive improvements in older adults with amnestic mild cognitive impairment (aMCI). What remains unknown, however, is what neurophysiological mechanisms account for the observed training effect. Much of the work in this area has focused on the central nervous system, neglecting the fact that the peripheral system can contributes to changes of the central nervous system and vice versa. We examined the prospective relationship between an adaptive parasympathetic nervous system response to cognitive stimuli and VSOP training-induced plasticity. Twenty-one participants with aMCI (10 for VSOP training, and 11 for mental leisure activities (MLA) control) were enrolled. We assessed high-frequency heart rate variability (HF-HRV) during training sessions, and striatum-related neural networks and cognition at baseline and post-training. Compared to MLA, the VSOP group showed a significant U-shaped pattern of HF-HRV response during training, as well as decreases in connectivity strength between bilateral striatal and prefrontal regions. These two effects were associated with training-induced improvements in both the trained (attention and processing speed) and transferred (working memory) cognitive domains. This work provides novel support for interactions between the central and the peripheral nervous systems in relation to cognitive training, and motivates further studies to elucidate the causality of the observed link. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Rapid deployment intrusion detection system

International Nuclear Information System (INIS)

Graham, R.H.

1997-01-01

A rapidly deployable security system is one that provides intrusion detection, assessment, communications, and annunciation capabilities; is easy to install and configure; can be rapidly deployed, and is reusable. A rapidly deployable intrusion detection system (RADIDS) has many potential applications within the DOE Complex: back-up protection for failed zones in a perimeter intrusion detection and assessment system, intrusion detection and assessment capabilities in temporary locations, protection of assets during Complex reconfiguration, and protection in hazardous locations, protection of assets during Complex reconfiguration, and protection in hazardous locations. Many DOE user-need documents have indicated an interest in a rapidly deployable intrusion detection system. The purpose of the RADIDS project is to design, develop, and implement such a system. 2 figs

Detecting Adulteration in Lotus Honey Using a Machine Olfactory System

Directory of Open Access Journals (Sweden)

M Hajinezhad

2017-10-01

classification of samples. It is based on the variance of the data-set. For PCA analysis, overall PC1 and PC2 explained 91% of the total variance among Lotus honey samples and the adulterations (PC1=80% and PC2=11%. The results indicate that it is clearly possible to recognize Lotus honey with adulterant using electronic nose systems. LDA Results The LDA method for the detection of adulterated honey samples using leave-one-out validation was estimated. The method is most widely used as a method of classification that maximizes variance between the clusters and minimizes variance of within classes. By applying LDA on the collected data, 100% accurate classification for detecting of honey and their adulterations was obtained. It can also be concluded that this method could recognize adulterated honey samples properly. ANN Results The back propagation multilayer perceptron algorithm was used to classify and to detect honey and adulterated types. Performance evaluations of each designed networks were compared by mean square error (MSE and correlation coefficient (r.The data were divided to three subsets: 60% was used for training, 20% for testing and the remaining 20% were kept for cross validation.After network training and validation using optimized ANN model, i.e. 6-8-4 structure, success rate for 4 outputs (0, 20, 35 and 50% adulterated levelswere found to be 100%.After detecting adulteration, e-nose system accompanied with ANN can accurately classify honey from honey mixtures with fraud materials. Conclusions An electronic nose based on six metal oxide semiconductor sensors was used to detect adulterated honey samples. Electronic nose system can successfully classify between original honey and the adulterated one by pattern recognition method. The PCA, LDA and ANN techniques and analyzes of the electronic nose were very useful for evaluating the quality of the lotus honey. The results of these methods were used to classify the fraud in Lotus honey. However, there is a need to

Battle Staff Training System II: Computer-Based Instruction Supporting the Force XXI Training Program

National Research Council Canada - National Science Library

Wampler, Richard

1998-01-01

This report documents the methodology and lessons learned in the development of the Innovative Tools and Techniques for Brigade and Below Staff Training II - Battle Staff Training System II (ITTBBST-BSTS II...

Wildlife detection dog training: A case study on achieving generalization between target odor variations while retaining specificity

NARCIS (Netherlands)

Oldenburg, Cor; Schoon, Adee; Heitkönig, I.M.A.

2016-01-01

Wildlife detection dogs are required to correctly discriminate target wildlife species odor from nontarget
species odors (specificity), while enabling some degree of target odor variation (generality). Because
there is no standardized training protocol, and little knowledge on training

Can GPS be used to detect deleterious progression in training volume among runners?

DEFF Research Database (Denmark)

Nielsen, Rasmus Oestergaard; Cederholm, Jens Peter; Buist, Ida

2013-01-01

There is a need to ascertain if an association exists between excessive progression in weekly volume and development of running-related injuries (RRI). The purpose of this study was to investigate if GPS can be used to detect deleterious progression in weekly training volume among 60 novice runners...... included in a 10-week prospective study. All participants used GPS to quantify training volume while running. In case of injury, participants attended a clinical examination. The 13 runners who sustained injuries during follow-up had a significantly higher weekly progression in total training volume...... in the week before the injury origin (86% [95% confidence interval: 12.9-159.9], p = 0.026) compared with other weeks. Although not significant, participants with injuries had an increase in weekly training volume of 31.6% compared with a 22.1% increase among the healthy participants. The error of the GPS...

An environmental monitoring detection system

International Nuclear Information System (INIS)

Leli Yuniarsari; Istofa; Sukandar

2015-01-01

Is part of radiation detection of the nuclear facilities engineering activities within nuclear facilities. The system comprised of gamma-ray radiation detector and weather detection which includes anemometer to detect the wind direction and speed, as well as rain gauge to measure the rainfall in a period of time. Data acquisition of the output is processed by Arduino Uno system which transformed the data into a particular standard and then displayed online in the website. The radiation detection system uses gamma-ray detector of NaI(Tl) and GM which convert the radiation detected into electric pulse to be fed into a pre-amp and amplifier and modified into square pulse. The weather detection system on the other hand works based on switch principle. For example, the wind with a certain speed could turn on a switch in the system and produce a voltage or pulse which can be measured. This value will then be interpreted as the wind direction and speed. Likewise for the rainfall gauge, the volume of water entering the bucket will turn the switch on, at the same time producing 1 pulse. The result of the experiment shows that for radiation detection system the output is a square pulse 4 volts by using detector NaI(Tl) and 4.4 volts by using detector GM. For weather detection system, basically was able to detect the wind direction, wind speed and rainfall just to find out further research is needed accuracy and the results compared with the standard tools available in BMKG. (author)

Leadership training to improve adenoma detection rate in screening colonoscopy: A randomised trial

NARCIS (Netherlands)

M.F. Kaminski (Michal); J. Anderson (John); R.M. Valori (Roland ); E. Kraszewska (Ewa); M. Rupinski (Maciej); J. Pachlewski (Jacek); E. Wronska (Ewa); M. Bretthauer (Michael); S. Thomas-Gibson (Siwan); E.J. Kuipers (Ernst); J. Regula (J.)

2016-01-01

textabstractObjective Suboptimal adenoma detection rate (ADR) at colonoscopy is associated with increased risk of interval colorectal cancer. It is uncertain how ADR might be improved. We compared the effect of leadership training versus feedback only on colonoscopy quality in a countrywide

Analysis of Train Suspension System Using MR dampers

Science.gov (United States)

RamaSastry, DVA; Ramana, K. V.; Mohan Rao, N.; Siva Kumar, SVR; Priyanka, T. G. L.

2016-09-01

This paper deals with introducing MR dampers to the Train Suspension System for improving the ride comfort of the passengers. This type of suspension system comes under Semi-active suspension system which utilizes the properties of MR fluid to damp the vibrations. In case of high speed trains, the coach body is subjected to vibrations due to vertical displacement, yaw and pitch movements. When the body receives these disturbances from the ground,the transmission of vibrations to the passenger increases which affect the ride comfort. In this work, the equations of motion of suspension system are developed for both conventional passive system and semi-active system and are modelled in Matlab/Simulink and analysis has been carried out. The passive suspension system analysis shows that it is taking more time to damp the vibrations and at the same time the transmissibility of vibrations is more.Introducing MR dampers,vertical and angular displacements of the body are computed and compared. The results show that the introduction of MR dampers into the train suspension system improves ride comfort.

Introducing a feedback training system for guided home rehabilitation

Directory of Open Access Journals (Sweden)

Disselhorst-Klug Catherine

2010-01-01

Full Text Available Abstract As the number of people requiring orthopaedic intervention is growing, individualized physiotherapeutic rehabilitation and adequate postoperative care becomes increasingly relevant. The chances of improvement in the patients condition is directly related to the performance and consistency of the physiotherapeutic exercises. In this paper a smart, cost-effective and easy to use Feedback Training System for home rehabilitation based on standard resistive elements is introduced. This ensures high accuracy of the exercises performed and offers guidance and control to the patient by offering direct feedback about the performance of the movements. 46 patients were recruited and performed standard physiotherapeutic training to evaluate the system. The results show a significant increase in the patient's ability to reproduce even simple physiotherapeutic exercises when being supported by the Feedback Training System. Thus physiotherapeutic training can be extended into the home environment whilst ensuring a high quality of training.

Introducing a feedback training system for guided home rehabilitation.

Science.gov (United States)

Kohler, Fabian; Schmitz-Rode, Thomas; Disselhorst-Klug, Catherine

2010-01-15

As the number of people requiring orthopaedic intervention is growing, individualized physiotherapeutic rehabilitation and adequate postoperative care becomes increasingly relevant. The chances of improvement in the patients condition is directly related to the performance and consistency of the physiotherapeutic exercises.In this paper a smart, cost-effective and easy to use Feedback Training System for home rehabilitation based on standard resistive elements is introduced. This ensures high accuracy of the exercises performed and offers guidance and control to the patient by offering direct feedback about the performance of the movements.46 patients were recruited and performed standard physiotherapeutic training to evaluate the system. The results show a significant increase in the patient's ability to reproduce even simple physiotherapeutic exercises when being supported by the Feedback Training System. Thus physiotherapeutic training can be extended into the home environment whilst ensuring a high quality of training.

Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system.

Science.gov (United States)

Wittmann, Frieder; Held, Jeremia P; Lambercy, Olivier; Starkey, Michelle L; Curt, Armin; Höver, Raphael; Gassert, Roger; Luft, Andreas R; Gonzenbach, Roman R

2016-08-11

The effect of rehabilitative training after stroke is dose-dependent. Out-patient rehabilitation training is often limited by transport logistics, financial resources and a lack of motivation/compliance. We studied the feasibility of an unsupervised arm therapy for self-directed rehabilitation therapy in patients' homes. An open-label, single group study involving eleven patients with hemiparesis due to stroke (27 ± 31.5 months post-stroke) was conducted. The patients trained with an inertial measurement unit (IMU)-based virtual reality system (ArmeoSenso) in their homes for six weeks. The self-selected dose of training with ArmeoSenso was the principal outcome measure whereas the Fugl-Meyer Assessment of the upper extremity (FMA-UE), the Wolf Motor Function Test (WMFT) and IMU-derived kinematic metrics were used to assess arm function, training intensity and trunk movement. Repeated measures one-way ANOVAs were used to assess differences in training duration and clinical scores over time. All subjects were able to use the system independently in their homes and no safety issues were reported. Patients trained on 26.5 ± 11.5 days out of 42 days for a duration of 137 ± 120 min per week. The weekly training duration did not change over the course of six weeks (p = 0.146). The arm function of these patients improved significantly by 4.1 points (p = 0.003) in the FMA-UE. Changes in the WMFT were not significant (p = 0.552). ArmeoSenso based metrics showed an improvement in arm function, a high number of reaching movements (387 per session), and minimal compensatory movements of the trunk while training. Self-directed home therapy with an IMU-based home therapy system is safe and can provide a high dose of rehabilitative therapy. The assessments integrated into the system allow daily therapy monitoring, difficulty adaptation and detection of maladaptive motor patterns such as trunk movements during reaching. Unique identifier: NCT02098135 .

Qualification, certification and training systems of a Japanese nuclear power plant supplier

International Nuclear Information System (INIS)

Yoshijima, S.; Tomita, J.; Yoneda, Y.

1982-01-01

Training and indoctrination of personnel are very important for performing quality assurance activities in nuclear power plants. The paper presents policies, procedures and practices with regard to a training system for site construction workers, a training system for plant operation personnel at a special facility, and services and activities for operating plants. The training system for site workers and technicians offers basic training for all workers, and special training and qualification for field welders, cable-termination workers and non-destructive examination personnel. In addition to the qualification system for field welders applied by the regulatory body, a privat-company qualification system exists. Also, a training centre for BWR operators has been established. This facility has a simulator duplicating the main control room of an actual plant and a computer-assisted instruction system. Standard training courses, short-term basic courses, re-training courses, group training courses and special training courses are held at the training centre. Finally, the services and activities performed by Toshiba Corporation for operating plants are described. These activities of the plant supplier aim at keeping up and further enhancing the safety and reliability of operating plants and mainly consist of: (1) collection and evaluation of plant operation data, with re-evaluation and improvement of systems and components; (2) development of new maintenance techniques; (3) development of measures for reducing annual outage periods; and (4) plant emergency preparedness. (author)

A radiation monitoring system model for the Laguna Verde nuclear power training simulator

International Nuclear Information System (INIS)

Ocampo, M.H.; DeAlbornoz, B.A.

1988-01-01

A model for the Radiation Monitoring System of the Laguna Verde Boiling Water Reactor training simulator is presented. This model comprises enough definitions to assure interactions with the processes related, directly or indirectly, with the transport of radioisotopes. It is capable of following a dynamic behavior of the plant so an operator could be trained to become aware of nuclear radiation hazards. The model is composed of three parts: the electronics for the Process and Area Radiation Monitoring System; a lumped parameter transport model for the most representative radioisotopes; and the interactions with the modeled processes as well as with process not being simulated. The first part represents the radiation monitor controls in the vertical board panels of the nuclear station. The second part allows the carrying of nuclear isotopes between processes. The third part defines the way that the process interacts with the electronics at the point of release to environment or the point of detection. Each part of the model has been tested individually, and the transport model has been incorporated as a part of each process required to simulate nuclear radiation. The model parameters has been calculated using typical BWR nuclear radiation data, and Laguna Verde heat balance data at 100% design power. However, tunning will be necessary once the Simulator is integrated and tested. The tunning allows each detecting channel to behave as expected

Train-to-Ground communications of a Train Control and Monitoring Systems: A simulation platform modelling approach

DEFF Research Database (Denmark)

Bouaziz, Maha; Yan, Ying; Kassab, Mohamed

2018-01-01

wireless technologies, e.g. Wi-Fi and LTE. Different T2G scenarios are defined in order to evaluate the performances of the Mobile Communication Gateway (managing train communications) and Quality of Services (QoS) offered to TCMS applications in the context of various environments (regular train lines......Under the SAFE4RAIL project, we are developing a simulation platform based on a discrete-events network simulator. This platform models the Train-to-Ground (T2G) link in the framework of a system-level simulation of Train Control Management System (TCMS). The modelled T2G link is based on existing...

Expert systems for plant operations training and assistance

International Nuclear Information System (INIS)

Pack, R.W.; Lazar, P.M.; Schmidt, R.V.; Gaddy, C.D.

1988-01-01

The project described in this paper explored the use of expert systems for plant operations training and assistance. Three computer technologies were reviewed: computer-aided instruction, expert systems, and expert training systems (ETS). The technology of CAI has been developed since the early 1960s, and a wide range of applications are available commercially today. Expert systems have been developed primarily as job performance aids, and the number of commercial applications is increasing. A fully developed ETS has models of the trainer and trainee, in addition to a knowledge base

Voltage control on a train system

Science.gov (United States)

Gordon, Susanna P.; Evans, John A.

2004-01-20

The present invention provides methods for preventing low train voltages and managing interference, thereby improving the efficiency, reliability, and passenger comfort associated with commuter trains. An algorithm implementing neural network technology is used to predict low voltages before they occur. Once voltages are predicted, then multiple trains can be controlled to prevent low voltage events. Further, algorithms for managing inference are presented in the present invention. Different types of interference problems are addressed in the present invention such as "Interference During Acceleration", "Interference Near Station Stops", and "Interference During Delay Recovery." Managing such interference avoids unnecessary brake/acceleration cycles during acceleration, immediately before station stops, and after substantial delays. Algorithms are demonstrated to avoid oscillatory brake/acceleration cycles due to interference and to smooth the trajectories of closely following trains. This is achieved by maintaining sufficient following distances to avoid unnecessary braking/accelerating. These methods generate smooth train trajectories, making for a more comfortable ride, and improve train motor reliability by avoiding unnecessary mode-changes between propulsion and braking. These algorithms can also have a favorable impact on traction power system requirements and energy consumption.

Performance measurement system for training simulators. Interim report

International Nuclear Information System (INIS)

Bockhold, G. Jr.; Roth, D.R.

1978-05-01

In the first project phase, the project team has designed, installed, and test run on the Browns Ferry nuclear power plant training simulator a performance measurement system capable of automatic recording of statistical information on operator actions and plant response. Key plant variables and operator actions were monitored and analyzed by the simulator computer for a selected set of four operating and casualty drills. The project has the following objectives: (1) To provide an empirical data base for statistical analysis of operator reliability and for allocation of safety and control functions between operators and automated controls; (2) To develop a method for evaluation of the effectiveness of control room designs and operating procedures; and (3) To develop a system for scoring aspects of operator performance to assist in training evaluations and to support operator selection research. The performance measurement system has shown potential for meeting the research objectives. However, the cost of training simulator time is high; to keep research program costs reasonable, the measurement system is being designed to be an integral part of operator training programs. In the pilot implementation, participating instructors judged the measurement system to be a valuable and objective extension of their abilities to monitor trainee performance

Training and Maintaining System-Wide Reliability in Outcome Management.

Science.gov (United States)

Barwick, Melanie A; Urajnik, Diana J; Moore, Julia E

2014-01-01

The Child and Adolescent Functional Assessment Scale (CAFAS) is widely used for outcome management, for providing real time client and program level data, and the monitoring of evidence-based practices. Methods of reliability training and the assessment of rater drift are critical for service decision-making within organizations and systems of care. We assessed two approaches for CAFAS training: external technical assistance and internal technical assistance. To this end, we sampled 315 practitioners trained by external technical assistance approach from 2,344 Ontario practitioners who had achieved reliability on the CAFAS. To assess the internal technical assistance approach as a reliable alternative training method, 140 practitioners trained internally were selected from the same pool of certified raters. Reliabilities were high for both practitioners trained by external technical assistance and internal technical assistance approaches (.909-.995, .915-.997, respectively). 1 and 3-year estimates showed some drift on several scales. High and consistent reliabilities over time and training method has implications for CAFAS training of behavioral health care practitioners, and the maintenance of CAFAS as a global outcome management tool in systems of care.

Decision process simulation in training systems

International Nuclear Information System (INIS)

Zajtsev, K.S.; Serov, A.A.; Ajnutdinov, V.A.

1984-01-01

One of the approaches to arrangement of training process an automated trainning systems (ATS) based on actjve use of knowledge of experienced operators is presented. Problems of mathematical model simulatjon of decision process by people not having special knowledge in mathematics are considered. A language of solution tables based on indistinct tables is suggested to the used as a simulation language. The problem of automation of decision process simulation in ATS is solued

Spaceflight Systems Training: A Comparison and Contrasting of Techniques for Training Ground Operators and Onboard Crewmembers

Science.gov (United States)

Balmain, Clinton; Fleming, Mark

2009-01-01

When developing techniques and products for instruction on manned spaceflight systems, training organizations are often faced with two very different customers: ground operators and onboard crewmembers. Frequently, instructional development focuses on one of these customers with the assumption that the other s needs will be met by default. Experience teaches us that differing approaches are required when developing training tailored to the specific needs of each customer. As a rule, ground operators require focused instruction on specific areas of expertise. Their knowledge should be of the details of the hardware, software, and operational techniques associated with that system. They often benefit from historical knowledge of how their system has operated over its lifetime. Since several different ground operators may be interfacing with the same system, each individual operator must understand the agreed-to principles by which that system will be run. In contrast, onboard crewmembers require a more broad, hands-on awareness of their operational environment. Their training should be developed with an understanding of the physical environment in which they live and work and the day-to-day tasks they are most likely to perform. Rarely do they require a deep understanding of the details of a system; it is often sufficient to teach them just enough to maintain situational awareness and perform basic tasks associated with maintenance and operation of onboard systems. Crewmembers may also develop unique onboard operational techniques that differ from preceding crews. They should be taught what flexibility they have in systems operations and how their specific habits can be communicated to ground support personnel. This paper will explore the techniques that can be employed when developing training for these unique customers. We will explore the history of International Space Station training development and how past efforts can guide us in creating training for users of

The twilight of the training analysis system.

Science.gov (United States)

Kernberg, Otto F

2014-04-01

This paper briefly reviews challenges to psychoanalysis at this time, including those derived from both external, societal origins and internal psychoanalytic problems. It focuses attention on serious conflicts around psychoanalytic education, and refers to the training analysis system as a central problem determining fundamental constraints on present-day psychoanalytic education. These constraints are examined in some detail, and the general advantages and disadvantages of the training analysis system are outlined. The effects of all these dynamics on the administrative organization of the American Psychoanalytic Association are explored, and a proposal for a fundamental reorganization of our educational system to resolve the correspondent problems is outlined.

Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images

Directory of Open Access Journals (Sweden)

Samina Khalid

2017-01-01

Full Text Available Maculopathy is the excessive damage to macula that leads to blindness. It mostly occurs due to retinal edema (RE, central serous chorioretinopathy (CSCR, or age related macular degeneration (ARMD. Optical coherence tomography (OCT imaging is the latest eye testing technique that can detect these syndromes in early stages. Many researchers have used OCT images to detect retinal abnormalities. However, to the best of our knowledge, no research that presents a fully automated system to detect all of these macular syndromes is reported. This paper presents the world’s first ever decision support system to automatically detect RE, CSCR, and ARMD retinal pathologies and healthy retina from OCT images. The automated disease diagnosis in our proposed system is based on multilayered support vector machines (SVM classifier trained on 40 labeled OCT scans (10 healthy, 10 RE, 10 CSCR, and 10 ARMD. After training, SVM forms an accurate decision about the type of retinal pathology using 9 extracted features. We have tested our proposed system on 2819 OCT scans (1437 healthy, 640 RE, and 742 CSCR of 502 patients from two different datasets and our proposed system correctly diagnosed 2817/2819 subjects with the accuracy, sensitivity, and specificity ratings of 99.92%, 100%, and 99.86%, respectively.

Technological sequence of creating components of the training system of the future officers to the management of physical training

Directory of Open Access Journals (Sweden)

Olkhovy O.M.

2012-09-01

Full Text Available The goal is to determine constructive ways of sequence of constructing components of the training system of the future officers to carry out official questions of managing the physical training in the process of the further military career. The structural logic circuit of the interconnections stages of optimum cycle management and technological sequence of constructing the components of the training system of the future officers to the management of physical training, which provides: definition of requirements to the typical problems of professional activities on the issues of the leadership, organization and conducting of physical training, the creation of the phased system model cadets training, training of the curriculum discipline ″Physical education, special physical training and sport″; model creation and definition of criteria of the integral evaluation of the readiness of the future officers to the management of physical training was determined through the analysis more than thirty documentary and scientific literature.

System Detects Vibrational Instabilities

Science.gov (United States)

Bozeman, Richard J., Jr.

1990-01-01

Sustained vibrations at two critical frequencies trigger diagnostic response or shutdown. Vibration-analyzing electronic system detects instabilities of combustion in rocket engine. Controls pulse-mode firing of engine and identifies vibrations above threshold amplitude at 5.9 and/or 12kHz. Adapted to other detection and/or control schemes involving simultaneous real-time detection of signals above or below preset amplitudes at two or more specified frequencies. Potential applications include rotating machinery and encoders and decoders in security systems.

Nonparametric method for failures detection and localization in the actuating subsystem of aircraft control system

Science.gov (United States)

Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures detection and localization in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on algebraic solvability conditions for the aircraft model identification problem. This makes it possible to significantly increase the efficiency of detection and localization problem solution by completely eliminating errors, associated with aircraft model uncertainties.

Examining the motivators of training transfer in an enterprise systems context

Science.gov (United States)

Arasanmi, Chris Niyi; Wang, William Yu Chung; Singh, Harminder

2017-09-01

Enterprise systems (ES) are large software packages that have been widely adopted, but are complex to deploy. One way to obtain more value from them is to train end-users. However, little is known about the effectiveness of ES training. This study examines post-training behaviour in the ES environment through the concept of training transfer and the theoretical framework of self-determination theory. It proposes that end-users' computer self-efficacy (CSE) and mastery orientation (MO), as well as the perceived ease-of-use (PEOU) of a system, influence their motivation to transfer the skills they have gained during training to their work environment and to use the system. Data was collected from 170 ES end-users, who had previously attended ES training, through a survey. Partial least squares modelling was used to analyse the data, and all of the hypotheses were supported. This study is among the first few studies that investigate the more distal impact of information systems training.

Trip optimization system and method for a train

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ajith Kuttannair; Shaffer, Glenn Robert; Houpt, Paul Kenneth; Movsichoff, Bernardo Adrian; Chan, David So Keung

2017-08-15

A system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives, the system including a locator element to determine a location of the train, a track characterization element to provide information about a track, a sensor for measuring an operating condition of the locomotive consist, a processor operable to receive information from the locator element, the track characterizing element, and the sensor, and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train.

Nuclear power plant personnel training process management system

International Nuclear Information System (INIS)

Arjona Vazquez, Orison; Venegas Bernal, Maria del Carmen; Armeteros Lopez, Ana L.

1996-01-01

The system in charge the management of the training process personnel from a nuclear power plant was designed taking into account all the requirements stated in the training guide for nuclear power plant personnel and their evaluation, which were prepared by the IAEA in 1995 in order to implement the SAT in the training programs for nuclear plant personnel. In the preparations of formats and elements that shape the system, account has been taken of the views expressed in such a guide, in some other bibliography that was consulted, and in the authors own opinion mainly with regard to those issues which the guide does not go deeper into

The computer aided education and training system for accident management

International Nuclear Information System (INIS)

Yoneyama, Mitsuru; Masuda, Takahiro; Kubota, Ryuji; Fujiwara, Tadashi; Sakuma, Hitoshi

2000-01-01

Under severe accident conditions of a nuclear power plant, plant operators and technical support center (TSC) staffs will be under a amount of stress. Therefore, those individuals responsible for managing the plant should promote their understanding about the accident management and operations. Moreover, it is also important to train in ordinary times, so that they can carry out accident management operations effectively on severe accidents. Therefore, the education and training system which works on personal computers was developed by Japanese BWR group (Tokyo Electric Power Co.,Inc., Tohoku Electric Power Co. ,Inc., Chubu Electric Power Co. ,Inc., Hokuriku Electric Power Co.,Inc., Chugoku Electric Power Co.,Inc., Japan Atomic Power Co.,Inc.), and Hitachi, Ltd. The education and training system is composed of two systems. One is computer aided instruction (CAI) education system and the other is education and training system with a computer simulation. Both systems are designed to execute on MS-Windows(R) platform of personal computers. These systems provide plant operators and technical support center staffs with an effective education and training tool for accident management. TEPCO used the simulation system for the emergency exercise assuming the occurrence of hypothetical severe accident, and have performed an effective exercise in March, 2000. (author)

Computer-enhanced laparoscopic training system (CELTS): bridging the gap.

Science.gov (United States)

Stylopoulos, N; Cotin, S; Maithel, S K; Ottensmeye, M; Jackson, P G; Bardsley, R S; Neumann, P F; Rattner, D W; Dawson, S L

2004-05-01

There is a large and growing gap between the need for better surgical training methodologies and the systems currently available for such training. In an effort to bridge this gap and overcome the disadvantages of the training simulators now in use, we developed the Computer-Enhanced Laparoscopic Training System (CELTS). CELTS is a computer-based system capable of tracking the motion of laparoscopic instruments and providing feedback about performance in real time. CELTS consists of a mechanical interface, a customizable set of tasks, and an Internet-based software interface. The special cognitive and psychomotor skills a laparoscopic surgeon should master were explicitly defined and transformed into quantitative metrics based on kinematics analysis theory. A single global standardized and task-independent scoring system utilizing a z-score statistic was developed. Validation exercises were performed. The scoring system clearly revealed a gap between experts and trainees, irrespective of the task performed; none of the trainees obtained a score above the threshold that distinguishes the two groups. Moreover, CELTS provided educational feedback by identifying the key factors that contributed to the overall score. Among the defined metrics, depth perception, smoothness of motion, instrument orientation, and the outcome of the task are major indicators of performance and key parameters that distinguish experts from trainees. Time and path length alone, which are the most commonly used metrics in currently available systems, are not considered good indicators of performance. CELTS is a novel and standardized skills trainer that combines the advantages of computer simulation with the features of the traditional and popular training boxes. CELTS can easily be used with a wide array of tasks and ensures comparability across different training conditions. This report further shows that a set of appropriate and clinically relevant performance metrics can be defined and a

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

Science.gov (United States)

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

An Affordable Microsurgical Training System for a Beginning Neurosurgeon: How to Realize the Self-Training Laboratory.

Science.gov (United States)

Chung, Sang-Bong; Ryu, Jiwook; Chung, Yeongu; Lee, Sung Ho; Choi, Seok Keun

2017-09-01

To provide detailed information about how to realize a self-training laboratory with cost-effective microsurgical instruments, especially pertinent for the novice trainee. Our training model is designed to allow the practice of the microsurgery skills in an efficient and cost-effective manner. A used stereoscopic microscope is prepared for microsurgical training. A sufficient working distance for microsurgical practice is obtained by attaching an auxiliary objective lens. The minimum instrument list includes 2 jeweler's forceps, iris scissors, and alligator clips. The iris scissors and alligator clip provide good alternatives to micro-scissors and microvascular clamp. The short time needed to set up the microscope and suture the gauze with micro-forceps makes the training model suitable for daily practice. It takes about 15 minutes to suture 10 neighboring fibers of the gauze with 10-0 nylon; thus, training can be completed more quickly. We have developed an inexpensive and efficient micro-anastomosis training system using a stereoscopic microscope and minimal micro-instruments. Especially useful for novice trainees, this system provides high accessibility for microsurgical training. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of fast wireless detection system for fixed offshore platform

Science.gov (United States)

Li, Zhigang; Yu, Yan; Jiao, Dong; Wang, Jie; Li, Zhirui; Ou, Jinping

2011-04-01

Offshore platforms' security is concerned since in 1950s and 1960s, and in the early 1980s some important specifications and standards are built, and all these provide technical basis of fixed platform design, construction, installation and evaluation. With the condition that more and more platforms are in serving over age, the research about the evaluation and detection technology of offshore platform has been a hotspot, especially underwater detection, and assessment method based on the finite element calculation. For fixed platform structure detection, conventional NDT methods, such as eddy current, magnetic powder, permeate, X-ray and ultrasonic, etc, are generally used. These techniques are more mature, intuitive, but underwater detection needs underwater robot, the necessary supporting tools of auxiliary equipment, and trained professional team, thus resources and cost used are considerable, installation time of test equipment is long. This project presents a new kind of fast wireless detection and damage diagnosis system for fixed offshore platform using wireless sensor networks, that is, wireless sensor nodes can be put quickly on the offshore platform, detect offshore platform structure global status by wireless communication, and then make diagnosis. This system is operated simply, suitable for offshore platform integrity states rapid assessment. The designed system consists in intelligence acquisition equipment and 8 wireless collection nodes, the whole system has 64 collection channels, namely every wireless collection node has eight 16-bit accuracy of A/D channels. Wireless collection node, integrated with vibration sensing unit, embedded low-power micro-processing unit, wireless transceiver unit, large-capacity power unit, and GPS time synchronization unit, can finish the functions such as vibration data collection, initial analysis, data storage, data wireless transmission. Intelligence acquisition equipment, integrated with high

A knowledge based system for training radiation emergency response personnel

International Nuclear Information System (INIS)

Kuriakose, K.K.; Peter, T.U.; Natarajan, A.

1992-01-01

One of the important aspects of radiation emergency preparedness is to impart training to emergency handling staff. Mock exercises are generally used for this purpose. But practical considerations limit the frequency of such exercises. A suitably designed computer software can be effectively used to impart training. With the advent of low cost personal computers, the frequency with which the training programme can be conducted is unlimited. A computer software with monotonic behaviour is inadequate for such training. It is necessary to provide human like tutoring capabilities. With the advances in knowledge based computer systems, it is possible to develop such a system. These systems have the capability of providing individualized training. This paper describes the development of such a system for training and evaluation of agencies associated with the management of radiation emergency. It also discusses the utility of the software as a general purpose tutor. The details required for the preparation of data files and knowledge base files are included. It uses a student model based on performance measures. The software is developed in C under MS-DOS. It uses a rule based expert system shell developed in C. The features of this shell are briefly described. (author). 5 refs

Particle detection systems and methods

Science.gov (United States)

Morris, Christopher L.; Makela, Mark F.

2010-05-11

Techniques, apparatus and systems for detecting particles such as muons and neutrons. In one implementation, a particle detection system employs a plurality of drift cells, which can be for example sealed gas-filled drift tubes, arranged on sides of a volume to be scanned to track incoming and outgoing charged particles, such as cosmic ray-produced muons. The drift cells can include a neutron sensitive medium to enable concurrent counting of neutrons. The system can selectively detect devices or materials, such as iron, lead, gold, uranium, plutonium, and/or tungsten, occupying the volume from multiple scattering of the charged particles passing through the volume and can concurrently detect any unshielded neutron sources occupying the volume from neutrons emitted therefrom. If necessary, the drift cells can be used to also detect gamma rays. The system can be employed to inspect occupied vehicles at border crossings for nuclear threat objects.

Virtual Reality Simulator Systems in Robotic Surgical Training.

Science.gov (United States)

Mangano, Alberto; Gheza, Federico; Giulianotti, Pier Cristoforo

2018-06-01

The number of robotic surgical procedures has been increasing worldwide. It is important to maximize the cost-effectiveness of robotic surgical training and safely reduce the time needed for trainees to reach proficiency. The use of preliminary lab training in robotic skills is a good strategy for the rapid acquisition of further, standardized robotic skills. Such training can be done either by using a simulator or by exercises in a dry or wet lab. While the use of an actual robotic surgical system for training may be problematic (high cost, lack of availability), virtual reality (VR) simulators can overcome many of these obstacles. However, there is still a lack of standardization. Although VR training systems have improved, they cannot yet replace experience in a wet lab. In particular, simulated scenarios are not yet close enough to a real operative experience. Indeed, there is a difference between technical skills (i.e., mechanical ability to perform a simulated task) and surgical competence (i.e., ability to perform a real surgical operation). Thus, while a VR simulator can replace a dry lab, it cannot yet replace training in a wet lab or operative training in actual patients. However, in the near future, it is expected that VR surgical simulators will be able to provide total reality simulation and replace training in a wet lab. More research is needed to produce more wide-ranging, trans-specialty robotic curricula.

Ferret Workflow Anomaly Detection System

National Research Council Canada - National Science Library

Smith, Timothy J; Bryant, Stephany

2005-01-01

The Ferret workflow anomaly detection system project 2003-2004 has provided validation and anomaly detection in accredited workflows in secure knowledge management systems through the use of continuous, automated audits...

From Training to Learning in Enterprise Resource Planning Systems

Science.gov (United States)

Kerr, Don; Murray, Peter A.; Burgess, Kevin

2012-01-01

The information systems' literature outlines how training is a critical factor to successful Enterprise Resource Planning (ERP) implementations. Yet, types of training are not discussed in the literature and there is little indication if existing training is effective and whether relevant contextual factors have been considered. Without…

Solar system fault detection

Science.gov (United States)

Farrington, R.B.; Pruett, J.C. Jr.

1984-05-14

A fault detecting apparatus and method are provided for use with an active solar system. The apparatus provides an indication as to whether one or more predetermined faults have occurred in the solar system. The apparatus includes a plurality of sensors, each sensor being used in determining whether a predetermined condition is present. The outputs of the sensors are combined in a pre-established manner in accordance with the kind of predetermined faults to be detected. Indicators communicate with the outputs generated by combining the sensor outputs to give the user of the solar system and the apparatus an indication as to whether a predetermined fault has occurred. Upon detection and indication of any predetermined fault, the user can take appropriate corrective action so that the overall reliability and efficiency of the active solar system are increased.

Rapid detection of small oscillation faults via deterministic learning.

Science.gov (United States)

Wang, Cong; Chen, Tianrui

2011-08-01

Detection of small faults is one of the most important and challenging tasks in the area of fault diagnosis. In this paper, we present an approach for the rapid detection of small oscillation faults based on a recently proposed deterministic learning (DL) theory. The approach consists of two phases: the training phase and the test phase. In the training phase, the system dynamics underlying normal and fault oscillations are locally accurately approximated through DL. The obtained knowledge of system dynamics is stored in constant radial basis function (RBF) networks. In the diagnosis phase, rapid detection is implemented. Specially, a bank of estimators are constructed using the constant RBF neural networks to represent the training normal and fault modes. By comparing the set of estimators with the test monitored system, a set of residuals are generated, and the average L(1) norms of the residuals are taken as the measure of the differences between the dynamics of the monitored system and the dynamics of the training normal mode and oscillation faults. The occurrence of a test oscillation fault can be rapidly detected according to the smallest residual principle. A rigorous analysis of the performance of the detection scheme is also given. The novelty of the paper lies in that the modeling uncertainty and nonlinear fault functions are accurately approximated and then the knowledge is utilized to achieve rapid detection of small oscillation faults. Simulation studies are included to demonstrate the effectiveness of the approach.

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.

Science.gov (United States)

Yang, Xin; Liu, Chaoyue; Wang, Zhiwei; Yang, Jun; Min, Hung Le; Wang, Liang; Cheng, Kwang-Ting Tim

2017-12-01

Multi-parameter magnetic resonance imaging (mp-MRI) is increasingly popular for prostate cancer (PCa) detection and diagnosis. However, interpreting mp-MRI data which typically contains multiple unregistered 3D sequences, e.g. apparent diffusion coefficient (ADC) and T2-weighted (T2w) images, is time-consuming and demands special expertise, limiting its usage for large-scale PCa screening. Therefore, solutions to computer-aided detection of PCa in mp-MRI images are highly desirable. Most recent advances in automated methods for PCa detection employ a handcrafted feature based two-stage classification flow, i.e. voxel-level classification followed by a region-level classification. This work presents an automated PCa detection system which can concurrently identify the presence of PCa in an image and localize lesions based on deep convolutional neural network (CNN) features and a single-stage SVM classifier. Specifically, the developed co-trained CNNs consist of two parallel convolutional networks for ADC and T2w images respectively. Each network is trained using images of a single modality in a weakly-supervised manner by providing a set of prostate images with image-level labels indicating only the presence of PCa without priors of lesions' locations. Discriminative visual patterns of lesions can be learned effectively from clutters of prostate and surrounding tissues. A cancer response map with each pixel indicating the likelihood to be cancerous is explicitly generated at the last convolutional layer of the network for each modality. A new back-propagated error E is defined to enforce both optimized classification results and consistent cancer response maps for different modalities, which help capture highly representative PCa-relevant features during the CNN feature learning process. The CNN features of each modality are concatenated and fed into a SVM classifier. For images which are classified to contain cancers, non-maximum suppression and adaptive

Nuclear fuel element leak detection system

International Nuclear Information System (INIS)

John, C.D. Jr.

1978-01-01

Disclosed is a leak detection system integral with a wall of a building used to fabricate nuclear fuel elements for detecting radiation leakage from the nuclear fuel elements as the fuel elements exit the building. The leak detecting system comprises a shielded compartment constructed to withstand environmental hazards extending into a similarly constructed building and having sealed doors on both ends along with leak detecting apparatus connected to the compartment. The leak detecting system provides a system for removing a nuclear fuel element from its fabrication building while testing for radiation leaks in the fuel element

Server application for automated management training system of NPP personnel

International Nuclear Information System (INIS)

Poplavskij, I.A.; Pribysh, P.I.; Karpej, A.L.

2016-01-01

This paper describer the server side of automated management training system. This system will increase the efficiency of planning and accounting training activities, simplifies the collecting the necessary documentation and analysis of the results. (authors)

Comparison of enclosed space detection system with conventional methods

Energy Technology Data Exchange (ETDEWEB)

Kercel, S.W.; Baylor, V.M.; Labaj, L.E.

1997-09-01

Enclosed Space Detection System (ESDS) is a fast, inexpensive, and reliable device for detecting human occupants hidden in vehicles. Operation requires less than two minutes. ESDS is used to foil attempts at smuggling illegal aliens, terrorists, and escaping prisoners. It is being tested at nuclear weapons facilities and has been operated at several prisons and international border crossings. ESDS is the first practical electronic alternative to physical searches of vehicles for hidden passengers. At critical checkpoints, a thorough physical search of a single fully loaded truck requires a team of from two to six people, and may take as long as eight hours. Despite this level of security, experience has shown that the search can occasionally be foiled. Due to the enormous time and expense of thorough physical searches of vehicles, they are seldom conducted at any but the most critical of locations, simply leaving many sites vulnerable to crime and terrorism. Prior to the development of the ESDS, the only other effective alternative to physical search was the use of specially-trained canines, which can be vastly superior to the physical search in both time and accuracy. However, as discussed in this paper, canine inspection is not really a competitive substitute for ESDS because canine reliability (80% at most) is not as high as that of the ESDS (99%+), while the costs, training requirements, and operator skill needed are significantly higher with canines than with the ESDS. In addition, the ESDS has straightforward self-diagnostic tests to ensure the system is operating correctly; such tests are not currently available with either canine or human inspectors. ESDS offers an attractive supplement or alternative to meet current security requirements for vehicle searches at portals at government, nuclear, industrial, and other facilities where concealed persons may pose a threat either by entering or leaving.

Comparison of enclosed space detection system with conventional methods

International Nuclear Information System (INIS)

Kercel, S.W.; Baylor, V.M.; Labaj, L.E.

1997-01-01

Enclosed Space Detection System (ESDS) is a fast, inexpensive, and reliable device for detecting human occupants hidden in vehicles. Operation requires less than two minutes. ESDS is used to foil attempts at smuggling illegal aliens, terrorists, and escaping prisoners. It is being tested at nuclear weapons facilities and has been operated at several prisons and international border crossings. ESDS is the first practical electronic alternative to physical searches of vehicles for hidden passengers. At critical checkpoints, a thorough physical search of a single fully loaded truck requires a team of from two to six people, and may take as long as eight hours. Despite this level of security, experience has shown that the search can occasionally be foiled. Due to the enormous time and expense of thorough physical searches of vehicles, they are seldom conducted at any but the most critical of locations, simply leaving many sites vulnerable to crime and terrorism. Prior to the development of the ESDS, the only other effective alternative to physical search was the use of specially-trained canines, which can be vastly superior to the physical search in both time and accuracy. However, as discussed in this paper, canine inspection is not really a competitive substitute for ESDS because canine reliability (80% at most) is not as high as that of the ESDS (99%+), while the costs, training requirements, and operator skill needed are significantly higher with canines than with the ESDS. In addition, the ESDS has straightforward self-diagnostic tests to ensure the system is operating correctly; such tests are not currently available with either canine or human inspectors. ESDS offers an attractive supplement or alternative to meet current security requirements for vehicle searches at portals at government, nuclear, industrial, and other facilities where concealed persons may pose a threat either by entering or leaving

The training system for technical personnel of producers

International Nuclear Information System (INIS)

Kleiner, E.

1980-01-01

The training system of BBC Mannheim for technical personnel is divided in different activities, according to the different target groups and tenors. Different departments take care of this activities, which supply one another. Problem, training activities and methods are described. (orig.) [de

Computer based training for NPP personnel (interactive communication systems and functional trainers)

International Nuclear Information System (INIS)

Martin, H.D.

1987-01-01

KWU as a manufacturer of thermal and nuclear power plants has extensive customer training obligations within its power plant contracts. In this respect KWU has gained large experience in training of personnel, in the production of training material including video tapes an in the design of simulators. KWU developed interactive communication systems (ICS) for training and retraining purposes with a personal computer operating a video disc player on which video instruction is stored. The training program is edited with the help of a self developed editing system which enables the author to easily enter his instructions into the computer. ICS enables the plant management to better monitor the performance of its personnel through computerized training results and helps to save training manpower. German NPPs differ very much from other designs with respect to a more complex and integrated reactor control system and an additional reactor limitation system. Simulators for such plants therefore have also to simulate these systems. KWU developed a Functional Trainer (FT) which is a replica of the primary system, the auxiliary systems linked to it and the associated control, limitation and protection systems including the influences of the turbine operation and control

The E-learning system used in the civil servants' job-training

Science.gov (United States)

Yang, Rui; Ruan, Jianhai

The Chinese government is pursuing e-learning policies which makes job-training with a knowledge-based society. To explain more fully the important role of the e-learning environment, this article undertakes some typical examples of the governments' job-training under e-learning environment. The main problems in servants' job-training in China are the low quantity in the servants' training, short of restriction, the uniform manner in the training and less fairness and availability of opportunities for educational training. In order to develop the e-learning system, the civil servant's job-training policies are provided and the measures of the effective e-learning system are designed.

Sample Selection for Training Cascade Detectors.

Science.gov (United States)

Vállez, Noelia; Deniz, Oscar; Bueno, Gloria

2015-01-01

Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represent anything except the object of interest. In this respect, the negative set typically contains orders of magnitude more images than the positive set. However, imbalanced training databases lead to biased classifiers. In this paper, we focus our attention on a negative sample selection method to properly balance the training data for cascade detectors. The method is based on the selection of the most informative false positive samples generated in one stage to feed the next stage. The results show that the proposed cascade detector with sample selection obtains on average better partial AUC and smaller standard deviation than the other compared cascade detectors.

Hidden psychiatric morbidity. Part II: Training health care workers in detection: a pre- and post-study at Karanda Mission Hospital.

Science.gov (United States)

Hall, A; Williams, H

1987-11-01

A simple 5-session training program covering basic mental health problems, and instruction in the use of the Harding Self Report Questionaire, was instituted at Karanda Mission Hospital to help medical students recognise hidden psychiatric morbidity in somatically presenting patients. The Harding Self Report Questionaire was used as both a detection and training instrument, together with a Health Staff Rating Scale. Medical Assistants were assessed pre- and post-training on 2 measures--specificity and sensitivity. The training program demonstrated that health care workers can be trained to more accurately detect and diagnose hidden psychiatric disorder in this group of patients. An additional benefit was that workers developed an increased interest in this difficult area of patient care. In a previous study, the prevalence of hidden psychiatric morbidity in a general medical outpatient population in Bindura Provincial was found to be in line with other developing countries (i.e., in excess of 10%) and detection rate by health care workers (4.25%) was low, although comparable to that found in other studies. One of the conclusions reached after the Bindura study was that a simple program was needed to alert workers to recognise underlying psychiatric disorder in somatically presenting patients. With this in mind, the training program was devised and given at Karanda Mission Hospital which is situated about 220 km from Harare, Zimbabwe. It has 120 beds and is staffed by 2 doctors, 3 locally trained SRNs, several American trained SRNs, and 3 locally trained medical assistants. It also runs a nursing school for medical assistants. The hospital serves a population drawn from both subsistence and purchase area farmers, but is less diverse that that of Bindura. The training program was shown to be effective, as demonstrated in the improved accuracy in detection and diagnosis by medical assistants. The improvement post-training is perhaps all the more remarkable when the

A software toolkit for implementing low-cost virtual reality training systems

International Nuclear Information System (INIS)

Louka, Michael N.

1999-04-01

VR is a powerful technology for implementing training systems but better tools are needed to achieve wider usage and acceptance for desktop computer-based training applications. A need has been identified for a software tool kit to support the efficient implementation of well-structured desktop VR training systems. A powerful toolkit for implementing scalable low-cost VR training applications is described in this report (author) (ml)

Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode

Directory of Open Access Journals (Sweden)

Tao Ye

2018-06-01

Full Text Available Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net. It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.

An Instructional Systems Approach or FAA Student Centered Training.

Science.gov (United States)

Federal Aviation Administration (DOT), Washington, DC.

The Federal Aviation Administration (FAA) Academy has been using a systems approach as part of its training program since 1969. This booklet describes the general characteristics of an instructional system and explains the steps the FAA goes through in implementing the approach. These steps are: 1) recognize a need for training, 2) specify the…

Ambient Intelligence Systems for Personalized Sport Training

Directory of Open Access Journals (Sweden)

Daniel González-Jiménez

2010-03-01

Full Text Available Several research programs are tackling the use of Wireless Sensor Networks (WSN at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.. Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.. Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR of the runner in a target range. For each track, the environmental conditions (temperature of the next track, the current athlete condition (HR, and the intrinsic difficulty of the track (slopes influence the performance of the athlete. The decision engine, implemented by means of (m; s-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably.

New Train Run Monitoring system: Getting the most out of an ERTMS level 2 Signalling system

DEFF Research Database (Denmark)

Richter, Troels; Landex, Alex; Andersen, Jonas Lohmann Elkjær

. Rail Net Denmark is currently implementing ERTMS Level 2 signalling systems on the entire long distance network and a CBTC signalling system on the Copenhagen Suburban network. It is unlikely, that the current RDS will be able to function in this environment and especially be capable of taking...... advantage of the additional data delivered by the new systems. The conceptual design of a new RDS has consequently been underway since the start of the signalling program. The vision is to create an automatic system that delivers “perfect train run histories” with a cause for every time loss. The future...... ERTMS Traffic Management System will include a rescheduler: Every time a train leaves its path, a rescheduling is triggered and the train receives a new timetable. As a part of this process, other trains may also be rescheduled. A concept for converting this information into the “perfect train run...

46 CFR 108.405 - Fire detection system.

Science.gov (United States)

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Fire detection system. 108.405 Section 108.405 Shipping... EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and each smoke detection system on a unit must— (1) Be approved by the Commandant; and (2) Have a visual...

Proximity detection system underground

Energy Technology Data Exchange (ETDEWEB)

Denis Kent [Mine Site Technologies (Australia)

2008-04-15

Mine Site Technologies (MST) with the support ACARP and Xstrata Coal NSW, as well as assistance from Centennial Coal, has developed a Proximity Detection System to proof of concept stage as per plan. The basic aim of the project was to develop a system to reduce the risk of the people coming into contact with vehicles in an uncontrolled manner (i.e. being 'run over'). The potential to extend the developed technology into other areas, such as controls for vehicle-vehicle collisions and restricting access of vehicle or people into certain zones (e.g. non FLP vehicles into Hazardous Zones/ERZ) was also assessed. The project leveraged off MST's existing Intellectual Property and experience gained with our ImPact TRACKER tagging technology, allowing the development to be fast tracked. The basic concept developed uses active RFID Tags worn by miners underground to be detected by vehicle mounted Readers. These Readers in turn provide outputs that can be used to alert a driver (e.g. by light and/or audible alarm) that a person (Tag) approaching within their vicinity. The prototype/test kit developed proved the concept and technology, the four main components being: Active RFID Tags to send out signals for detection by vehicle mounted receivers; Receiver electronics to detect RFID Tags approaching within the vicinity of the unit to create a long range detection system (60 m to 120 m); A transmitting/exciter device to enable inner detection zone (within 5 m to 20 m); and A software/hardware device to process & log incoming Tags reads and create certain outputs. Tests undertaken in the laboratory and at a number of mine sites, confirmed the technology path taken could form the basis of a reliable Proximity Detection/Alert System.

Description of training activities and re-training system for nuclear professionals at the Paks Nuclear Power Plant, Hungary

International Nuclear Information System (INIS)

Jambrich, I.; Trampus, P.

1993-01-01

The nuclear power units of Paks, Hungary, have always been operated by Hungarian personnel, from the very beginning. The operator staff of unit 1 acquired its knowledge primarily outside of the country, but since 1983 the overall training process has been run entirely in Hungary, in Paks. This report gives details of present system of training programme in Hungary. The system of training for professionals builds up in vertically linked modules and is job oriented. It begins with theoretical training, followed by programmed on-the-job training which must successfully be finished before a release onto in-company or authority licensing exams for individual job performance

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

Energy Technology Data Exchange (ETDEWEB)

El Hariri, Mohamad [Florida Intl Univ., Miami, FL (United States); Faddel, Samy [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States)

2017-11-01

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted to verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.

An analysis of the medical specialty training system in Spain.

Science.gov (United States)

Freire, José-Manuel; Infante, Alberto; de Aguiar, Adriana Cavalcanti; Carbajo, Pilar

2015-06-02

In this paper, we analyse the medical specialty training system in Spain (the so-called "residency system"). In order to do so, we a) summarize its historical evolution; b) describe the five major architectural pillars on which the system is currently based; c) analyse the special contract of the specialist-in-training; d) discuss the three major challenges for the medical specialist training future: the evolution and expansion of the residency system to other health professions, the issue of grouping specialties with a common core trunk and the continuity of the learning process; and e) draw four conclusions that may be relevant for those who are in the process of developing or revising their own medical specialization systems.

Implementation of a ferromagnetic detection system in a clinical MRI setting

International Nuclear Information System (INIS)

Orchard, L.J.

2015-01-01

Purpose: To evaluate the implementation of a ferromagnetic detection system (FMDS) into a clinical MRI setting. Materials and methods: One thousand patients were considered for MRI safety screening using an FMDS. Equipment used was a Ferroguard ® Screener (Metrasens Ltd, Malvern, Worcestershire, UK). Fully gowned patients rotated 360° in front of the FMDS in a standardized manner following traditional MRI screening methods (the use of a written questionnaire (Fig. B.1) and verbal interview. Results: Final results included 1032 individual screening events performed in 977 patients. There were 922 (94%) initial passes using the FMDS; 34 (4%) failed initial screens but passed a subsequent screen; 21 (2%) failed the initial and subsequent screens. Thus, including all screening events (n = 1032), there were 956 (93%) true negatives (TN); 21 (2%) false positives (FP) and 55 (5%) true positives (TP). No false negatives (FN) were recorded. Therefore, sensitivity was 100% and specificity was 98%. Conclusion: Implementation and correct usage of an FMDS proved to increase safety within a clinical MRI environment by alerting staff to ferromagnetic items or implants not identified using traditional MRI screening methods. An FMDS should be used as an adjunct to these methods. The information in this study pertains to the specific equipment used in this investigation. - Highlights: • Ferromagnetic detection system sensitivity in this study was 100%. • Ferromagnetic detection system specificity in this study was 98%. • The additional screening procedure had little impact on throughput ie additional time taken was minimal. • Staff training, technique and compliance is important in implementing the screening procedures. • The ferromagnetic detection system identified objects that may have demonstrated projectile, heating or artefact effects

A Longitudinal Study of Adenoma Detection Rate in Gastroenterology Fellowship Training.

Science.gov (United States)

Gianotti, Robert J; Oza, Sveta Shah; Tapper, Elliot B; Kothari, Darshan; Sheth, Sunil G

2016-10-01

Current guidelines suggest that a gastroenterology fellow in training needs to perform 140 colonoscopies to achieve competency. Data are limited regarding adenoma detection rate (ADR) in fellowship. To assess how fellow ADR correlates with number of colonoscopies performed. We performed a retrospective study examining consecutive colonoscopies performed by gastroenterology fellows. Fellow ADR before and after the 140 procedure benchmark was compared to colonoscopies performed by attending only with whom these fellows trained. A threshold for ideal procedure count was performed using ROC analysis. We analyzed 2021 average-risk colonoscopies performed by 10 gastroenterology fellows under the supervision of an attending physician. When fellows had performed 140 colonoscopies under attending supervision (p = 0.02). The ADR of fellows who had performed >140 colonoscopies under attending supervision was greater than that of attending-only colonoscopies (36 vs. 25 %, p 325 (male patients) and 539 (female patients) colonoscopies was determined to be ideal for achieving adequate ADR based on ROC analysis. Our data suggest that ADR increases after fellows perform >140 colonoscopies under attending supervision, and thereafter surpasses the ADR of attending-only colonoscopies. Some of the differences may be driven by detection of small adenomas. The findings of this study suggest that a higher threshold for number of colonoscopies performed under attending supervision may be needed to achieve adequate ADR during fellowship prior to independent practice.

Experience of automation failures in training: effects on trust, automation bias, complacency and performance.

Science.gov (United States)

Sauer, Juergen; Chavaillaz, Alain; Wastell, David

2016-06-01

This work examined the effects of operators' exposure to various types of automation failures in training. Forty-five participants were trained for 3.5 h on a simulated process control environment. During training, participants either experienced a fully reliable, automatic fault repair facility (i.e. faults detected and correctly diagnosed), a misdiagnosis-prone one (i.e. faults detected but not correctly diagnosed) or a miss-prone one (i.e. faults not detected). One week after training, participants were tested for 3 h, experiencing two types of automation failures (misdiagnosis, miss). The results showed that automation bias was very high when operators trained on miss-prone automation encountered a failure of the diagnostic system. Operator errors resulting from automation bias were much higher when automation misdiagnosed a fault than when it missed one. Differences in trust levels that were instilled by the different training experiences disappeared during the testing session. Practitioner Summary: The experience of automation failures during training has some consequences. A greater potential for operator errors may be expected when an automatic system failed to diagnose a fault than when it failed to detect one.

29 CFR 1910.164 - Fire detection systems.

Science.gov (United States)

2010-07-01

... 29 Labor 5 2010-07-01 2010-07-01 false Fire detection systems. 1910.164 Section 1910.164 Labor... detection systems. (a) Scope and application. This section applies to all automatic fire detection systems... detection systems and components to normal operating condition as promptly as possible after each test or...

FY1995 study of feedback type gait training system; 1995 nendo feedback gata hoko kuren sochi ni kansuru kenkyu kaihatsu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

The purpose of this project is to develop and demonstrate the utility of feedback type gait training equipment designed for the measurement and evaluation by a walking training of the aged or patient. As similar concepts of walking training, a locomotion in the water for the aged is applied in rehabilitation. Our development of this study established the system of a suspending mechanism which revolves around the prop, and a walking on the circular type force plate by the aged or patient. It is possible to detect a walking reaction force of several patients from force plate simultaneously. And then, the data from force plate makes feedback signal to put up the patient like a buoyancy in the water. Concerning the evaluations of walking pattern a step range, a hanging ratio and a walking speed, etc. are acquired for each patient by the acknowledgment base. This system is actively able to perform a walking training continuously compared with conventional passive gait equipment. (NEDO)

Training Sessions and Materials Present Ways to Improve System Efficiency: OIT Technical Assistance Fact Sheet: Training

International Nuclear Information System (INIS)

Ericksen, E.

1999-01-01

Interested in learning about innovative ways to improve the efficiency of your plant's steam, electric motor, and compressed air systems? This US Department of Energy Office of Industrial Technologies fact sheet offers information regarding training sessions, teleconferences, and various training materials to teach you and your company ways to reduce energy use, save money, and reduce waste and pollution through system optimization

Client application for automated management training system of NPP personnel

International Nuclear Information System (INIS)

Pribysh, P.I.; Poplavskij, I.A.; Karpej, A.L.

2016-01-01

This paper describes the client side of automated management training system. This system will optimize the speed of the organization and quality of the training plan; reduce the time of collecting the necessary documentation and facilitate the analysis of the results. (authors)

Development of a Virtual Reality (VR) system for nuclear security training

International Nuclear Information System (INIS)

Yamaguchi, Yasuo; Hanai, Tasuku

2014-01-01

The Integrated Support Center for Nuclear nonproliferation and Nuclear Security (ISCN) under the Japan Atomic Energy Agency (JAEA) began the development of Virtual Reality (VR) training system for the purpose of teaching trainees nuclear security. ISCN set up two VR training courses by 2013. One is for teaching a nuclear security system of nuclear plants. The VR training system allows trainees to have virtual experiences visiting a nuclear plant. Through these experiences, trainees are able to learn how physical protection systems work in the plant. The course focuses on learning fundamental knowledge and is suitable for trainees having little experiences in the field of nuclear security. The other is for teaching fundamental skills corresponding to a contingency plan in a Central Alarm Station (CAS) of nuclear power plant. Computers of the VR training system deploy an intrusion scenario in a virtual space. Trainees in a group sit in front of 3-D screens and play a role play game in a virtual CAS. Through the exercise, trainees are able to learn skills necessary to the contingency case of nuclear plants. In my presentation, I will introduce the two training courses, advantages and disadvantages of the VR training system, reactions of trainees and future plans. (author)

Modular training as technology of professional skills development of mechanical engineers

OpenAIRE

Shamshina Irina

2016-01-01

There are main provisions of modular training program by “Theory of Automatic Control” for students of technical universities is treating. Analyze of advantages and disadvantages of modular training system in comparison with the traditional system in the formation of future engineers’ professional skills. Detection of changes in the level of learning, basic skills and motivational sphere of students en-rolled in the modular training program.

Wireless sensor node for detection of freight train derailment

Science.gov (United States)

Costa, Andrea; Milani, Damiano; Resta, Ferruccio; Tomasini, Gisella

2016-04-01

The target of the research activity presented in this paper is to design, to realize and to test an autonomous sensor node able to measure the accelerations in correspondence of the axle box of a freight train. The final goal of the sensor is to identify the derailment conditions by observing the variations in the spectra of the box accelerations, around the frequencies associated to the wheel revolution and its multiples. The sensor node embeds an accelerometer, a microprocessor, a transmission system, a piezoelectric bimorph energy harvester and an integrated circuit for managing the power distribution to each component of the node. In particular, a mechanical filter to be applied to the node was specifically designed to increment the energy recovered by the harvester and to filter out the high frequency components of the axle-box acceleration, allowing the use of a more sensitive accelerometer. The harvesting system was setup by means of laboratory tests carried out with an electromechanical shaker and the sensor node was finally tested through field tests on freight trains.

Sample Selection for Training Cascade Detectors.

Directory of Open Access Journals (Sweden)

Noelia Vállez

Full Text Available Automatic detection systems usually require large and representative training datasets in order to obtain good detection and false positive rates. Training datasets are such that the positive set has few samples and/or the negative set should represent anything except the object of interest. In this respect, the negative set typically contains orders of magnitude more images than the positive set. However, imbalanced training databases lead to biased classifiers. In this paper, we focus our attention on a negative sample selection method to properly balance the training data for cascade detectors. The method is based on the selection of the most informative false positive samples generated in one stage to feed the next stage. The results show that the proposed cascade detector with sample selection obtains on average better partial AUC and smaller standard deviation than the other compared cascade detectors.

Fluorescence detection system for microfluidic droplets

Science.gov (United States)

Chen, Binyu; Han, Xiaoming; Su, Zhen; Liu, Quanjun

2018-05-01

In microfluidic detection technology, because of the universality of optical methods in laboratory, optical detection is an attractive solution for microfluidic chip laboratory equipment. In addition, the equipment with high stability and low cost can be realized by integrating appropriate optical detection technology on the chip. This paper reports a detection system for microfluidic droplets. Photomultiplier tubes (PMT) is used as a detection device to improve the sensitivity of detection. This system improves the signal to noise ratio by software filtering and spatial filter. The fluorescence intensity is proportional to the concentration of the fluorescence and intensity of the laser. The fluorescence micro droplets of different concentrations can be distinguished by this system.

Train flow chaos analysis based on an improved cellular automata model

International Nuclear Information System (INIS)

Meng, Xuelei; Xiang, Wanli; Jia, Limin; Xu, Jie

2015-01-01

To control the chaos in the railway traffic flow and offer valuable information for the dispatchers of the railway system, an improved cellular model is presented to detect and analyze the chaos in the traffic flow. We first introduce the working mechanism of moving block system, analyzing the train flow movement characteristics. Then we improve the cellular model on the evolution rules to adjust the train flow movement. We give the train operation steps from three cases: the trains running on a railway section, a train will arrive in a station and a train will departure from a station. We simulate 4 trains to run on a high speed section fixed with moving block system and record the distances between the neighbor trains and draw the Poincare section to analyze the chaos in the train operation. It is concluded that there is not only chaos but order in the train operation system with moving blocking system and they can interconvert to each other. The findings have the potential value in train dispatching system construction and offer supporting information for the daily dispatching work.

Quantization and training of object detection networks with low-precision weights and activations

Science.gov (United States)

Yang, Bo; Liu, Jian; Zhou, Li; Wang, Yun; Chen, Jie

2018-01-01

As convolutional neural networks have demonstrated state-of-the-art performance in object recognition and detection, there is a growing need for deploying these systems on resource-constrained mobile platforms. However, the computational burden and energy consumption of inference for these networks are significantly higher than what most low-power devices can afford. To address these limitations, this paper proposes a method to train object detection networks with low-precision weights and activations. The probability density functions of weights and activations of each layer are first directly estimated using piecewise Gaussian models. Then, the optimal quantization intervals and step sizes for each convolution layer are adaptively determined according to the distribution of weights and activations. As the most computationally expensive convolutions can be replaced by effective fixed point operations, the proposed method can drastically reduce computation complexity and memory footprint. Performing on the tiny you only look once (YOLO) and YOLO architectures, the proposed method achieves comparable accuracy to their 32-bit counterparts. As an illustration, the proposed 4-bit and 8-bit quantized versions of the YOLO model achieve a mean average precision of 62.6% and 63.9%, respectively, on the Pascal visual object classes 2012 test dataset. The mAP of the 32-bit full-precision baseline model is 64.0%.

Tritium Systems Test Assembly operator training program

International Nuclear Information System (INIS)

Kerstiens, F.L.

1985-01-01

Proper operator training is needed to help ensure the safe operation of fusion facilities by personnel who are qualified to carry out their assigned responsibilities. Operators control and monitor the Tritium Systems Test Assembly (TSTA) during normal, emergency, and maintenance phases. Their performance is critical both to operational safety, assuring no release of tritium to the atmosphere, and to the successful simulation of the fusion reaction progress. Through proper training we are helping assure that TSTA facility operators perform their assignments in a safe and efficient manner and that the operators maintain high levels of operational proficiency through continuing training, retraining, requalification, and recertification

A neuro-fuzzy inference system for sensor failure detection using wavelet denoising, PCA and SPRT

International Nuclear Information System (INIS)

Na, Man Gyun

2001-01-01

In this work, a neuro-fuzzy inference system combined with the wavelet denoising, PCA(principal component analysis) and SPRT (sequential probability ratio test) methods is developed to detect the relevant sensor failure using other sensor signals. The wavelet denoising technique is applied to remove noise components in input signals into the neuro-fuzzy system. The PCA is used to reduce the dimension of an input space without losing a significant amount of information, The PCA makes easy the selection of the input signals into the neuro-fuzzy system. Also, a lower dimensional input space usually reduces the time necessary to train a neuro-fuzzy system. The parameters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The residuals between the estimated signals and the measured signals are used to detect whether the sensors are failed or not. The SPRT is used in this failure detection algorithm. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level and the hot-leg flowrate sensors in pressurized water reactors

Damage Detection and Deteriorating Structural Systems

DEFF Research Database (Denmark)

Long, Lijia; Thöns, Sebastian; Döhler, Michael

2017-01-01

This paper addresses the quantification of the value of damage detection system and algorithm information on the basis of Value of Information (VoI) analysis to enhance the benefit of damage detection information by providing the basis for its optimization before it is performed and implemented....... The approach of the quantification the value of damage detection information builds upon the Bayesian decision theory facilitating the utilization of damage detection performance models, which describe the information and its precision on structural system level, facilitating actions to ensure the structural...... detection information is determined utilizing Bayesian updating. The damage detection performance is described with the probability of indication for different component and system damage states taking into account type 1 and type 2 errors. The value of damage detection information is then calculated...

Systematic Approach to Training for System Engineers in Nuclear Power Plants

Energy Technology Data Exchange (ETDEWEB)

Kwak, Jeong-keun [Korea Hydro and Nuclear Power Co., Ulsan (Korea, Republic of)

2015-10-15

In my paper, comprehensive preparations, tangible applications, and final establishments of training for system engineers are described using practical materials in KHNP. The purpose of this paper is to formulate SAT based training in KHNP, especially for system engineers. Hence, to achieve this goal, over one year study was performed considering voluminous materials and working experiences. Through the process, SAT based training package for system engineers was finished, in the end. In terms of training in NPPs, SAT methodology is the unwavering trend in South Korea since NPPs export to UAE. Therefore, materialization of SAT based training for system engineers from the origin of SAT to the finalization of SAT should not be overlooked. A variety of accident preventive approaches have been adopted since the first commercial NPP operation in Calder Hall, United Kingdom. Among diverse event preventive ways, training has played an important role for the improvement of NPPs reliability and safety. This is reason why nuclear industry in every country has established and maintained own training institutes and methods. Since the Three Mile Island (TMI) accident, United States Nuclear Regulatory Commission (USNRC) recommended many betterment plans to US nuclear industry for the elevation of NPPs safety. In the suggested considerations, systematic approach to training, so called SAT appeared in the world. Basically, SAT is composed of five stages, what is called ADDIE. Hence, through ADDIE process, holistic and trustworthy training could be realized in the actual NPPs operation and maintenance. For this reason, SAT is the representative training methodology in the US nuclear business.

Systematic Approach to Training for System Engineers in Nuclear Power Plants

International Nuclear Information System (INIS)

Kwak, Jeong-keun

2015-01-01

In my paper, comprehensive preparations, tangible applications, and final establishments of training for system engineers are described using practical materials in KHNP. The purpose of this paper is to formulate SAT based training in KHNP, especially for system engineers. Hence, to achieve this goal, over one year study was performed considering voluminous materials and working experiences. Through the process, SAT based training package for system engineers was finished, in the end. In terms of training in NPPs, SAT methodology is the unwavering trend in South Korea since NPPs export to UAE. Therefore, materialization of SAT based training for system engineers from the origin of SAT to the finalization of SAT should not be overlooked. A variety of accident preventive approaches have been adopted since the first commercial NPP operation in Calder Hall, United Kingdom. Among diverse event preventive ways, training has played an important role for the improvement of NPPs reliability and safety. This is reason why nuclear industry in every country has established and maintained own training institutes and methods. Since the Three Mile Island (TMI) accident, United States Nuclear Regulatory Commission (USNRC) recommended many betterment plans to US nuclear industry for the elevation of NPPs safety. In the suggested considerations, systematic approach to training, so called SAT appeared in the world. Basically, SAT is composed of five stages, what is called ADDIE. Hence, through ADDIE process, holistic and trustworthy training could be realized in the actual NPPs operation and maintenance. For this reason, SAT is the representative training methodology in the US nuclear business

A Hybrid Vision-Map Method for Urban Road Detection

Directory of Open Access Journals (Sweden)

Carlos Fernández

2017-01-01

Full Text Available A hybrid vision-map system is presented to solve the road detection problem in urban scenarios. The standardized use of machine learning techniques in classification problems has been merged with digital navigation map information to increase system robustness. The objective of this paper is to create a new environment perception method to detect the road in urban environments, fusing stereo vision with digital maps by detecting road appearance and road limits such as lane markings or curbs. Deep learning approaches make the system hard-coupled to the training set. Even though our approach is based on machine learning techniques, the features are calculated from different sources (GPS, map, curbs, etc., making our system less dependent on the training set.

Superfund Hazard Ranking System Training Course

Science.gov (United States)

The Hazard Ranking System (HRS) training course is a four and ½ day, intermediate-level course designed for personnel who are required to compile, draft, and review preliminary assessments (PAs), site inspections (SIs), and HRS documentation records/packag

Gas detection system

International Nuclear Information System (INIS)

Allan, C.J.; Bayly, J.G.

1975-01-01

The gas detection system provides for the effective detection of gas leaks over a large area. It includes a laser which has a laser line corresponding to an absorption line of the gas to be detected. A He-Xe laser scans a number of retroreflectors which are strategically located around a D 2 O plant to detect H 2 S leaks. The reflected beam is focused by a telescope, filtered, and passed into an infrared detector. The laser may be made to emit two frequencies, one of which corresponds with an H 2 S absorption line; or it may be modulated on and off the H 2 S absorption line. The relative amplitude of the absorbed light will be a measure of the H 2 S present

Launch team training system

Science.gov (United States)

Webb, J. T.

1988-01-01

A new approach to the training, certification, recertification, and proficiency maintenance of the Shuttle launch team is proposed. Previous training approaches are first reviewed. Short term program goals include expanding current training methods, improving the existing simulation capability, and scheduling training exercises with the same priority as hardware tests. Long-term goals include developing user requirements which would take advantage of state-of-the-art tools and techniques. Training requirements for the different groups of people to be trained are identified, and future goals are outlined.

Validation, verification and evaluation of a Train to Train Distance Measurement System by means of Colored Petri Nets

International Nuclear Information System (INIS)

Song, Haifeng; Liu, Jieyu; Schnieder, Eckehard

2017-01-01

Validation, verification and evaluation are necessary processes to assure the safety and functionality of a system before its application in practice. This paper presents a Train to Train Distance Measurement System (TTDMS), which can provide distance information independently from existing onboard equipment. Afterwards, we proposed a new process using Colored Petri Nets to verify the TTDMS system functional safety, as well as to evaluate the system performance. Three main contributions are carried out in the paper: Firstly, this paper proposes a formalized TTDMS model, and the model correctness is validated using state space analysis and simulation-based verification. Secondly, corresponding checking queries are proposed for the purpose of functional safety verification. Further, the TTDMS performance is evaluated by applying parameters in the formal model. Thirdly, the reliability of a functional prototype TTDMS is estimated. It is found that the procedure can cooperate with the system development, and both formal and simulation-based verifications are performed. Using our process to evaluate and verify a system is easier to read and more reliable compared to executable code and mathematical methods. - Highlights: • A new Train to Train Distance Measurement System. • New approach verifying system functional safety and evaluating system performance by means of CPN. • System formalization using the system property concept. • Verification of system functional safety using state space analysis. • Evaluation of system performance applying simulation-based analysis.

An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening

Science.gov (United States)

Wang, Weiya; Jia, Mengyu; Gao, Feng; Yang, Lihong; Qu, Pengpeng; Zou, Changping; Liu, Pengxi; Zhao, Huijuan

2015-02-01

The cervical cancer screening at a pre-cancer stage is beneficial to reduce the mortality of women. An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening is introduced in this paper. In this system, three electrodes alternately discharge to the cervical tissue and three light emitting diodes in different wavelengths alternately irradiate the cervical tissue. Then the relative optical reflectance and electrical voltage attenuation curve are obtained by optical and electrical detection, respectively. The system is based on DSP to attain the portable and cheap instrument. By adopting the relative reflectance and the voltage attenuation constant, the classification algorithm based on Support Vector Machine (SVM) discriminates abnormal cervical tissue from normal. We use particle swarm optimization to optimize the two key parameters of SVM, i.e. nuclear factor and cost factor. The clinical data were collected on 313 patients to build a clinical database of tissue responses under optical and electrical stimulations with the histopathologic examination as the gold standard. The classification result shows that the opto-electronic joint detection has higher total coincidence rate than separate optical detection or separate electrical detection. The sensitivity, specificity, and total coincidence rate increase with the increasing of sample numbers in the training set. The average total coincidence rate of the system can reach 85.1% compared with the histopathologic examination.

Training Requirements and Information Management System. Software user guide

Energy Technology Data Exchange (ETDEWEB)

Cillan, T.F.; Hodgson, M.A.

1992-05-01

This is the software user`s guide for the Training Requirements and Information Management System. This guide defines and describes the software operating procedures as they apply to the end user of the software program. This guide is intended as a reference tool for the user who already has an indepth knowledge of the Training Requirements and Information Management System functions and data reporting requirement.

Ukrainian National System of MC&A Training on Regular Basis at the George Kuzmych Training Center

International Nuclear Information System (INIS)

Kyryshchuk, V.; Gavrilyuk, V.; Drapey, S.; Romanova, O.; Levina, E.; Proskurin, D.; Gavrilyuk-Burakova, A.; Parkhomenko, V.; Van Dassen, L.; Delalic, Z.

2015-01-01

The George Kuzmych Training Center (GKTC) was created at the Kyiv Institute for Nuclear Research as a result of collaborative efforts between the United States and Ukraine in 1998. Later the European Commission (EC) and Sweden joined the USA supporting MC&A aspects of the GKTC activity. The GKTC was designated by the Ukrainian Government to provide the MPC&A training and methodological assistance to nuclear facilities and nuclear specialists. In order to increase the efficiency of State MC&A system an essential number of new regulations, norms and rules was developed demanding regular and more intensive MC&A experts training from the Regulatory Body of Ukraine and all nuclear facilities. For this purpose ten training courses were developed by the GKTC under the EC contract taking into account both specifics of Ukrainian nuclear facilities and expertise level of their personnel. Along with the NDA training laboratory created with the US DOE financial support and methodological assistance in 2003, a new surveillance and containment laboratory was created under the EC contract and with US DOE financial support as well. Moreover, under the EC contract the laboratory was equipped with the state-of-the-art and most advanced means of surveillance and containment strengthening even more the GKTC training opportunities. As a result, the MC&A experts from all nuclear facilities and Regulatory Body of Ukraine can regularly be trained practically on all MC&A issues. This paper briefly describes the practical efforts applied to improve Ukrainian MC&A systems both at the State and facility levels and real results on the way to develop the National System for MC&A regular training at the GKTC, problems encountered and their solution, comments, suggestions and recommendations for the future activity to promote and improve the nuclear security culture in Ukraine. (author)

Headmasters Training for Creating the In-School Quality Management System

Directory of Open Access Journals (Sweden)

M. A. Desyateritchenko

2012-01-01

Full Text Available The paper looks at the issue of the further professional training of educational staff for developing quality management systems. Mastering the qualitative educational practices provides the effective school training quality assessment, as well as optimization of staff, material, technical and financial resources, and consideration of the requirements of educational process participants. The peculiarities of the quality management penetration into the general educational sphere are analyzed. The factors obstructing the innovative experience spreading are denoted along with the corresponding ways of experimental practices. The content and organizational technological aspects of headmasters and teaching staff readiness for implementing the above innovation in the system of further professional training are defined. The stages of a lyceum readiness for certification of in-school quality management system according to the international standard ISO 9001:2008 are described. The author points out the necessity of developing the training system for managerial and teaching staff with regard to the person oriented and humanity approach. 

Semiconductor radiation detection systems

CERN Document Server

2010-01-01

Covers research in semiconductor detector and integrated circuit design in the context of medical imaging using ionizing radiation. This book explores other applications of semiconductor radiation detection systems in security applications such as luggage scanning, dirty bomb detection and border control.

B-1 Systems Approach to Training. Simulation Technology Assessment Report (STAR)

Science.gov (United States)

1975-07-01

Psychology in the Air Force, 1974. Creelman , J.A., Evaluation of Approach Training Procedures, U.S. Naval School of Aviation Med., Proj. No. NM001-109-107...training. 3.2 PHYSICAL VERSUS PSYCHOLOGICAL SIMULATION In the previous section, the term "physical simulation" was used to represent the case where... psychology that there is no "step function" threshold. Rather, detection capability plotted against phys- ical parameter strength results in an ogival

Real-time petroleum spill detection system

International Nuclear Information System (INIS)

Dakin, D.T.

2001-01-01

A real-time autonomous oil and fuel spill detection system has been developed to rapidly detect of a wide range of petroleum products floating on, or suspended in water. The system consists of an array of spill detection buoys distributed within the area to be monitored. The buoys are composed of a float and a multispectral fluorometer, which looks up through the top 5 cm of water to detect floating and suspended petroleum products. The buoys communicate to a base station computer that controls the sampling of the buoys and analyses the data from each buoy to determine if a spill has occurred. If statistically significant background petroleum levels are detected, the system raises an oil spill alarm. The system is useful because early detection of a marine oil spill allows for faster containment, thereby minimizing the contaminated area and reducing cleanup costs. This paper also provided test results for biofouling, various petroleum product detection, water turbidity and wave tolerance. The technology has been successfully demonstrated. The UV light source keeps the optic window free from biofouling, and the electronics are fully submerged so there is no risk that the unit could ignite the vapours of a potential oil spill. The system can also tolerate moderately turbid waters and can therefore be used in many rivers, harbours, water intakes and sumps. The system can detect petroleum products with an average thickness of less than 3 micrometers floating on the water surface. 3 refs., 15 figs

A coupled classification - evolutionary optimization model for contamination event detection in water distribution systems.

Science.gov (United States)

Oliker, Nurit; Ostfeld, Avi

2014-03-15

This study describes a decision support system, alerts for contamination events in water distribution systems. The developed model comprises a weighted support vector machine (SVM) for the detection of outliers, and a following sequence analysis for the classification of contamination events. The contribution of this study is an improvement of contamination events detection ability and a multi-dimensional analysis of the data, differing from the parallel one-dimensional analysis conducted so far. The multivariate analysis examines the relationships between water quality parameters and detects changes in their mutual patterns. The weights of the SVM model accomplish two goals: blurring the difference between sizes of the two classes' data sets (as there are much more normal/regular than event time measurements), and adhering the time factor attribute by a time decay coefficient, ascribing higher importance to recent observations when classifying a time step measurement. All model parameters were determined by data driven optimization so the calibration of the model was completely autonomic. The model was trained and tested on a real water distribution system (WDS) data set with randomly simulated events superimposed on the original measurements. The model is prominent in its ability to detect events that were only partly expressed in the data (i.e., affecting only some of the measured parameters). The model showed high accuracy and better detection ability as compared to previous modeling attempts of contamination event detection. Copyright © 2013 Elsevier Ltd. All rights reserved.

46 CFR 108.411 - Smoke detection system.

Science.gov (United States)

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Smoke detection system. 108.411 Section 108.411 Shipping... EQUIPMENT Fire Extinguishing Systems § 108.411 Smoke detection system. Each smoke accumulator in a smoke detection system must be located on the overhead of the compartment protected by the system in a location...

Training-induced improvement of response selection and error detection in aging assessed by task switching: effects of cognitive, physical, and relaxation training.

Science.gov (United States)

Gajewski, Patrick D; Falkenstein, Michael

2012-01-01

Cognitive control functions decline with increasing age. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in changes of cognitive functions, as measured in electrophysiological brain activity (event-related potentials). One hundred forty-one healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength training), cognitive training (paper-pencil and computer-aided), relaxation and wellness (social control group), and a control group that did not receive any intervention. Training sessions took place twice a week for 90 min for a period of 4 months. The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task sets in working memory, and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials which showed higher amplitudes in a number of potentials associated with response selection (N2), allocation of cognitive resources (P3b), and error detection (Ne). Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods.

Development of a totally integrated severe accident training system

International Nuclear Information System (INIS)

Kim, Ko Ryu; Park, Sun Hee; Choi, Young; Kim, Dong Ha

2006-01-01

Recently KAERI has developed the severe accident management guidance to establish the Korea standard severe accident management system. On the other hand the PC-based severe accident training simulator SATS has been developed, which uses the MELCOR code as the simulation engine. The simulator SATS graphically displays and simulates the severe accidents with interactive user commands. Especially the control capability of SATS could make a severe accident training course more interesting and effective. In this paper we will describe the development and functions of the electrical guidance module, HyperKAMG, and the SATS-HyperKAMG linkage system designed for a totally integrated and automated severe accident training. (author)

GTRI Remote Monitoring System: Training and Operational Needs Assessment Analysis Report

Energy Technology Data Exchange (ETDEWEB)

Day, Debra E.; Fox, Sorcha

2012-04-20

The mission of the United States Department of Energy (DOE) National Nuclear Security Administrations (NNSA's) Global Threat Reduction Initiative (GTRI) is to identify, secure, recover and facilitate the disposition of vulnerable nuclear and high-risk radioactive materials around the world that pose a threat to the United States and the international community. The GTRI's unique mission to reduce and protect vulnerable nuclear and radiological materials located at civilian sites worldwide directly addresses recommendations of the 9/11 Commission1, and is a vital part of the President's National Security Strategy and the Global Initiative. The GTRI Remote Monitoring System (RMS) is a standalone security system that includes radiation and tamper alarms, and CCTV; which can be transmitted securely over the Internet to multiple on-site and off-site locations. Through our experiences during installation of the system at 162 sites, plus feedback received from Alarm Response Training course participants, site input to project teams and analysis of trouble calls; indications were that current system training was lacking and inconsistent. A survey was undertaken to gather information from RMS users across the nation, to evaluate the current level of training and determine what if any improvements needed to be made. Additional questions were focused on the operation of the RMS software. The training survey was initially sent electronically to 245 users at the RMS sites and achieved a 37.6% return rate. Analysis of the resulting data revealed that 34.6% of the respondents had not received training or were unsure if they had, despite the fact that vendor engineers provide training at installation of the system. Any training received was referred to as minimal, and brief, not documented, and nothing in writing. 63.7% of respondents said they were either not at all prepared or only somewhat prepared to use the RMS software required to effectively operate the

Detecting suicidality among adolescent outpatients: evaluation of trained clinicians' suicidality assessment against a structured diagnostic assessment made by trained raters

Directory of Open Access Journals (Sweden)

Tuisku Virpi

2008-12-01

Full Text Available Abstract Background Accurate assessment of suicidality is of major importance. We aimed to evaluate trained clinicians' ability to assess suicidality against a structured assessment made by trained raters. Method Treating clinicians classified 218 adolescent psychiatric outpatients suffering from a depressive mood disorder into three classes: 1-no suicidal ideation, 2-suicidal ideation, no suicidal acts, 3-suicidal or self-harming acts. This classification was compared with a classification with identical content derived from the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-PL made by trained raters. The convergence was assessed by kappa- and weighted kappa tests. Results The clinicians' classification to class 1 (no suicidal ideation was 85%, class 2 (suicidal ideation 50%, and class 3 (suicidal acts 10% concurrent with the K-SADS evaluation (γ2 = 37.1, df 4, p = 0.000. Weighted kappa for the agreement of the measures was 0.335 (CI = 0.198–0.471, p Conclusion There was only a modest agreement between the trained clinicians' suicidality evaluation and the K-SADS evaluation, especially concerning suicidal or self-harming acts. We suggest a wider use of structured scales in clinical and research settings to improve reliable detection of adolescents with suicidality.

Design and Realization of Ship Fire Simulation Training System Based on Unity3D

Science.gov (United States)

Ting, Ye; Feng, Chen; Wenqiang, Wang; Kai, Yang

2018-01-01

Ship fire training is a very important training to ensure the safety of the ship, but limited by the characteristics of the ship itself, it is difficult to carry out fire training on the ship. This paper proposes to introduce a virtual reality technology to build a set of ship fire simulation training system, used to improve the quality of training, reduce training costs. First, the system design ideas are elaborated, and the system architecture diagram is given. Then, the key technologies in the process of system implementation are analyzed. Finally, the system examples are built and tested.

Security training symposium: Meeting the challenge: Firearms and explosives recognition and detection

Energy Technology Data Exchange (ETDEWEB)

1990-09-01

These conference proceedings have been prepared in support of the US Nuclear Regulatory Commission's Security Training Symposium on Meeting the Challenge -- Firearms and Explosives Recognition and Detection,'' November 28 through 30, 1989, in Bethesda, Maryland. This document contains the edited transcripts of the guest speakers. It also contains some of the speakers' formal papers that were distributed and some of the slides that were shown at the symposium (Appendix A).

Proprioception rehabilitation training system for stroke patients using virtual reality technology.

Science.gov (United States)

Kim, Sun I; Song, In-Ho; Cho, Sangwoo; Kim, In Young; Ku, Jeonghun; Kang, Youn Joo; Jang, Dong Pyo

2013-01-01

We investigated a virtual reality (VR) proprioceptive rehabilitation system that could manipulate the visual feedback of upper-limb during training and could do training by relying on proprioception feedback only. Virtual environments were designed in order to switch visual feedback on/off during upper-limb training. Two types of VR training tasks were designed for evaluating the effect of the proprioception focused training compared to the training with visual feedback. In order to evaluate the developed proprioception feedback virtual environment system, we recruited ten stroke patients (age: 54.7± 7.83years, on set: 3.29± 3.83 years). All patients performed three times PFVE task in order to check the improvement of proprioception function just before training session, after one week training, and after all training. In a comparison between FMS score and PFVE, the FMS score had a significant relationship with the error distance(r = -.662, n=10, p = .037) and total movement distance(r = -.726, n=10, p = .018) in PFVE. Comparing the training effect between in virtual environment with visual feedback and with proprioception, the click count, error distance and total error distance was more reduced in PFVE than VFVE. (Click count: p = 0.005, error distance: p = 0.001, total error distance: p = 0.007). It suggested that the proprioception feedback rather than visual feedback could be effective means to enhancing motor control during rehabilitation training. The developed VR system for rehabilitation has been verified in that stroke patients improved motor control after VR proprioception feedback training.

Air Cushion Vehicle Operator Training System (ACVOTS) Problem Analysis

Science.gov (United States)

1981-11-01

Appendix A - Discussion of Fundemental Training Analysis Requirements. Appendix B - Data Sources. 9 SECTION II APPROACHES TO TRAINING PRESENT ASSAULT CRAFT...the training system is worth the investment of time and resources required to produce that output. A unique feature which distinguishes ISD from more...when they have been considered in the context of making alternative investment decisions. Investments in technology for certain long high-flow

Computer Directed Training System (CDTS), User’s Manual

Science.gov (United States)

1983-07-01

lessons, together with an estimate of the time required for completion. a. BSCOl0. This lesson in BASIC ( Beginners All Purpose Symbolic Instruction Code...A2-8 FIGURESj Figure A2-1. Training Systems Manager and Training Monitors Responsibility Flowchart ...training at the site. Therefore, the TSM must be knowledgeable in the various tasks required. Figure A2-1 illustrates the position in the flowchart . These

OPTIMAL TRAINING POLICY FOR PROMOTION - STOCHASTIC MODELS OF MANPOWER SYSTEMS

Directory of Open Access Journals (Sweden)

V.S.S. Yadavalli

2012-01-01

Full Text Available In this paper, the optimal planning of manpower training programmes in a manpower system with two grades is discussed. The planning of manpower training within a given organization involves a trade-off between training costs and expected return. These planning problems are examined through models that reflect the random nature of manpower movement in two grades. To be specific, the system consists of two grades, grade 1 and grade 2. Any number of persons in grade 2 can be sent for training and after the completion of training, they will stay in grade 2 and will be given promotion as and when vacancies arise in grade 1. Vacancies arise in grade 1 only by wastage. A person in grade 1 can leave the system with probability p. Vacancies are filled with persons in grade 2 who have completed the training. It is assumed that there is a perfect passing rate and that the sizes of both grades are fixed. Assuming that the planning horizon is finite and is T, the underlying stochastic process is identified as a finite state Markov chain and using dynamic programming, a policy is evolved to determine how many persons should be sent for training at any time k so as to minimize the total expected cost for the entire planning period T.

Cephalometric landmark detection in dental x-ray images using convolutional neural networks

Science.gov (United States)

Lee, Hansang; Park, Minseok; Kim, Junmo

2017-03-01

In dental X-ray images, an accurate detection of cephalometric landmarks plays an important role in clinical diagnosis, treatment and surgical decisions for dental problems. In this work, we propose an end-to-end deep learning system for cephalometric landmark detection in dental X-ray images, using convolutional neural networks (CNN). For detecting 19 cephalometric landmarks in dental X-ray images, we develop a detection system using CNN-based coordinate-wise regression systems. By viewing x- and y-coordinates of all landmarks as 38 independent variables, multiple CNN-based regression systems are constructed to predict the coordinate variables from input X-ray images. First, each coordinate variable is normalized by the length of either height or width of an image. For each normalized coordinate variable, a CNN-based regression system is trained on training images and corresponding coordinate variable, which is a variable to be regressed. We train 38 regression systems with the same CNN structure on coordinate variables, respectively. Finally, we compute 38 coordinate variables with these trained systems from unseen images and extract 19 landmarks by pairing the regressed coordinates. In experiments, the public database from the Grand Challenges in Dental X-ray Image Analysis in ISBI 2015 was used and the proposed system showed promising performance by successfully locating the cephalometric landmarks within considerable margins from the ground truths.

Fast Detection of Compressively Sensed IR Targets Using Stochastically Trained Least Squares and Compressed Quadratic Correlation Filters

KAUST Repository

Millikan, Brian; Dutta, Aritra; Sun, Qiyu; Foroosh, Hassan

2017-01-01

Target detection of potential threats at night can be deployed on a costly infrared focal plane array with high resolution. Due to the compressibility of infrared image patches, the high resolution requirement could be reduced with target detection capability preserved. For this reason, a compressive midwave infrared imager (MWIR) with a low-resolution focal plane array has been developed. As the most probable coefficient indices of the support set of the infrared image patches could be learned from the training data, we develop stochastically trained least squares (STLS) for MWIR image reconstruction. Quadratic correlation filters (QCF) have been shown to be effective for target detection and there are several methods for designing a filter. Using the same measurement matrix as in STLS, we construct a compressed quadratic correlation filter (CQCF) employing filter designs for compressed infrared target detection. We apply CQCF to the U.S. Army Night Vision and Electronic Sensors Directorate dataset. Numerical simulations show that the recognition performance of our algorithm matches that of the standard full reconstruction methods, but at a fraction of the execution time.

Fast Detection of Compressively Sensed IR Targets Using Stochastically Trained Least Squares and Compressed Quadratic Correlation Filters

KAUST Repository

Millikan, Brian

2017-05-02

Target detection of potential threats at night can be deployed on a costly infrared focal plane array with high resolution. Due to the compressibility of infrared image patches, the high resolution requirement could be reduced with target detection capability preserved. For this reason, a compressive midwave infrared imager (MWIR) with a low-resolution focal plane array has been developed. As the most probable coefficient indices of the support set of the infrared image patches could be learned from the training data, we develop stochastically trained least squares (STLS) for MWIR image reconstruction. Quadratic correlation filters (QCF) have been shown to be effective for target detection and there are several methods for designing a filter. Using the same measurement matrix as in STLS, we construct a compressed quadratic correlation filter (CQCF) employing filter designs for compressed infrared target detection. We apply CQCF to the U.S. Army Night Vision and Electronic Sensors Directorate dataset. Numerical simulations show that the recognition performance of our algorithm matches that of the standard full reconstruction methods, but at a fraction of the execution time.

Development of the video streaming system for the radiation safety training

International Nuclear Information System (INIS)

Uemura, Jitsuya

2005-01-01

Radiation workers have to receive the radiation safety training every year. It is very hard for them to receive the training within a limited chance of training. Then, we developed the new training system using the video streaming technique and opened the web page for the training on our homepage. Every worker is available to receive the video lecture at any time and at any place by using his PC via internet. After watching the video, the worker should receive the completion examination. It he can pass the examination, he was registered as a radiation worker by the database system for radiation control. (author)

Care staff training in detection of depression in residential homes for the elderly - Randomised trial

NARCIS (Netherlands)

Eisses, AMH; Kluiter, H; Jongenelis, K; Beekman, ATF; Ormel, J

Background. Many people with depression in residential care homes for the elderly do not receive treatment because their depression remains undetected. Aims. To determine the effects of staff training on the detection, treatment and outcome of depression in residents often homes. Method. We

The Impact of PMIS Training: Patterns of Benefit Realization in Project Management Information Systems Training

Directory of Open Access Journals (Sweden)

Andrew McCarty

2017-01-01

Full Text Available The benefits of project, program, and portfolio management software toolsets can be enhanced through training. Little is known about the realization of positive, beneficial outcomes and Project Management Information System (PMIS training. This research seeks to improve understanding of project management software toolset training practices and outcomes. This study examines the prevalence, effectiveness, and impact-per-hour efficiency of training in real-world organizations. We further explore relationships between individual and organizational characteristics and training outcomes. Formulae for estimating training costs are derived using regression modeling. Surveys were collected from 1,021 active professionals and analyzed using quantitative methods. Research participants were practitioners recruited by eight different companies, industry groups, and professional organizations within the PMIS community. The findings of this research indicate significant differences in utilization, efficacy, and efficiency of PMIS training in practice. The outcomes and methodologies of this study are being incorporated into ongoing research that focuses on improving PMIS training delivery, evaluation, and planning. The outcomes of this research may result in more effective, efficient, and economical PMIS training that is better tailored to the unique needs of each organization.

Integrated multisensor perimeter detection systems

Science.gov (United States)

Kent, P. J.; Fretwell, P.; Barrett, D. J.; Faulkner, D. A.

2007-10-01

The report describes the results of a multi-year programme of research aimed at the development of an integrated multi-sensor perimeter detection system capable of being deployed at an operational site. The research was driven by end user requirements in protective security, particularly in threat detection and assessment, where effective capability was either not available or prohibitively expensive. Novel video analytics have been designed to provide robust detection of pedestrians in clutter while new radar detection and tracking algorithms provide wide area day/night surveillance. A modular integrated architecture based on commercially available components has been developed. A graphical user interface allows intuitive interaction and visualisation with the sensors. The fusion of video, radar and other sensor data provides the basis of a threat detection capability for real life conditions. The system was designed to be modular and extendable in order to accommodate future and legacy surveillance sensors. The current sensor mix includes stereoscopic video cameras, mmWave ground movement radar, CCTV and a commercially available perimeter detection cable. The paper outlines the development of the system and describes the lessons learnt after deployment in a pilot trial.

Gas Detection Instrument Based on Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

ANSONG FENG

2013-06-01

Full Text Available The wireless sensor network is used to simulate poisonous gas generating system in the Fire-Fighting Simulated Training System. In the paper, we use the wireless signal to simulate the poisonous gas source and use received signal strength indicator (RSSI to simulate the distance between the fireman and the gas source. The gas detection instrument samples the temperature and sphygmus of the trainee and uses the wireless signal as poisonous gas signal. When the trainee enters into the poisonous gas area, the gas detection instrument warns with sound and light and sends the type, density value, the location of the poisonous gas and vital signs of the trainee to host. The paper discusses the software and hardware design of the gas detection instrument. The system has been used to the several of Fire-Fighting training systems.

Application of Islanding Detection and Classification of Power Quality Disturbance in Hybrid Energy System

Science.gov (United States)

Sun, L. B.; Wu, Z. S.; Yang, K. K.

2018-04-01

Islanding and power quality (PQ) disturbances in hybrid energy system become more serious with the application of renewable energy sources. In this paper, a novel method based on wavelet transform (WT) and modified feed forward neural network (FNN) is proposed to detect islanding and classify PQ problems. First, the performance indices, i.e., the energy content and SD of the transformed signal are extracted from the negative sequence component of the voltage signal at PCC using WT. Afterward, WT indices are fed to train FNNs midfield by Particle Swarm Optimization (PSO) which is a novel heuristic optimization method. Then, the results of simulation based on WT-PSOFNN are discussed in MATLAB/SIMULINK. Simulations on the hybrid power system show that the accuracy can be significantly improved by the proposed method in detecting and classifying of different disturbances connected to multiple distributed generations.

Timing system for multi-bunch/multi-train operation at ATF

International Nuclear Information System (INIS)

Naito, T.; Hayano, H.; Urakawa, J.; Imai, T.

2000-01-01

A timing system has been constructed for multi-bunch/multi-train operation at KEK-ATF. The linac accelerates 20 bunches of multi-bunch with 2.8 ns spacing. The Damping Ring stores up to 5 trains of multi-bunch. The timing system is required to provide flexible operation mode and bucket selection. A personal computer is used for manipulating the timing. The performance of kicker magnets at the injection/extruction is key issue for multi-train operation. The hardware and the test results are presented. (author)

Use of VR Technology and Passive Haptics for MANPADS Training System

Science.gov (United States)

2017-09-01

reach satisfactory technical performance like latency and frame rate, while generating the sensory stimuli needed for this type of training —visual...release. Distribution is unlimited. USE OF VR TECHNOLOGY AND PASSIVE HAPTICS FOR MANPADS TRAINING SYSTEM by Faisal Rashid September 2017...HAPTICS FOR MANPADS TRAINING SYSTEM 5. FUNDING NUMBERS 6. AUTHOR(S) Faisal Rashid 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval

An improved technique for the detection of pilot contamination attacks in TDD wireless communication systems

Directory of Open Access Journals (Sweden)

Mihaylova Dimitriya

2017-01-01

Full Text Available One of the problems phasing the physical layer security of a wireless system is its vulnerability to pilot contamination attacks and hence schemes for its detection need to be applied. A method proposed in the literature consists of training with two N-PSK pilots. Although the method is effective in most of the cases, it is not able to discover an attack initiated during the transmission of the second pilot from the pair if both the legitimate and non-legitimate pilots coincide. In this current paper, an improvement to this method is proposed which detects an intruder who misses the first pilot transmission. The suggested improvement eliminates the usage of threshold values in the detection – a main drawback of previously existing solution.

Statistical fault detection in photovoltaic systems

KAUST Repository

Garoudja, Elyes

2017-05-08

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model with the extended capacity of an exponentially weighted moving average (EWMA) control chart to detect incipient changes in a PV system. The one-diode model, which is easily calibrated due to its limited calibration parameters, is used to predict the healthy PV array\\'s maximum power coordinates of current, voltage and power using measured temperatures and irradiances. Residuals, which capture the difference between the measurements and the predictions of the one-diode model, are generated and used as fault indicators. Then, the EWMA monitoring chart is applied on the uncorrelated residuals obtained from the one-diode model to detect and identify the type of fault. Actual data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria, are used to assess the performance of the proposed approach. Results show that the proposed approach successfully monitors the DC side of PV systems and detects temporary shading.

Training and Technical Assistance for Small Systems Funding

Science.gov (United States)

Provides water and wastewater system staff and private well owners with training and tools to enhance system operations and management practices, and support EPA’s continuing efforts to protect public health and promote sustainability.

Homodyne detection of holographic memory systems

Science.gov (United States)

Urness, Adam C.; Wilson, William L.; Ayres, Mark R.

2014-09-01

We present a homodyne detection system implemented for a page-wise holographic memory architecture. Homodyne detection by holographic memory systems enables phase quadrature multiplexing (doubling address space), and lower exposure times (increasing read transfer rates). It also enables phase modulation, which improves signal-to-noise ratio (SNR) to further increase data capacity. We believe this is the first experimental demonstration of homodyne detection for a page-wise holographic memory system suitable for a commercial design.

Training programs for the systems approach to nuclear security

International Nuclear Information System (INIS)

Ellis, D.

2005-01-01

Full text: In support of United States Government (USG) and International Atomic Energy Agency (IAEA) nuclear security programs, Sandia National Laboratories (SNL) has advocated and practiced a risk-based, systematic approach to nuclear security. The risk equation has been developed and implemented as the basis for a performance-based methodology for the design and evaluation of physical protection systems against a design basis threat (DBT) for theft and sabotage of nuclear and/or radiological materials. Integrated systems must include technology, people, and the man-machine interface. A critical aspect of the human element is training on the systems-approach for all the stakeholders in nuclear security. Current training courses and workshops have been very beneficial but are still rather limited in scope. SNL has developed two primary international classes - the international training course on the physical protection of nuclear facilities and materials, and the design basis threat methodology workshop. SNL is also completing the development of three new courses that will be offered and presented in the near term. They are vital area identification methodology focused on nuclear power plants to aid in their protection against radiological sabotage, insider threat analysis methodology and protection schemes, and security foundations for competent authority and facility operator stakeholders who are not security professionals. In the long term, we envision a comprehensive nuclear security curriculum that spans policy and technology, regulators and operators, introductory and expert levels, classroom and laboratory/field, and local and offsite training options. This training curriculum will be developed in concert with a nuclear security series of guidance documents that is expected to be forthcoming from the IAEA. It is important to note that while appropriate implementation of systems based on such training and documentation can improve the risk reduction, such a

Gas Flow Detection System

Science.gov (United States)

Moss, Thomas; Ihlefeld, Curtis; Slack, Barry

2010-01-01

This system provides a portable means to detect gas flow through a thin-walled tube without breaking into the tubing system. The flow detection system was specifically designed to detect flow through two parallel branches of a manifold with only one inlet and outlet, and is a means for verifying a space shuttle program requirement that saves time and reduces the risk of flight hardware damage compared to the current means of requirement verification. The prototype Purge Vent and Drain Window Cavity Conditioning System (PVD WCCS) Flow Detection System consists of a heater and a temperature-sensing thermistor attached to a piece of Velcro to be attached to each branch of a WCCS manifold for the duration of the requirement verification test. The heaters and thermistors are connected to a shielded cable and then to an electronics enclosure, which contains the power supplies, relays, and circuit board to provide power, signal conditioning, and control. The electronics enclosure is then connected to a commercial data acquisition box to provide analog to digital conversion as well as digital control. This data acquisition box is then connected to a commercial laptop running a custom application created using National Instruments LabVIEW. The operation of the PVD WCCS Flow Detection System consists of first attaching a heater/thermistor assembly to each of the two branches of one manifold while there is no flow through the manifold. Next, the software application running on the laptop is used to turn on the heaters and to monitor the manifold branch temperatures. When the system has reached thermal equilibrium, the software application s graphical user interface (GUI) will indicate that the branch temperatures are stable. The operator can then physically open the flow control valve to initiate the test flow of gaseous nitrogen (GN2) through the manifold. Next, the software user interface will be monitored for stable temperature indications when the system is again at

Care staff training in detection of depression in residential homes for the elderly: randomised trial

NARCIS (Netherlands)

Eisses, A.M.H.; Kluiter, H.; Jongenelis, K.; Pot, A.M.; Beekman, A.T.F.; Ormel, J.

2005-01-01

Background: Many people with depression in residential care homes for the elderly do not receive treatment because their depression remains undetected. Aims: To determine the effects of staff training on the detection, treatment and outcome of depression in residents of ten homes. Method: We

Multiple-instance learning for computer-aided detection of tuberculosis

Science.gov (United States)

Melendez, J.; Sánchez, C. I.; Philipsen, R. H. H. M.; Maduskar, P.; van Ginneken, B.

2014-03-01

Detection of tuberculosis (TB) on chest radiographs (CXRs) is a hard problem. Therefore, to help radiologists or even take their place when they are not available, computer-aided detection (CAD) systems are being developed. In order to reach a performance comparable to that of human experts, the pattern recognition algorithms of these systems are typically trained on large CXR databases that have been manually annotated to indicate the abnormal lung regions. However, manually outlining those regions constitutes a time-consuming process that, besides, is prone to inconsistencies and errors introduced by interobserver variability and the absence of an external reference standard. In this paper, we investigate an alternative pattern classi cation method, namely multiple-instance learning (MIL), that does not require such detailed information for a CAD system to be trained. We have applied this alternative approach to a CAD system aimed at detecting textural lesions associated with TB. Only the case (or image) condition (normal or abnormal) was provided in the training stage. We compared the resulting performance with those achieved by several variations of a conventional system trained with detailed annotations. A database of 917 CXRs was constructed for experimentation. It was divided into two roughly equal parts that were used as training and test sets. The area under the receiver operating characteristic curve was utilized as a performance measure. Our experiments show that, by applying the investigated MIL approach, comparable results as with the aforementioned conventional systems are obtained in most cases, without requiring condition information at the lesion level.

PCA-based detection of damage in time-varying systems

Science.gov (United States)

Bellino, A.; Fasana, A.; Garibaldi, L.; Marchesiello, S.

2010-10-01

When performing Structural Health Monitoring, it is well known that the natural frequencies do not depend only on the damage but also on environmental conditions, such as temperature and humidity. The Principal Component Analysis is used to take this problem into account, because it allows eliminating the effect of external factors. The purpose of the present work is to show that this technique can be successfully used not only for time-invariant systems, but also for time-varying ones. Referring to the latter, one of the most studied systems which shows these characteristics is the bridge with crossing loads, such as the case of the railway bridge studied in present paper; in this case, the mass and the velocity of the train can be considered as "environmental" factors.This paper, after a brief description of the PCA method and one example of its application on time-invariant systems, presents the great potentialities of the methodology when applied to time-varying systems. The results show that this method is able to better detect the presence of damage and also to properly distinguish among different levels of crack depths.

A computer-based training system combining virtual reality and multimedia

International Nuclear Information System (INIS)

Stansfield, S.A.

1993-01-01

Training new users of complex machines is often an expensive and time-consuming process. This is particularly true for special purpose systems, such as those frequently encountered in DOE applications. This paper presents a computer-based training system intended as a partial solution to this problem. The system extends the basic virtual reality (VR) training paradigm by adding a multimedia component which may be accessed during interaction with the virtual environment: The 3D model used to create the virtual reality is also used as the primary navigation tool through the associated multimedia. This method exploits the natural mapping between a virtual world and the real world that it represents to provide a more intuitive way for the student to interact with all forms of information about the system

New control method of on-board ATP system of Shinkansen trains

Energy Technology Data Exchange (ETDEWEB)

Fukuda, N.; Watanabe, T. [Railway Technical Research Inst. (Japan)

2000-07-01

We studied a new control method of the on-board automatic train protection (ATP) system for Shinkansen trains to shorten the operation time and not to degrade ride comfort at changes in deceleration of the train, while maintaining the safety and reliability of the present ATP signal system. We propose a new on-board pattern brake control system based on the present ATP data without changing the wayside equipment. By simulating the ATP braking of the proposed control method, we succeeded in shortening the operation time by 48 seconds per one station in comparison with the present ATP brake control system. This paper reports the concept of the system and simulation results of the on-board pattern. (orig.)

[Design and development of an online system of parasite's images for training and evaluation].

Science.gov (United States)

Yuan-Chun, Mao; Sui, Xu; Jie, Wang; Hua-Yun, Zhou; Jun, Cao

2017-08-08

To design and develop an online training and evaluation system for parasitic pathogen recognition. The system was based on a Parasitic Diseases Specimen Image Digitization Construction Database by using MYSQL 5.0 as the system of database development software, and PHP 5 as the interface development language. It was mainly used for online training and evaluation of parasitic pathology diagnostic techniques. The system interface was designed simple, flexible, and easy to operate for medical staff. It enabled full day and 24 hours accessible to online training study and evaluation. Thus, the system broke the time and space constraints of the traditional training models. The system provides a shared platform for the professional training of parasitic diseases, and a reference for other training tasks.

An Ice Protection and Detection Systems Manufacturer's Perspective

Science.gov (United States)

Sweet, Dave

2009-01-01

Accomplishments include: World Class Aircraft Icing Research Center and Facility. Primary Sponsor/Partner - Aircraft Icing Consortia/Meetings. Icing Research Tunnel. Icing Test Aircraft. Icing Codes - LEWICE/Scaling, et al. Development of New Technologies (SBIR, STTR, et al). Example: Look Ahead Ice Detection. Pilot Training Materials. Full Cooperation with Academia, Government and Industry.

Embedded Systems - Missile Detection/Interception

Directory of Open Access Journals (Sweden)

Luis Cintron

2010-01-01

Full Text Available Missile defense systems are often related to major military resources aimed at shielding a specific region from incoming attacks. They are intended to detect, track, intercept, and destruct incoming enemy missiles. These systems vary in cost, efficiency, dependability, and technology. In present times, the possession of these types of systems is associated with large capacity military countries. Demonstrated here are the mathematical techniques behind missile systems which calculate trajectories of incoming missiles and potential intercept positions after initial missile detection. This procedure involved the use of vector-valued functions, systems of equations, and knowledge of projectile motion concepts.

A new training philosophy: The local system of development of competence

International Nuclear Information System (INIS)

Billard, P.

1996-01-01

Fifteen years ago, the French Nuclear Program has created a particular climate full of dynamism and enthusiasm, in the accomplishment of which each individual has been motivated, using the strong centralized training system with aims to develop knowledge and skills necessary to be promoted in new jobs. Now a day environment has been changed because of, among other things, the general career development plateau, the aging of installations and personnel and the external pressure on nuclear safety. It is now necessary to move from a centralized training system of development of skills to local systems of development of competencies. But how to keep advantages of standardized nuclear program with individual plant organization which is different from one plant to another? The paper describes how EDF is changing his training organization, the relationship between NPP's and training centres, the roles and responsibilities between corporate resources departments, NPP management and training centres. (author)

Optimal trajectory planning and train scheduling for urban rail transit systems

CERN Document Server

Wang, Yihui; van den Boom, Ton; De Schutter, Bart

2016-01-01

This book contributes to making urban rail transport fast, punctual and energy-efficient –significant factors in the importance of public transportation systems to economic, environmental and social requirements at both municipal and national levels. It proposes new methods for shortening passenger travel times and for reducing energy consumption, addressing two major topics: (1) train trajectory planning: the authors derive a nonlinear model for the operation of trains and present several approaches for calculating optimal and energy-efficient trajectories within a given schedule; and (2) train scheduling: the authors develop a train scheduling model for urban rail systems and optimization approaches with which to balance total passenger travel time with energy efficiency and other costs to the operator. Mixed-integer linear programming and pseudospectral methods are among the new methods proposed for single- and multi-train systems for the solution of the nonlinear trajectory planning problem which involv...

Hybrid Intrusion Detection System for DDoS Attacks

Directory of Open Access Journals (Sweden)

Özge Cepheli

2016-01-01

Full Text Available Distributed denial-of-service (DDoS attacks are one of the major threats and possibly the hardest security problem for today’s Internet. In this paper we propose a hybrid detection system, referred to as hybrid intrusion detection system (H-IDS, for detection of DDoS attacks. Our proposed detection system makes use of both anomaly-based and signature-based detection methods separately but in an integrated fashion and combines the outcomes of both detectors to enhance the overall detection accuracy. We apply two distinct datasets to our proposed system in order to test the detection performance of H-IDS and conclude that the proposed hybrid system gives better results than the systems based on nonhybrid detection.

Flat Surface Damage Detection System (FSDDS)

Science.gov (United States)

Williams, Martha; Lewis, Mark; Gibson, Tracy; Lane, John; Medelius, Pedro; Snyder, Sarah; Ciarlariello, Dan; Parks, Steve; Carrejo, Danny; Rojdev, Kristina

2013-01-01

The Flat Surface Damage Detection system (FSDDS} is a sensory system that is capable of detecting impact damages to surfaces utilizing a novel sensor system. This system will provide the ability to monitor the integrity of an inflatable habitat during in situ system health monitoring. The system consists of three main custom designed subsystems: the multi-layer sensing panel, the embedded monitoring system, and the graphical user interface (GUI). The GUI LABVIEW software uses a custom developed damage detection algorithm to determine the damage location based on the sequence of broken sensing lines. It estimates the damage size, the maximum depth, and plots the damage location on a graph. Successfully demonstrated as a stand alone technology during 2011 D-RATS. Software modification also allowed for communication with HDU avionics crew display which was demonstrated remotely (KSC to JSC} during 2012 integration testing. Integrated FSDDS system and stand alone multi-panel systems were demonstrated remotely and at JSC, Mission Operations Test using Space Network Research Federation (SNRF} network in 2012. FY13, FSDDS multi-panel integration with JSC and SNRF network Technology can allow for integration with other complementary damage detection systems.

Virtual Exercise Training Software System

Science.gov (United States)

Vu, L.; Kim, H.; Benson, E.; Amonette, W. E.; Barrera, J.; Perera, J.; Rajulu, S.; Hanson, A.

2018-01-01

The purpose of this study was to develop and evaluate a virtual exercise training software system (VETSS) capable of providing real-time instruction and exercise feedback during exploration missions. A resistive exercise instructional system was developed using a Microsoft Kinect depth-camera device, which provides markerless 3-D whole-body motion capture at a small form factor and minimal setup effort. It was hypothesized that subjects using the newly developed instructional software tool would perform the deadlift exercise with more optimal kinematics and consistent technique than those without the instructional software. Following a comprehensive evaluation in the laboratory, the system was deployed for testing and refinement in the NASA Extreme Environment Mission Operations (NEEMO) analog.

A training system of orientation and mobility for blind people using acoustic virtual reality.

Science.gov (United States)

Seki, Yoshikazu; Sato, Tetsuji

2011-02-01

A new auditory orientation training system was developed for blind people using acoustic virtual reality (VR) based on a head-related transfer function (HRTF) simulation. The present training system can reproduce a virtual training environment for orientation and mobility (O&M) instruction, and the trainee can walk through the virtual training environment safely by listening to sounds such as vehicles, stores, ambient noise, etc., three-dimensionally through headphones. The system can reproduce not only sound sources but also sound reflection and insulation, so that the trainee can learn both sound location and obstacle perception skills. The virtual training environment is described in extensible markup language (XML), and the O&M instructor can edit it easily according to the training curriculum. Evaluation experiments were conducted to test the efficiency of some features of the system. Thirty subjects who had not acquired O&M skills attended the experiments. The subjects were separated into three groups: a no-training group, a virtual-training group using the present system, and a real-training group in real environments. The results suggested that virtual-training can reduce "veering" more than real-training and also can reduce stress as much as real training. The subjective technical and anxiety scores also improved.

Electromagnetic field analysis and modeling of a relative position detection sensor for high speed maglev trains.

Science.gov (United States)

Xue, Song; He, Ning; Long, Zhiqiang

2012-01-01

The long stator track for high speed maglev trains has a tooth-slot structure. The sensor obtains precise relative position information for the traction system by detecting the long stator tooth-slot structure based on nondestructive detection technology. The magnetic field modeling of the sensor is a typical three-dimensional (3-D) electromagnetic problem with complex boundary conditions, and is studied semi-analytically in this paper. A second-order vector potential (SOVP) is introduced to simplify the vector field problem to a scalar field one, the solution of which can be expressed in terms of series expansions according to Multipole Theory (MT) and the New Equivalent Source (NES) method. The coefficients of the expansions are determined by the least squares method based on the boundary conditions. Then, the solution is compared to the simulation result through Finite Element Analysis (FEA). The comparison results show that the semi-analytical solution agrees approximately with the numerical solution. Finally, based on electromagnetic modeling, a difference coil structure is designed to improve the sensitivity and accuracy of the sensor.

Electromagnetic Field Analysis and Modeling of a Relative Position Detection Sensor for High Speed Maglev Trains

Directory of Open Access Journals (Sweden)

Song Xue

2012-05-01

Full Text Available The long stator track for high speed maglev trains has a tooth-slot structure. The sensor obtains precise relative position information for the traction system by detecting the long stator tooth-slot structure based on nondestructive detection technology. The magnetic field modeling of the sensor is a typical three-dimensional (3-D electromagnetic problem with complex boundary conditions, and is studied semi-analytically in this paper. A second-order vector potential (SOVP is introduced to simplify the vector field problem to a scalar field one, the solution of which can be expressed in terms of series expansions according to Multipole Theory (MT and the New Equivalent Source (NES method. The coefficients of the expansions are determined by the least squares method based on the boundary conditions. Then, the solution is compared to the simulation result through Finite Element Analysis (FEA. The comparison results show that the semi-analytical solution agrees approximately with the numerical solution. Finally, based on electromagnetic modeling, a difference coil structure is designed to improve the sensitivity and accuracy of the sensor.

Training set optimization and classifier performance in a top-down diabetic retinopathy screening system

Science.gov (United States)

Wigdahl, J.; Agurto, C.; Murray, V.; Barriga, S.; Soliz, P.

2013-03-01

Diabetic retinopathy (DR) affects more than 4.4 million Americans age 40 and over. Automatic screening for DR has shown to be an efficient and cost-effective way to lower the burden on the healthcare system, by triaging diabetic patients and ensuring timely care for those presenting with DR. Several supervised algorithms have been developed to detect pathologies related to DR, but little work has been done in determining the size of the training set that optimizes an algorithm's performance. In this paper we analyze the effect of the training sample size on the performance of a top-down DR screening algorithm for different types of statistical classifiers. Results are based on partial least squares (PLS), support vector machines (SVM), k-nearest neighbor (kNN), and Naïve Bayes classifiers. Our dataset consisted of digital retinal images collected from a total of 745 cases (595 controls, 150 with DR). We varied the number of normal controls in the training set, while keeping the number of DR samples constant, and repeated the procedure 10 times using randomized training sets to avoid bias. Results show increasing performance in terms of area under the ROC curve (AUC) when the number of DR subjects in the training set increased, with similar trends for each of the classifiers. Of these, PLS and k-NN had the highest average AUC. Lower standard deviation and a flattening of the AUC curve gives evidence that there is a limit to the learning ability of the classifiers and an optimal number of cases to train on.

Detection technique of targets for missile defense system

Science.gov (United States)

Guo, Hua-ling; Deng, Jia-hao; Cai, Ke-rong

2009-11-01

Ballistic missile defense system (BMDS) is a weapon system for intercepting enemy ballistic missiles. It includes ballistic-missile warning system, target discrimination system, anti-ballistic-missile guidance systems, and command-control communication system. Infrared imaging detection and laser imaging detection are widely used in BMDS for surveillance, target detection, target tracking, and target discrimination. Based on a comprehensive review of the application of target-detection techniques in the missile defense system, including infrared focal plane arrays (IRFPA), ground-based radar detection technology, 3-dimensional imaging laser radar with a photon counting avalanche photodiode (APD) arrays and microchip laser, this paper focuses on the infrared and laser imaging detection techniques in missile defense system, as well as the trends for their future development.

Operating a Microwave Radiation Detection Monitor. Module 10. Vocational Education Training in Environmental Health Sciences.

Science.gov (United States)

Consumer Dynamics Inc., Rockville, MD.

This module, one of 25 on vocational education training for careers in environmental health occupations, contains self-instructional materials on operating a microwave radiation detection monitor. Following guidelines for students and instructors and an introduction that explains what the student will learn are three lessons: (1) testing the…

System for the quality assurance of personnel training programs

International Nuclear Information System (INIS)

Rjona, Orison; Venegas, Maria del C.; Rodriguez, Lazaro; Lopez, Miguel A.; Armenteros, Ana L.

1999-01-01

In this work are described the fundamental possibilities and characteristics of a software that allows to carry out the management and automatic evaluation of all data gotten during jobs analysis and design, development, implementation and evaluation of personnel training programs of nuclear and radioactive installations and risk industries. The system that is introduced, GESAT, proportion a tool of centralized managerial control of training data and the obtaining of the quality objectives of each installation in the training of their personnel. GESAT includes all phases of SAT method (Systematic Approach to Training). It constitutes the necessary practical support for the elaboration, implementation and evaluation of training programs, allowing the establishment of restrictions and controls and avoiding inconsistencies in the process. It offers the possibility of automatic evaluation that identify fundamental deficiencies in the planning and implementation of training programs. This evaluation facilitates the systematic feed back and the continuous improvement of the training programs.(author)

Design of a Construction Safety Training System using Contextual Design Methodology

OpenAIRE

Baldev, Darshan H.

2006-01-01

In the U.S., the majority of construction companies are small companies with 10 or fewer employees (BLS, 2004). The fatality rate in the construction industry is high, indicating a need for implementing safety training to a greater extent. This research addresses two main goals: to make recommendations and design a safety training system for small construction companies, and to use Contextual Design to design the training system. Contextual Design was developed by Holtzblatt (Beyer and Holtzb...

A cable-driven locomotor training system for restoration of gait in human SCI.

Science.gov (United States)

Wu, Ming; Hornby, T George; Landry, Jill M; Roth, Heidi; Schmit, Brian D

2011-02-01

A novel cable-driven robotic locomotor training system was developed to provide compliant assistance/resistance forces to the legs during treadmill training in patients with incomplete spinal cord injury (SCI). Eleven subjects with incomplete SCI were recruited to participate in two experiments to test the feasibility of the robotic gait training system. Specifically, 10 subjects participated in one experimental session to test the characteristics of the robotic gait training system and one subject participated in repeated testing sessions over 8 weeks with the robotic device to test improvements in locomotor function. Limb kinematics were recorded in one experiment to evaluate the system characteristics of the cable-driven locomotor trainer and the overground gait speed and 6 min walking distance were evaluated at pre, 4 and 8 weeks post treadmill training of a single subject as well. The results indicated that the cable driven robotic gait training system improved the kinematic performance of the leg during treadmill walking and had no significant impact on the variability of lower leg trajectory, suggesting a high backdrivability of the cable system. In addition, results from a patient with incomplete SCI indicated that prolonged robotic gait training using the cable robot improved overground gait speed. Results from this study suggested that a cable driven robotic gait training system is effective in improving leg kinematic performance, yet allows variability of gait kinematics. Thus, it seems feasible to improve the locomotor function in human SCI using this cable driven robotic system, warranting testing with a larger group of patients. Copyright © 2010 Elsevier B.V. All rights reserved.

Ferromagnetic Objects Magnetovision Detection System.

Science.gov (United States)

Nowicki, Michał; Szewczyk, Roman

2013-12-02

This paper presents the application of a weak magnetic fields magnetovision scanning system for detection of dangerous ferromagnetic objects. A measurement system was developed and built to study the magnetic field vector distributions. The measurements of the Earth's field distortions caused by various ferromagnetic objects were carried out. The ability for passive detection of hidden or buried dangerous objects and the determination of their location was demonstrated.

Current trauma care system and trauma care training in China

Directory of Open Access Journals (Sweden)

Lian-Yang Zhang

2018-04-01

Full Text Available Trauma is a life-threatening “modern disease”. The outcomes could only be optimized by cost-efficient and prompt trauma care, which embarks on the improvement of essential capacities and conceptual revolution in addition to the disruptive innovation of the trauma care system. According to experiences from the developed countries, systematic trauma care training is the cornerstone of the generalization and the improvement on the trauma care, such as the Advance Trauma Life Support (ATLS. Currently, the pre-hospital emergency medical services (EMS has been one of the essential elements of infrastructure of health services in China, which is also fundamental to the trauma care system. Hereby, the China Trauma Care Training (CTCT with independent intellectual property rights has been initiated and launched by the Chinese Trauma Surgeon Association to extend the up-to-date concepts and techniques in the field of trauma care as well to reinforce the generally well-accepted standardized protocols in the practices. This article reviews the current status of the trauma care system as well as the trauma care training. Keywords: Trauma care system, Trauma care training, China

Cyber Security Testing and Training Programs for Industrial Control Systems

Energy Technology Data Exchange (ETDEWEB)

Daniel Noyes

2012-03-01

Service providers rely on industrial control systems (ICS) to manage the flow of water at dams, open breakers on power grids, control ventilation and cooling in nuclear power plants, and more. In today's interconnected environment, this can present a serious cyber security challenge. To combat this growing challenge, government, private industry, and academia are working together to reduce cyber risks. The Idaho National Laboratory (INL) is a key contributor to the Department of Energy National SCADA Test Bed (NSTB) and the Department of Homeland Security (DHS) Control Systems Security Program (CSSP), both of which focus on improving the overall security posture of ICS in the national critical infrastructure. In support of the NSTB, INL hosts a dedicated SCADA testing facility which consists of multiple control systems supplied by leading national and international manufacturers. Within the test bed, INL researchers systematically examine control system components and work to identify vulnerabilities. In support of the CSSP, INL develops and conducts training courses which are designed to increase awareness and defensive capabilities for IT/Control System professionals. These trainings vary from web-based cyber security trainings for control systems engineers to more advanced hands-on training that culminates with a Red Team/ Blue Team exercise that is conducted within an actual control systems environment. INL also provides staffing and operational support to the DHS Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) Security Operations Center which responds to and analyzes control systems cyber incidents across the 18 US critical infrastructure sectors.

Carboy Security Testing and Training Programs for Industrial Control Systems

International Nuclear Information System (INIS)

Noyes, Daniel

2012-01-01

Service providers rely on industrial control systems (ICS) to manage the flow of water at dams, open breakers on power grids, control ventilation and cooling in nuclear power plants, and more. In today's interconnected environment, this can present a serious cyber security challenge. To combat this growing challenge, government, private industry, and academia are working together to reduce cyber risks. The Idaho National Laboratory (INL) is a key contributor to the Department of Energy National SCADA Test Bed (NSTB) and the Department of Homeland Security (DHS) Control Systems Security Program (CSSP), both of which focus on improving the overall security posture of ICS in the national critical infrastructure. In support of the NSTB, INL hosts a dedicated SCADA testing facility which consists of multiple control systems supplied by leading national and international manufacturers. Within the test bed, INL researchers systematically examine control system components and work to identify vulnerabilities. In support of the CSSP, INL develops and conducts training courses which are designed to increase awareness and defensive capabilities for IT/Control System professionals. These training vary from web-based cyber security training for control systems engineers to more advanced hands-on training that culminates with a Red Team/Blue Team exercise that is conducted within an actual control systems environment. INL also provides staffing and operational support to the DHS Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) Security Operations Center which responds to and analyzes control systems cyber incidents across the 18 US critical infrastructure sectors

Cyber Security Testing and Training Programs for Industrial Control Systems

International Nuclear Information System (INIS)

Noyes, Daniel

2012-01-01

Service providers rely on industrial control systems (ICS) to manage the flow of water at dams, open breakers on power grids, control ventilation and cooling in nuclear power plants, and more. In today's interconnected environment, this can present a serious cyber security challenge. To combat this growing challenge, government, private industry, and academia are working together to reduce cyber risks. The Idaho National Laboratory (INL) is a key contributor to the Department of Energy National SCADA Test Bed (NSTB) and the Department of Homeland Security (DHS) Control Systems Security Program (CSSP), both of which focus on improving the overall security posture of ICS in the national critical infrastructure. In support of the NSTB, INL hosts a dedicated SCADA testing facility which consists of multiple control systems supplied by leading national and international manufacturers. Within the test bed, INL researchers systematically examine control system components and work to identify vulnerabilities. In support of the CSSP, INL develops and conducts training courses which are designed to increase awareness and defensive capabilities for IT/Control System professionals. These trainings vary from web-based cyber security trainings for control systems engineers to more advanced hands-on training that culminates with a Red Team/ Blue Team exercise that is conducted within an actual control systems environment. INL also provides staffing and operational support to the DHS Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) Security Operations Center which responds to and analyzes control systems cyber incidents across the 18 US critical infrastructure sectors.

Carboy Security Testing and Training Programs for Industrial Control Systems

Energy Technology Data Exchange (ETDEWEB)

Noyes, Daniel [Idaho National Laboratory, Idaho (United States)

2012-03-15

Service providers rely on industrial control systems (ICS) to manage the flow of water at dams, open breakers on power grids, control ventilation and cooling in nuclear power plants, and more. In today's interconnected environment, this can present a serious cyber security challenge. To combat this growing challenge, government, private industry, and academia are working together to reduce cyber risks. The Idaho National Laboratory (INL) is a key contributor to the Department of Energy National SCADA Test Bed (NSTB) and the Department of Homeland Security (DHS) Control Systems Security Program (CSSP), both of which focus on improving the overall security posture of ICS in the national critical infrastructure. In support of the NSTB, INL hosts a dedicated SCADA testing facility which consists of multiple control systems supplied by leading national and international manufacturers. Within the test bed, INL researchers systematically examine control system components and work to identify vulnerabilities. In support of the CSSP, INL develops and conducts training courses which are designed to increase awareness and defensive capabilities for IT/Control System professionals. These training vary from web-based cyber security training for control systems engineers to more advanced hands-on training that culminates with a Red Team/Blue Team exercise that is conducted within an actual control systems environment. INL also provides staffing and operational support to the DHS Industrial Control Systems Cyber Emergency Response Team (ICS-CERT) Security Operations Center which responds to and analyzes control systems cyber incidents across the 18 US critical infrastructure sectors.

Research on driver fatigue detection

Science.gov (United States)

Zhang, Ting; Chen, Zhong; Ouyang, Chao

2018-03-01

Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

DEVELOPMENT AND IMPLEMENTATION OF A PRACTICAL PUBLIC HEALTH TRAINING SYSTEM IN CHINA.

Science.gov (United States)

Liu, Changjiang; Zhang, Junyue; Chen, Guoyuan; Yang, Kedi

2015-03-01

Public health education is becoming an increasing priority among educators of medicine. In China, little attention has been paid to public health education reform. A new public health training system was introduced in China in 2007. We conducted this study during 2006-2012 to evaluate the graduate core competencies under the new system. Data were collected from 231 graduates and 49 public health agencies. The 144 graduates who enrolled in 2006 and were trained under the old system constituted the control group; the 87 graduates who enrolled in 2007 and were trained under the new system constituted the experimental group. Surveys of graduate core competencies found analyzing and solving problems in the laboratory, conducting on-site practice and learning new technologies were the top three abilities most expected by public health agencies. After 5-year practical ability training, the graduates in the experimental group had better performance; on-site practical ability and laboratory practical ability increased significantly by 24.5% and 20.0%, respectively. Three other important competencies also improved: designing epidemiologic surveys, collecting information from the literature and doing statistical analyses. However, preventing and controlling common diseases and dealing with emergencies remained weak. These results show the new training system should be continued, but revisions are needed to improve this training system, especially in the areas of preventing and controlling common diseases and dealing with emergencies.

An Information-Theoretic Approach for Indirect Train Traffic Monitoring Using Building Vibration

OpenAIRE

Xu, Susu; Zhang, Lin; Zhang, Pei; Noh, Hae Young

2017-01-01

This paper introduces an indirect train traffic monitoring method to detect and infer real-time train events based on the vibration response of a nearby building. Monitoring and characterizing traffic events are important for cities to improve the efficiency of transportation systems (e.g., train passing, heavy trucks, and traffic). Most prior work falls into two categories: (1) methods that require intensive labor to manually record events or (2) systems that require deployment of dedicated ...

Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

Energy Technology Data Exchange (ETDEWEB)

Talathi, S. S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-06-05

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizure detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.

Effective e-Training: Using a Course Management System and e-Learning Tools to Train Library Employees

Science.gov (United States)

See, Andrew; Teetor, Travis Stephen

2014-01-01

In the summer of 2012, the University of Arizona Libraries implemented an online training program to effectively train Access Services staff and student employees at a large academic research library. This article discusses the program, which was built using a course management system (D2L) and various e-Learning software applications (Articulate…

The Design of EMG Measurement System for Arm Strength Training Machine

Directory of Open Access Journals (Sweden)

Tze-Yee Ho

2015-01-01

Full Text Available The setup of interactive communication between arm strength training machine and the people will make exercise and rehabilitation therapy become more friendly. The employment of electromyographic not only can help physical therapy but also can achieve more effective rehabilitation. Both of the system hardware and software of the arm strength training machine with EMG system are well designed and described. The fundamental design of electromyographic measurement system based on a microcontroller is analyzed and discussed. The software programming is developed in MPLAB integrated development environment from the Microchip Technology Inc. and the friendly user interface is created as well. Finally, an arm strength training machine with electromyographic control system is realized and demonstrated. The experimental results show the feasibility and fidelity of the complete designed system.

Traffic Modelling for Moving-Block Train Control System

International Nuclear Information System (INIS)

Tang Tao; Li Keping

2007-01-01

This paper presents a new cellular automaton (CA) model for train control system simulation. In the proposed CA model, the driver reactions to train movements are captured by some updated rules. The space-time diagram of traffic flow and the trajectory of train movement is used to obtain insight into the characteristic behavior of railway traffic flow. A number of simulation results demonstrate that the proposed CA model can be successfully used for the simulations of railway traffic. Not only the characteristic behavior of railway traffic flow can be reproduced, but also the simulation values of the minimum time headway are close to the theoretical values.

Health policy and systems research training: global status and recommendations for action

Science.gov (United States)

Tancred, Tara M; Schleiff, Meike; Peters, David H

2016-01-01

Abstract Objective To investigate the characteristics of health policy and systems research training globally and to identify recommendations for improvement and expansion. Methods We identified institutions offering health policy and systems research training worldwide. In 2014, we recruited participants from identified institutions for an online survey on the characteristics of the institutions and the courses given. Survey findings were explored during in-depth interviews with selected key informants. Findings The study identified several important gaps in health policy and systems research training. There were few courses in central and eastern Europe, the Middle East, North Africa or Latin America. Most (116/152) courses were instructed in English. Institutional support for courses was often lacking and many institutions lacked the critical mass of trained individuals needed to support doctoral and postdoctoral students. There was little consistency between institutions in definitions of the competencies required for health policy and systems research. Collaboration across disciplines to provide the range of methodological perspectives the subject requires was insufficient. Moreover, the lack of alternatives to on-site teaching may preclude certain student audiences such as policy-makers. Conclusion Training in health policy and systems research is important to improve local capacity to conduct quality research in this field. We provide six recommendations to improve the content, accessibility and reach of training. First, create a repository of information on courses. Second, establish networks to support training. Third, define competencies in health policy and systems research. Fourth, encourage multidisciplinary collaboration. Fifth, expand the geographical and language coverage of courses. Finally, consider alternative teaching formats. PMID:27429488

The Effect of Online Systems Analysis Training on Aerospace Industry Business Performance: A Qualitative Study

Science.gov (United States)

Burk, Erlan

2012-01-01

Aerospace companies needed additional research on technology-based training to verify expectations when enhancing human capital through online systems analysis training. The research for online systems analysis training provided aerospace companies a means to verify expectations for systems analysis technology-based training on business…

Dedicated Barrett's surveillance sessions managed by trained endoscopists improve dysplasia detection rate.

Science.gov (United States)

Ooi, Joanne; Wilson, Patrick; Walker, Giles; Blaker, Paul; DeMartino, Sabina; O'Donohue, John; Reffitt, David; Lanaspre, Effie; Chang, Fuju; Meenan, John; Dunn, Jason M

2017-06-01

Background and study aim  Barrett's esophagus (BE)-associated dysplasia is an important marker for risk of progression to esophageal adenocarcinoma (EAC) and an indication for endoscopic therapy. However, BE surveillance technique is variable. The aim of this study was to assess the effect of dedicated BE surveillance lists on dysplasia detection rate (DDR). Patients and methods  This was a prospective study of patients undergoing BE surveillance at two hospitals - community (UHL) and upper gastrointestinal center (GSTT). Four endoscopists (Group A) were trained in Prague classification, Seattle protocol biopsy technique, and lesion detection prior to performing BE surveillance endoscopies at both sites, with dedicated time slots or lists. The DDR was then compared with historical data from 47 different endoscopists at GSTT and 24 at UHL (Group B) who had undertaken Barrett's surveillance over the preceding 5-year period. Results  A total of 729 patients with BE underwent surveillance endoscopy between 2007 and 2012. There was no significant difference in patient age, sex, or length of BE between the two groups. There was a significant difference in detection rate of confirmed indefinite or low grade dysplasia and high grade dysplasia (HGD)/EAC between the two groups: 18 % (26 /142) Group A vs. 8 % (45/587) in Group B ( P  < 0.001). Documentation of Prague criteria and adherence to the Seattle protocol was significantly higher in Group A. Conclusion  This study demonstrated that a group of trained endoscopists undertaking Barrett's surveillance on dedicated lists had significantly higher DDR than a nonspecialist cohort. These findings support the introduction of dedicated Barrett's surveillance lists. © Georg Thieme Verlag KG Stuttgart · New York.

Improved biosensor-based detection system

DEFF Research Database (Denmark)

2015-01-01

Described is a new biosensor-based detection system for effector compounds, useful for in vivo applications in e.g. screening and selecting of cells which produce a small molecule effector compound or which take up a small molecule effector compound from its environment. The detection system...... comprises a protein or RNA-based biosensor for the effector compound which indirectly regulates the expression of a reporter gene via two hybrid proteins, providing for fewer false signals or less 'noise', tuning of sensitivity or other advantages over conventional systems where the biosensor directly...

Ferromagnetic Objects Magnetovision Detection System

Directory of Open Access Journals (Sweden)

Michał Nowicki

2013-12-01

Full Text Available This paper presents the application of a weak magnetic fields magnetovision scanning system for detection of dangerous ferromagnetic objects. A measurement system was developed and built to study the magnetic field vector distributions. The measurements of the Earth’s field distortions caused by various ferromagnetic objects were carried out. The ability for passive detection of hidden or buried dangerous objects and the determination of their location was demonstrated.

Bat detective-Deep learning tools for bat acoustic signal detection.

Science.gov (United States)

Mac Aodha, Oisin; Gibb, Rory; Barlow, Kate E; Browning, Ella; Firman, Michael; Freeman, Robin; Harder, Briana; Kinsey, Libby; Mead, Gary R; Newson, Stuart E; Pandourski, Ivan; Parsons, Stuart; Russ, Jon; Szodoray-Paradi, Abigel; Szodoray-Paradi, Farkas; Tilova, Elena; Girolami, Mark; Brostow, Gabriel; Jones, Kate E

2018-03-01

Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained on full-spectrum ultrasonic audio collected along road-transects across Europe and labelled by citizen scientists from www.batdetective.org. When compared to other existing algorithms and commercial systems, we show significantly higher detection performance of search-phase echolocation calls with our test sets. As an example application, we ran our detection pipeline on bat monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system. Our detection pipeline can be used for the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale. Our proposed pipeline makes only a small number of bat specific design decisions, and with appropriate training data it could be applied to detecting other species in audio. A crucial novelty of our work is showing that with careful, non-trivial, design and implementation considerations, state-of-the-art deep learning methods can be used for accurate and efficient monitoring in audio.

Video game training and the reward system.

Science.gov (United States)

Lorenz, Robert C; Gleich, Tobias; Gallinat, Jürgen; Kühn, Simone

2015-01-01

Video games contain elaborate reinforcement and reward schedules that have the potential to maximize motivation. Neuroimaging studies suggest that video games might have an influence on the reward system. However, it is not clear whether reward-related properties represent a precondition, which biases an individual toward playing video games, or if these changes are the result of playing video games. Therefore, we conducted a longitudinal study to explore reward-related functional predictors in relation to video gaming experience as well as functional changes in the brain in response to video game training. Fifty healthy participants were randomly assigned to a video game training (TG) or control group (CG). Before and after training/control period, functional magnetic resonance imaging (fMRI) was conducted using a non-video game related reward task. At pretest, both groups showed strongest activation in ventral striatum (VS) during reward anticipation. At posttest, the TG showed very similar VS activity compared to pretest. In the CG, the VS activity was significantly attenuated. This longitudinal study revealed that video game training may preserve reward responsiveness in the VS in a retest situation over time. We suggest that video games are able to keep striatal responses to reward flexible, a mechanism which might be of critical value for applications such as therapeutic cognitive training.

Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection

Directory of Open Access Journals (Sweden)

Jayakumar Kaliappan

2015-01-01

Full Text Available An intrusion detection system (IDS helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU, there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate.

Anomaly-based intrusion detection for SCADA systems

International Nuclear Information System (INIS)

Yang, D.; Usynin, A.; Hines, J. W.

2006-01-01

Most critical infrastructure such as chemical processing plants, electrical generation and distribution networks, and gas distribution is monitored and controlled by Supervisory Control and Data Acquisition Systems (SCADA. These systems have been the focus of increased security and there are concerns that they could be the target of international terrorists. With the constantly growing number of internet related computer attacks, there is evidence that our critical infrastructure may also be vulnerable. Researchers estimate that malicious online actions may cause $75 billion at 2007. One of the interesting countermeasures for enhancing information system security is called intrusion detection. This paper will briefly discuss the history of research in intrusion detection techniques and introduce the two basic detection approaches: signature detection and anomaly detection. Finally, it presents the application of techniques developed for monitoring critical process systems, such as nuclear power plants, to anomaly intrusion detection. The method uses an auto-associative kernel regression (AAKR) model coupled with the statistical probability ratio test (SPRT) and applied to a simulated SCADA system. The results show that these methods can be generally used to detect a variety of common attacks. (authors)

Extended UTAUT to Examine the Acceptance of Web Based Training System by Public Sector

Directory of Open Access Journals (Sweden)

Thamer A Alrawashdeh

2013-01-01

Full Text Available With the development of information technology, organizations have applied e-learning system to train their employees in order to enhance the its performance. In this respect, applying web based training will enable the organization to train their employees quickly, efficiently and effectively anywhere at any time. This research aims to extend Unified Theory of Acceptance and Use Technology (UTAUT using some factors such flexibility of web based training system, system interactivity and system enjoyment, in order to explain the employees

Designing and Implementing a Family of Intrusion Detection Systems

Science.gov (United States)

2004-11-01

configure (train), generates many false alarms – Misuse detection (signature analysis) (NFR, Emerald , Snort, STAT) • Generates few false alarms • Detects...to create .rhosts file in world-writable ftp home directory – rlogin using bogus .rhosts file S0 create_file read_rhosts S3S2 login S1 STAT KN-14...world-writable ftp home directory – rlogin using bogus .rhosts file S0 create_file read_rhosts S3S2 login S1 STAT KN-17 ftp-write in STATL use ustat

Security training with interactive laser-video-disk technology

International Nuclear Information System (INIS)

Wilson, D.

1988-01-01

DOE, through its contractor EG and G Energy Measurements, Inc., has developed a state-of-the-art interactive-video system for use at the Department of Energy's Central Training Academy. Called the Security Training and Evaluation Shooting System (STRESS), the computer-driven decision shooting system employs the latest is laservideo-disk technology. STRESS is designed to provide realistic and stressful training for security inspectors employed by the DOE and its contractors. The system uses wide-screen video projection, sophisticated scenario-branching technology, and customized video scenarios especially designed for the DOE. Firing a weapon that has been modified to shoot ''laser bullets,'' and wearing a special vest that detects ''hits'': the security inspector encounters adversaries on the wide screen who can shoot or be shot by the inspector in scenarios that demand fast decisions. Based on those decisions, the computer provides instantaneous branching to different scenes, giving the inspector confrontational training with the realism and variability of real life

Minimum detectable gas concentration performance evaluation method for gas leak infrared imaging detection systems.

Science.gov (United States)

Zhang, Xu; Jin, Weiqi; Li, Jiakun; Wang, Xia; Li, Shuo

2017-04-01

Thermal imaging technology is an effective means of detecting hazardous gas leaks. Much attention has been paid to evaluation of the performance of gas leak infrared imaging detection systems due to several potential applications. The minimum resolvable temperature difference (MRTD) and the minimum detectable temperature difference (MDTD) are commonly used as the main indicators of thermal imaging system performance. This paper establishes a minimum detectable gas concentration (MDGC) performance evaluation model based on the definition and derivation of MDTD. We proposed the direct calculation and equivalent calculation method of MDGC based on the MDTD measurement system. We build an experimental MDGC measurement system, which indicates the MDGC model can describe the detection performance of a thermal imaging system to typical gases. The direct calculation, equivalent calculation, and direct measurement results are consistent. The MDGC and the minimum resolvable gas concentration (MRGC) model can effectively describe the performance of "detection" and "spatial detail resolution" of thermal imaging systems to gas leak, respectively, and constitute the main performance indicators of gas leak detection systems.

Framework for Intelligent Teaching and Training Systems -- A Study of Systems

Science.gov (United States)

Graf von Malotky, Nikolaj Troels; Martens, Alke

2016-01-01

Intelligent Tutoring System are state of the art in eLearning since the late 1980s. The earliest system have been developed in teams of psychologists and computer scientists, with the goal to investigate learning processes and, later on with the goal to intelligently support teaching and training with computers. Over the years, the eLearning hype…

An Information-Theoretic Approach for Indirect Train Traffic Monitoring Using Building Vibration

Directory of Open Access Journals (Sweden)

Susu Xu

2017-05-01

Full Text Available This paper introduces an indirect train traffic monitoring method to detect and infer real-time train events based on the vibration response of a nearby building. Monitoring and characterizing traffic events are important for cities to improve the efficiency of transportation systems (e.g., train passing, heavy trucks, and traffic. Most prior work falls into two categories: (1 methods that require intensive labor to manually record events or (2 systems that require deployment of dedicated sensors. These approaches are difficult and costly to execute and maintain. In addition, most prior work uses dedicated sensors designed for a single purpose, resulting in deployment of multiple sensor systems. This further increases costs. Meanwhile, with the increasing demands of structural health monitoring, many vibration sensors are being deployed in commercial buildings. Traffic events create ground vibration that propagates to nearby building structures inducing noisy vibration responses. We present an information-theoretic method for train event monitoring using commonly existing vibration sensors deployed for building health monitoring. The key idea is to represent the wave propagation in a building induced by train traffic as information conveyed in noisy measurement signals. Our technique first uses wavelet analysis to detect train events. Then, by analyzing information exchange patterns of building vibration signals, we infer the category of the events (i.e., southbound or northbound train. Our algorithm is evaluated with an 11-story building where trains pass by frequently. The results show that the method can robustly achieve a train event detection accuracy of up to a 93% true positive rate and an 80% true negative rate. For direction categorization, compared with the traditional signal processing method, our information-theoretic approach reduces categorization error from 32.1 to 12.1%, which is a 2.5× improvement.

A novel balance training system using multimodal biofeedback.

Science.gov (United States)

Afzal, Muhammad Raheel; Oh, Min-Kyun; Choi, Hye Young; Yoon, Jungwon

2016-04-22

A biofeedback-based balance training system can be used to provide the compromised sensory information to subjects in order to retrain their sensorimotor function. In this study, the design and evaluation of the low-cost, intuitive biofeedback system developed at Gyeongsang National University is extended to provide multimodal biofeedback for balance training by utilization of visual and haptic modalities. The system consists of a smartphone attached to the waist of the subject to provide information about tilt of the torso, a personal computer running a purpose built software to process the smartphone data and provide visual biofeedback to the subject by means of a dedicated monitor and a dedicated Phantom Omni(®) device for haptic biofeedback. For experimental verification of the system, eleven healthy young participants performed balance tasks assuming two distinct postures for 30 s each while acquiring torso tilt. The postures used were the one foot stance and the tandem Romberg stance. For both the postures, the subjects stood on a foam platform which provided a certain amount of ground instability. Post-experiment data analysis was performed using MATLAB(®) to analyze reduction in body sway. Analysis parameters based on the projection of trunk tilt information were calculated in order to ascertain the reduction in body sway and improvements in postural control. Two-way analysis of variance (ANOVA) showed no statistically significant interactions between postures and biofeedback. Post-hoc analysis revealed statistically significant reduction in body sway on provision of biofeedback. Subjects exhibited maximum body sway during no biofeedback trial, followed by either haptic or visual biofeedback and in most of the trials the multimodal biofeedback of visual and haptic together resulted in minimization of body sway, thus indicating that the multimodal biofeedback system worked well to provide significant (p biofeedback system can offer more customized training

Primary care training and the evolving healthcare system.

Science.gov (United States)

Peccoralo, Lauren A; Callahan, Kathryn; Stark, Rachel; DeCherrie, Linda V

2012-01-01

With growing numbers of patient-centered medical homes and accountable care organizations, and the potential implementation of the Patient Protection and Affordable Care Act, the provision of primary care in the United States is expanding and changing. Therefore, there is an urgent need to create more primary-care physicians and to train physicians to practice in this environment. In this article, we review the impact that the changing US healthcare system has on trainees, strategies to recruit and retain medical students and residents into primary-care internal medicine, and the preparation of trainees to work in the changing healthcare system. Recruitment methods for medical students include early preclinical exposure to patients in the primary-care setting, enhanced longitudinal patient experiences in clinical clerkships, and primary-care tracks. Recruitment methods for residents include enhanced ambulatory-care training and primary-care programs. Financial-incentive programs such as loan forgiveness may encourage trainees to enter primary care. Retaining residents in primary-care careers may be encouraged via focused postgraduate fellowships or continuing medical education to prepare primary-care physicians as both teachers and practitioners in the changing environment. Finally, to prepare primary-care trainees to effectively and efficiently practice within the changing system, educators should consider shifting ambulatory training to community-based practices, encouraging resident participation in team-based care, providing interprofessional educational experiences, and involving trainees in quality-improvement initiatives. Medical educators in primary care must think innovatively and collaboratively to effectively recruit and train the future generation of primary-care physicians. © 2012 Mount Sinai School of Medicine.

The design method and research status of vehicle detection system based on geomagnetic detection principle

Science.gov (United States)

Lin, Y. H.; Bai, R.; Qian, Z. H.

2018-03-01

Vehicle detection systems are applied to obtain real-time information of vehicles, realize traffic control and reduce traffic pressure. This paper reviews geomagnetic sensors as well as the research status of the vehicle detection system. Presented in the paper are also our work on the vehicle detection system, including detection algorithms and experimental results. It is found that the GMR based vehicle detection system has a detection accuracy up to 98% with a high potential for application in the road traffic control area.

Constrained Optimization of MIMO Training Sequences

Directory of Open Access Journals (Sweden)

Coon Justin P

2007-01-01

Full Text Available Multiple-input multiple-output (MIMO systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent detection. In some special cases optimal, in the sense of mean-squared error (MSE, training sequences have been designed. However, in many practical systems it is not feasible to analytically find optimal solutions and numerical techniques must be used. In this paper, two systems (unique word (UW single carrier and OFDM with nulled subcarriers are considered and a method of designing near-optimal training sequences using nonlinear optimization techniques is proposed. In particular, interior-point (IP algorithms such as the barrier method are discussed. Although the two systems seem unrelated, the cost function, which is the MSE of the channel estimate, is shown to be effectively the same for each scenario. Also, additional constraints, such as peak-to-average power ratio (PAPR, are considered and shown to be easily included in the optimization process. Numerical examples illustrate the effectiveness of the designed training sequences, both in terms of MSE and bit-error rate (BER.

Counter Trafficking System Development "Analysis Training Program"

Energy Technology Data Exchange (ETDEWEB)

Peterson, Dennis C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2010-12-01

This document will detail the training curriculum for the Counter-Trafficking System Development (CTSD) Analysis Modules and Lesson Plans are derived from the United States Military, Department of Energy doctrine and Lawrence Livermore National Laboratory (LLNL), Global Security (GS) S Program.

Failure detection studies by layered neural network

International Nuclear Information System (INIS)

Ciftcioglu, O.; Seker, S.; Turkcan, E.

1991-06-01

Failure detection studies by layered neural network (NN) are described. The particular application area is an operating nuclear power plant and the failure detection is of concern as result of system surveillance in real-time. The NN system is considered to be consisting of 3 layers, one of which being hidden, and the NN parameters are determined adaptively by the backpropagation (BP) method, the process being the training phase. Studies are performed using the power spectra of the pressure signal of the primary system of an operating nuclear power plant of PWR type. The studies revealed that, by means of NN approach, failure detection can effectively be carried out using the redundant information as well as this is the case in this work; namely, from measurement of the primary pressure signals one can estimate the primary system coolant temperature and hence the deviation from the operational temperature state, the operational status identified in the training phase being referred to as normal. (author). 13 refs.; 4 figs.; 2 tabs

Microcomputer Intelligence for Technical Training (MITT): The evolution of an intelligent tutoring system

Science.gov (United States)

Norton, Jeffrey E.; Wiederholt, Bradley J.; Johnson, William B.

1990-01-01

Microcomputer Intelligence for Technical Training (MITT) uses Intelligent Tutoring System (OTS) technology to deliver diagnostic training in a variety of complex technical domains. Over the past six years, MITT technology has been used to develop training systems for nuclear power plant diesel generator diagnosis, Space Shuttle fuel cell diagnosis, and message processing diagnosis for the Minuteman missile. Presented here is an overview of the MITT system, describing the evolution of the MITT software and the benefits of using the MITT system.

An experimental study on a training support system utilizing trainee's eye gaze point and think aloud protocol for diagnosing nuclear power plant anomalies

International Nuclear Information System (INIS)

Ozawa, Takahisa; Samejima, Ryouta; Shimoda, Hiroshi; Yoshikawa, Hidekazu

2003-01-01

An experimental system has been developed for aiming at supporting the simulator training of diagnosis nuclear power plant anomaly, where an expert provides the instructions to a trainee by his/her own educational and experienced point of view. This system has several characteristics as follows: (1) the expert can provide the instruction through the local area network or the Internet, (2) the training task is the detection of the primary cause of plant anomaly, which is not including the plant operation but requires only thinking, and (3) the system can automatically detects the trainee's view-point and think aloud protocols and provide these two types of information to the expert in real time for supporting his/her instruction. A laboratory experiment using this system was conducted, where an expert, who had really engaged in plant operation as a chief operator, was employed as the instructor for novice students. As the result of analyzing the experimental data, it was found that the two types of information, trainee's viewpoints and his verbal protocols, have some potential of effectiveness for supporting the instructor to estimate the trainees diagnostic thinking process and provide the instruction. (author)

A wireless sensor system for a biofeedback training of hammer throwers.

Science.gov (United States)

Wang, Ye; Wan, Bingjun; Li, Hua; Shan, Gongbing

2016-01-01

Hammer-throw has a long-standing history in track and field, but unlike some other sports events, men's hammer throw has not seen a new world record since 1986. One of the possible reasons for this stagnation could be the lack of real-time biomechanical feedback training. In this study, we proposed to establish scientifically described training targets and routes, which in turn required tools that could measure and quantify characteristics of an effective hammer-throw. Towards this goal, we have developed a real-time biomechanical feedback device-a wireless sensor system-to help the training of hammer-throw. The system includes two sensors-an infrared proximity sensor for tracing the hip vertical movement and a load cell for recording the wire tension during a hammer-throw. The system uses XBees for data transmission and an Arduino processor for data processing and system control. The results revealed that the wire tension measurement could supply sufficient key features for coaches to analyze hammer-throw and give real-time feedback for improving training efficiency.

Network Intrusion Detection System using Apache Storm

Directory of Open Access Journals (Sweden)

Muhammad Asif Manzoor

2017-06-01

Full Text Available Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99 dataset to test and evaluate our proposed solution.

Web Based Information System for Job Training Activities Using Personal Extreme Programming (PXP)

Science.gov (United States)

Asri, S. A.; Sunaya, I. G. A. M.; Rudiastari, E.; Setiawan, W.

2018-01-01

Job training is one of the subjects in university or polytechnic that involves many users and reporting activities. Time and distance became problems for users to reporting and to do obligations tasks during job training due to the location where the job training took place. This research tried to develop a web based information system of job training to overcome the problems. This system was developed using Personal Extreme Programming (PXP). PXP is one of the agile methods is combination of Extreme Programming (XP) and Personal Software Process (PSP). The information system that has developed and tested which are 24% of users are strongly agree, 74% are agree, 1% disagree and 0% strongly disagree about system functionality.

Safeguards training at Pacific Northwest Laboratory

International Nuclear Information System (INIS)

Dickman, D.A.

1986-10-01

Safeguarding our country's nuclear materials against theft or diversion is extremely important due to their significantly strategic value. In addition, nuclear materials also have an extremely high monetary value. The term ''safeguards'' is defined as an integrated system of physical protection, accountability, and material control measures designed to deter, prevent, detect, and respond to unauthorized possession and use of special nuclear materials. An aggressive Safeguards program, therefore, employs both good security measures and a strong material control and accountability system. For effective internal control of nuclear materials, having people qualified in the many aspects of safeguards and accountability is essential. At Pacific Northwest Laboratory (PNL), this goal is accomplished through a Laboratory-wide Safeguards Awareness Program. All PNL staff members receive a level of Safeguards training appropriate to their particular function within the Laboratory. This paper presents an overview of the unique training opportunities this topic provides and how the training goals are accomplished through the various training courses given to the staff members

Transistor-based particle detection systems and methods

Science.gov (United States)

Jain, Ankit; Nair, Pradeep R.; Alam, Muhammad Ashraful

2015-06-09

Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

Training programs for the systems approach to nuclear security

International Nuclear Information System (INIS)

Ellis, Doris E.

2005-01-01

In support of the US Government and the International Atomic Energy Agency (IAEA) Nuclear Security Programmes, Sandia National Laboratories (SNL) has advocated and practiced a risk-based, systematic approach to nuclear security. The risk equation has been implemented as the basis for a performance methodology for the design and evaluation of Physical Protection Systems against a Design Basis Threat (DBT) for theft or sabotage of nuclear and/or radiological materials. Since integrated systems must include people as well as technology and the man-machine interface, a critical aspect of the human element is to train all stakeholders in nuclear security on the systems approach. Current training courses have been beneficial but are still limited in scope. SNL has developed two primary international courses and is completing development of three new courses that will be offered and presented in the near term. In the long-term, SNL envisions establishing a comprehensive nuclear security training curriculum that will be developed along with a series of forthcoming IAEA Nuclear Security Series guidance documents.

Intelligent control of a planning system for astronaut training.

Science.gov (United States)

Ortiz, J; Chen, G

1999-07-01

This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center.

Remote detection system

International Nuclear Information System (INIS)

Nixon, K.V.; France, S.W.; Garcia, C.; Hastings, R.D.

1981-05-01

A newly designed remote detection system has been developed at Los Alamos that allows the collection of high-resolution gamma-ray spectra and neutron data from a remote location. The system consists of the remote unit and a command unit. The remote unit collects data in a potentially hostile environment while the operator controls the unit by either radio or wire link from a safe position. Both units are battery powered and are housed in metal carrying cases

Android malware detection based on evolutionary super-network

Science.gov (United States)

Yan, Haisheng; Peng, Lingling

2018-04-01

In the paper, an android malware detection method based on evolutionary super-network is proposed in order to improve the precision of android malware detection. Chi square statistics method is used for selecting characteristics on the basis of analyzing android authority. Boolean weighting is utilized for calculating characteristic weight. Processed characteristic vector is regarded as the system training set and test set; hyper edge alternative strategy is used for training super-network classification model, thereby classifying test set characteristic vectors, and it is compared with traditional classification algorithm. The results show that the detection method proposed in the paper is close to or better than traditional classification algorithm. The proposed method belongs to an effective Android malware detection means.

Video Game Training and the Reward System

Directory of Open Access Journals (Sweden)

Robert C. Lorenz

2015-02-01

Full Text Available Video games contain elaborate reinforcement and reward schedules that have the potential to maximize motivation. Neuroimaging studies suggest that video games might have an influence on the reward system. However, it is not clear whether reward-related properties represent a precondition, which biases an individual towards playing video games, or if these changes are the result of playing video games. Therefore, we conducted a longitudinal study to explore reward-related functional predictors in relation to video gaming experience as well as functional changes in the brain in response to video game training.Fifty healthy participants were randomly assigned to a video game training (TG or control group (CG. Before and after training/control period, functional magnetic resonance imaging (fMRI was conducted using a non-video game related reward task.At pretest, both groups showed strongest activation in ventral striatum (VS during reward anticipation. At posttest, the TG showed very similar VS activity compared to pretest. In the CG, the VS activity was significantly attenuated.This longitudinal study revealed that video game training may preserve reward responsiveness in the ventral striatum in a retest situation over time. We suggest that video games are able to keep striatal responses to reward flexible, a mechanism which might be of critical value for applications such as therapeutic cognitive training.

Video game training and the reward system

Science.gov (United States)

Lorenz, Robert C.; Gleich, Tobias; Gallinat, Jürgen; Kühn, Simone

2015-01-01

Video games contain elaborate reinforcement and reward schedules that have the potential to maximize motivation. Neuroimaging studies suggest that video games might have an influence on the reward system. However, it is not clear whether reward-related properties represent a precondition, which biases an individual toward playing video games, or if these changes are the result of playing video games. Therefore, we conducted a longitudinal study to explore reward-related functional predictors in relation to video gaming experience as well as functional changes in the brain in response to video game training. Fifty healthy participants were randomly assigned to a video game training (TG) or control group (CG). Before and after training/control period, functional magnetic resonance imaging (fMRI) was conducted using a non-video game related reward task. At pretest, both groups showed strongest activation in ventral striatum (VS) during reward anticipation. At posttest, the TG showed very similar VS activity compared to pretest. In the CG, the VS activity was significantly attenuated. This longitudinal study revealed that video game training may preserve reward responsiveness in the VS in a retest situation over time. We suggest that video games are able to keep striatal responses to reward flexible, a mechanism which might be of critical value for applications such as therapeutic cognitive training. PMID:25698962

Noisy visual feedback training impairs detection of self-generated movement error: implications for anosognosia for hemiplegia

Directory of Open Access Journals (Sweden)

Catherine ePreston

2014-06-01

Full Text Available Anosognosia for hemiplegia (AHP is characterised as a disorder in which patients are unaware of their contralateral motor deficit. Many current theories for unawareness in AHP are based on comparator model accounts of the normal experience of agency. According to such models, while small mismatches between predicted and actual feedback allow unconscious fine-tuning of normal actions, mismatches that surpass an inherent threshold reach conscious awareness and inform judgements of agency (whether a given movement is produced by the self or another agent. This theory depends on a threshold for consciousness that is greater than the intrinsic noise in the system to reduce the occurrence of incorrect rejections of self-generated movements and maintain a fluid experience of agency. Pathological increases to this threshold could account for reduced motor awareness following brain injury, including AHP. The current experiment tested this hypothesis in healthy controls by exposing them to training in which noise was applied the visual feedback of their normal reaches. Subsequent self/other attribution tasks without noise revealed a decrease in the ability to detect manipulated (other feedback compared to training without noise. This suggests a slackening of awareness thresholds in the comparator model that may help to explain clinical observations of decreased action awareness following stroke.

Interactive wiimote gaze stabilization exercise training system for patients with vestibular hypofunction.

Science.gov (United States)

Chen, Po-Yin; Hsieh, Wan-Ling; Wei, Shun-Hwa; Kao, Chung-Lan

2012-10-09

Peripheral vestibular hypofunction is a major cause of dizziness. When complicated with postural imbalance, this condition can lead to an increased incidence of falls. In traditional clinical practice, gaze stabilization exercise is commonly used to rehabilitate patients. In this study, we established a computer-aided vestibular rehabilitation system by coupling infrared LEDs to an infrared receiver. This system enabled the subjects' head-turning actions to be quantified, and the training was performed using vestibular exercise combined with computer games and interactive video games that simulate daily life activities. Three unilateral and one bilateral vestibular hypofunction patients volunteered to participate in this study. The participants received 30 minutes of computer-aided vestibular rehabilitation training 2 days per week for 6 weeks. Pre-training and post-training assessments were completed, and a follow-up assessment was completed 1 month after the end of the training period. After 6 weeks of training, significant improvements in balance and dynamic visual acuity (DVA) were observed in the four participants. Self-reports of dizziness, anxiety and depressed mood all decreased significantly. Significant improvements in self-confidence and physical performance were also observed. The effectiveness of this training was maintained for at least 1 month after the end of the training period. Real-time monitoring of training performance can be achieved using this rehabilitation platform. Patients demonstrated a reduction in dizziness symptoms after 6 weeks of training with this short-term interactive game approach. This treatment paradigm also improved the patients' balance function. This system could provide a convenient, safe and affordable treatment option for clinical practitioners.

Detection of driving fatigue by using noncontact EMG and ECG signals measurement system.

Science.gov (United States)

Fu, Rongrong; Wang, Hong

2014-05-01

Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov-Smirnov Z test, the peak factor of EMG (p fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.

Virtual Reality-Based Center of Mass-Assisted Personalized Balance Training System

Directory of Open Access Journals (Sweden)

Deepesh Kumar

2018-01-01

Full Text Available Poststroke hemiplegic patients often show altered weight distribution with balance disorders, increasing their risk of fall. Conventional balance training, though powerful, suffers from scarcity of trained therapists, frequent visits to clinics to get therapy, one-on-one therapy sessions, and monotony of repetitive exercise tasks. Thus, technology-assisted balance rehabilitation can be an alternative solution. Here, we chose virtual reality as a technology-based platform to develop motivating balance tasks. This platform was augmented with off-the-shelf available sensors such as Nintendo Wii balance board and Kinect to estimate one’s center of mass (CoM. The virtual reality-based CoM-assisted balance tasks (Virtual CoMBaT was designed to be adaptive to one’s individualized weight-shifting capability quantified through CoM displacement. Participants were asked to interact with Virtual CoMBaT that offered tasks of varying challenge levels while adhering to ankle strategy for weight shifting. To facilitate the patients to use ankle strategy during weight-shifting, we designed a heel lift detection module. A usability study was carried out with 12 hemiplegic patients. Results indicate the potential of our system to contribute to improving one’s overall performance in balance-related tasks belonging to different difficulty levels.

Pothole Detection System Using a Black-box Camera

Directory of Open Access Journals (Sweden)

Youngtae Jo

2015-11-01

Full Text Available Aging roads and poor road-maintenance systems result a large number of potholes, whose numbers increase over time. Potholes jeopardize road safety and transportation efficiency. Moreover, they are often a contributing factor to car accidents. To address the problems associated with potholes, the locations and size of potholes must be determined quickly. Sophisticated road-maintenance strategies can be developed using a pothole database, which requires a specific pothole-detection system that can collect pothole information at low cost and over a wide area. However, pothole repair has long relied on manual detection efforts. Recent automatic detection systems, such as those based on vibrations or laser scanning, are insufficient to detect potholes correctly and inexpensively owing to the unstable detection of vibration-based methods and high costs of laser scanning-based methods. Thus, in this paper, we introduce a new pothole-detection system using a commercial black-box camera. The proposed system detects potholes over a wide area and at low cost. We have developed a novel pothole-detection algorithm specifically designed to work with the embedded computing environments of black-box cameras. Experimental results are presented with our proposed system, showing that potholes can be detected accurately in real-time.