Emerging technologies with potential for objectively evaluating speech recognition skills.

Science.gov (United States)

Rawool, Vishakha Waman

2016-01-01

Work-related exposure to noise and other ototoxins can cause damage to the cochlea, synapses between the inner hair cells, the auditory nerve fibers, and higher auditory pathways, leading to difficulties in recognizing speech. Procedures designed to determine speech recognition scores (SRS) in an objective manner can be helpful in disability compensation cases where the worker claims to have poor speech perception due to exposure to noise or ototoxins. Such measures can also be helpful in determining SRS in individuals who cannot provide reliable responses to speech stimuli, including patients with Alzheimer's disease, traumatic brain injuries, and infants with and without hearing loss. Cost-effective neural monitoring hardware and software is being rapidly refined due to the high demand for neurogaming (games involving the use of brain-computer interfaces), health, and other applications. More specifically, two related advances in neuro-technology include relative ease in recording neural activity and availability of sophisticated analysing techniques. These techniques are reviewed in the current article and their applications for developing objective SRS procedures are proposed. Issues related to neuroaudioethics (ethics related to collection of neural data evoked by auditory stimuli including speech) and neurosecurity (preservation of a person's neural mechanisms and free will) are also discussed.

Technical Reviews on Pattern Recognition in Process Analytical Technology

International Nuclear Information System (INIS)

Kim, Jong Yun; Choi, Yong Suk; Ji, Sun Kyung; Park, Yong Joon; Song, Kyu Seok; Jung, Sung Hee

2008-12-01

Pattern recognition is one of the first and the most widely adopted chemometric tools among many active research area in chemometrics such as design of experiment(DoE), pattern recognition, multivariate calibration, signal processing. Pattern recognition has been used to identify the origin of a wine and the time of year that the vine was grown by using chromatography, cause of fire by using GC/MS chromatography, detection of explosives and land mines, cargo and luggage inspection in seaports and airports by using a prompt gamma-ray activation analysis, and source apportionment of environmental pollutant by using a stable isotope ratio mass spectrometry. Recently, pattern recognition has been taken into account as a major chemometric tool in the so-called 'process analytical technology (PAT)', which is a newly-developed concept in the area of process analytics proposed by US Food and Drug Administration (US FDA). For instance, identification of raw material by using a pattern recognition analysis plays an important role for the effective quality control of the production process. Recently, pattern recognition technique has been used to identify the spatial distribution and uniformity of the active ingredients present in the product such as tablet by transforming the chemical data into the visual information

Gait recognition based on integral outline

Science.gov (United States)

Ming, Guan; Fang, Lv

2017-02-01

Biometric identification technology replaces traditional security technology, which has become a trend, and gait recognition also has become a hot spot of research because its feature is difficult to imitate and theft. This paper presents a gait recognition system based on integral outline of human body. The system has three important aspects: the preprocessing of gait image, feature extraction and classification. Finally, using a method of polling to evaluate the performance of the system, and summarizing the problems existing in the gait recognition and the direction of development in the future.

Evaluation of Adaptive Noise Management Technologies for School-Age Children with Hearing Loss.

Science.gov (United States)

Wolfe, Jace; Duke, Mila; Schafer, Erin; Jones, Christine; Rakita, Lori

2017-05-01

Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations. The objective of this study was to compare speech recognition, speech intelligibility ratings (SIRs), and sound preferences of children using hearing aids equipped with and without adaptive noise management technologies. A single-group, repeated measures design was used to evaluate performance differences obtained in four simulated environments. In each simulated environment, participants were tested in a basic listening program with minimal noise management features, a manual program designed for that scene, and the hearing instruments' adaptive operating system that steered hearing instrument parameterization based on the characteristics of the environment. Twelve children with mild to moderately severe sensorineural hearing loss. Speech recognition and SIRs were evaluated in three hearing aid programs with and without noise management technologies across two different test sessions and various listening environments. Also, the participants' perceptual hearing performance in daily real-world listening situations with two of the hearing aid programs was evaluated during a four- to six-week field trial that took place between the two laboratory sessions. On average, the use of adaptive noise management technology improved sentence recognition in noise for speech presented in front of the participant but resulted in a decrement in performance for signals arriving from behind when the participant was facing forward. However, the improvement

Evaluation of Extended-Wear Hearing Technology for Children with Hearing Loss.

Science.gov (United States)

Wolfe, Jace; Schafer, Erin; Martella, Natalie; Morais, Mila; Mann, Misty

2015-01-01

Research shows that many older children and teenagers who have mild to moderately severe sensorineural hearing loss do not use their hearing instruments during all waking hours. A variety of reasons may contribute toward this problem, including concerns about cosmetics associated with hearing aid use and the inconvenience of daily maintenance associated with hearing instruments. Extended-wear hearing instruments are inserted into the wearer's ear canal by an audiologist and are essentially invisible to outside observers. The goal of this study was to evaluate the potential benefits and limitations associated with use of extended-wear hearing instruments in a group of children with hearing loss. A two-way repeated measures design was used to examine performance differences obtained with the participants' daily-wear hearing instruments versus that obtained with extended-wear hearing instruments. Sixteen children, ages 10-17 yr old, with sensorineural hearing loss ranging from mild to moderately severe. Probe microphone measures were completed to evaluate the aided output of device. Behavioral test measures included word recognition in quiet, sentence recognition in noise, aided warble-tone thresholds, and psychophysical loudness scaling. Questionnaires were also administered to evaluate subjective performance with each hearing technology. Data logging suggested that many participants were not using their daily-wear hearing instruments during all waking hours (mean use was less than 6 h/day). Real ear probe microphone measurements indicated that a closer fit to the Desired Sensation Level Version 5 prescriptive targets was achieved with the children's daily-wear instruments when compared to the extended-wear instruments. There was no statistically significant difference in monosyllabic word recognition at 50 or 60 dBA obtained with the two hearing technologies. Sentence recognition in noise obtained with use of the extended-wear devices was, however, significantly

Wireless Technology Recognition Based on RSSI Distribution at Sub-Nyquist Sampling Rate for Constrained Devices.

Science.gov (United States)

Liu, Wei; Kulin, Merima; Kazaz, Tarik; Shahid, Adnan; Moerman, Ingrid; De Poorter, Eli

2017-09-12

Driven by the fast growth of wireless communication, the trend of sharing spectrum among heterogeneous technologies becomes increasingly dominant. Identifying concurrent technologies is an important step towards efficient spectrum sharing. However, due to the complexity of recognition algorithms and the strict condition of sampling speed, communication systems capable of recognizing signals other than their own type are extremely rare. This work proves that multi-model distribution of the received signal strength indicator (RSSI) is related to the signals' modulation schemes and medium access mechanisms, and RSSI from different technologies may exhibit highly distinctive features. A distinction is made between technologies with a streaming or a non-streaming property, and appropriate feature spaces can be established either by deriving parameters such as packet duration from RSSI or directly using RSSI's probability distribution. An experimental study shows that even RSSI acquired at a sub-Nyquist sampling rate is able to provide sufficient features to differentiate technologies such as Wi-Fi, Long Term Evolution (LTE), Digital Video Broadcasting-Terrestrial (DVB-T) and Bluetooth. The usage of the RSSI distribution-based feature space is illustrated via a sample algorithm. Experimental evaluation indicates that more than 92% accuracy is achieved with the appropriate configuration. As the analysis of RSSI distribution is straightforward and less demanding in terms of system requirements, we believe it is highly valuable for recognition of wideband technologies on constrained devices in the context of dynamic spectrum access.

[Application of image recognition technology in census of national traditional Chinese medicine resources].

Science.gov (United States)

Zhang, Xiao-Bo; Ge, Xiao-Guang; Jin, Yan; Shi, Ting-Ting; Wang, Hui; Li, Meng; Jing, Zhi-Xian; Guo, Lan-Ping; Huang, Lu-Qi

2017-11-01

With the development of computer and image processing technology, image recognition technology has been applied to the national medicine resources census work at all stages.Among them: ①In the preparatory work, in order to establish a unified library of traditional Chinese medicine resources, using text recognition technology based on paper materials, be the assistant in the digitalization of various categories related to Chinese medicine resources; to determine the representative area and plots of the survey from each census team, based on the satellite remote sensing image and vegetation map and other basic data, using remote sensing image classification and other technical methods to assist in determining the key investigation area. ②In the process of field investigation, to obtain the planting area of Chinese herbal medicine was accurately, we use the decision tree model, spectral feature and object-oriented method were used to assist the regional identification and area estimation of Chinese medicinal materials.③In the process of finishing in the industry, in order to be able to relatively accurately determine the type of Chinese medicine resources in the region, based on the individual photos of the plant, the specimens and the name of the use of image recognition techniques, to assist the statistical summary of the types of traditional Chinese medicine resources. ④In the application of the results of transformation, based on the pharmaceutical resources and individual samples of medicinal herbs, the development of Chinese medicine resources to identify APP and authentic herbs 3D display system, assisted the identification of Chinese medicine resources and herbs identification characteristics. The introduction of image recognition technology in the census of Chinese medicine resources, assisting census personnel to carry out related work, not only can reduce the workload of the artificial, improve work efficiency, but also improve the census results

Robustness-related issues in speaker recognition

CERN Document Server

Zheng, Thomas Fang

2017-01-01

This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book gives an overview of speaker recognition, such as the basic system framework, categories under different criteria, performance evaluation and its development history. Secondly, with regard to robustness issues, the book presents three categories, including environment-related issues, speaker-related issues and application-oriented issues. For each category, the book describes the current hot topics, existing technologies, and potential research focuses in the future. The book is a useful reference book and self-learning guide for early researchers working in the field of robust speech recognition.

Heuristics in primary care for recognition of unreported vision loss in older people: a technology development study.

Science.gov (United States)

Wijeyekoon, Skanda; Kharicha, Kalpa; Iliffe, Steve

2015-09-01

To evaluate heuristics (rules of thumb) for recognition of undetected vision loss in older patients in primary care. Vision loss is associated with ageing, and its prevalence is increasing. Visual impairment has a broad impact on health, functioning and well-being. Unrecognised vision loss remains common, and screening interventions have yet to reduce its prevalence. An alternative approach is to enhance practitioners' skills in recognising undetected vision loss, by having a more detailed picture of those who are likely not to act on vision changes, report symptoms or have eye tests. This paper describes a qualitative technology development study to evaluate heuristics for recognition of undetected vision loss in older patients in primary care. Using a previous modelling study, two heuristics in the form of mnemonics were developed to aid pattern recognition and allow general practitioners to identify potential cases of unreported vision loss. These heuristics were then analysed with experts. Findings It was concluded that their implementation in modern general practice was unsuitable and an alternative solution should be sort.

The 2016 NIST Speaker Recognition Evaluation

Science.gov (United States)

2017-08-20

impact on system performance. Index Terms: NIST evaluation, NIST SRE, speaker detection, speaker recognition, speaker verification 1. Introduction NIST... self -reported. Second, there were two training conditions in SRE16, namely fixed and open. In the fixed training condition, par- ticipants were only

Pattern recognition approach to nondestructive evaluation of materials

International Nuclear Information System (INIS)

Chen, C.H.

1987-01-01

In this paper, a pattern recognition approach to the ultrasonic nondestructive evaluation of materials is examined. Emphasis is placed on identifying effective features from time and frequency domains, correlation functions and impulse responses to classify aluminum plate specimens into three major defect geometry categories: flat, angular cut and circular hole defects. A multi-stage classification procedure is developed which can further determine the angles and sizes for defect characterization and classification. The research clearly demonstrates that the pattern recognition approach can significantly improve the nondestructive material evaluation capability of the ultrasonic methods without resorting to the solution of highly complex mathematical inverse problems

High-performance speech recognition using consistency modeling

Science.gov (United States)

Digalakis, Vassilios; Murveit, Hy; Monaco, Peter; Neumeyer, Leo; Sankar, Ananth

1994-12-01

The goal of SRI's consistency modeling project is to improve the raw acoustic modeling component of SRI's DECIPHER speech recognition system and develop consistency modeling technology. Consistency modeling aims to reduce the number of improper independence assumptions used in traditional speech recognition algorithms so that the resulting speech recognition hypotheses are more self-consistent and, therefore, more accurate. At the initial stages of this effort, SRI focused on developing the appropriate base technologies for consistency modeling. We first developed the Progressive Search technology that allowed us to perform large-vocabulary continuous speech recognition (LVCSR) experiments. Since its conception and development at SRI, this technique has been adopted by most laboratories, including other ARPA contracting sites, doing research on LVSR. Another goal of the consistency modeling project is to attack difficult modeling problems, when there is a mismatch between the training and testing phases. Such mismatches may include outlier speakers, different microphones and additive noise. We were able to either develop new, or transfer and evaluate existing, technologies that adapted our baseline genonic HMM recognizer to such difficult conditions.

Recognition and development of "educational technology" as a scientific field and school subject

Directory of Open Access Journals (Sweden)

Danilović Mirčeta S.

2004-01-01

Full Text Available The paper explores the process of development, establishment and recognition of "educational technology" as an independent scientific field and a separate teaching subject at universities. The paper points to: (a the problems that this field deals with or should deal with, (b knowledge needed for the profession of "educational technologist", (c various scientific institutions across the world involved in educational technology, (d scientific journals treating issues of modern educational technology, (e the authors i.e. psychologists and educators who developed and formulated the basic principles of this scientific field, (f educational features and potentials of educational technologies. Emphasis is placed on the role and importance of AV technology in developing, establishing and recognition of educational technology, and it is also pointed out that AV technology i.e. AV teaching aids and a movement for visualization of teaching were its forerunners and crucial factors for its establishing and developing into an independent area of teaching i.e. school subject. In summary it is stressed that educational technology provides for the execution of instruction through emission transmission, selection, coding, decoding, reception, memorization transformation of all types of pieces of information in teaching.

A usability evaluation of an interactive application for halal products using optical character recognition and augmented reality technologies

Science.gov (United States)

Lam, Meng Chun; Nizam, Siti Soleha Muhammad; Arshad, Haslina; A'isyah Ahmad Shukri, Saidatul; Hashim, Nurhazarifah Che; Putra, Haekal Mozzia; Abidin, Rimaniza Zainal

2017-10-01

This article discusses the usability of an interactive application for halal products using Optical Character Recognition (OCR) and Augmented Reality (AR) technologies. Among the problems that have been identified in this study is that consumers have little knowledge about the E-Code. Therefore, users often have doubts about the halal status of the product. Nowadays, the integrity of halal status can be doubtful due to the actions of some irresponsible people spreading false information about a product. Therefore, an application that uses OCR and AR technology developed in this study will help the users to identify the information content of a product by scanning the E-Code label and by scanning the product's brand to know the halal status of the product. In this application, E-Code on the label of a product is scanned using OCR technology to display information about the E-Code. The product's brand is scan using augmented reality technology to display halal status of the product. The findings reveal that users are satisfied with this application and it is useful and easy to use.

Touchless palmprint recognition systems

CERN Document Server

Genovese, Angelo; Scotti, Fabio

2014-01-01

This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems.It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Const

VASIR: An Open-Source Research Platform for Advanced Iris Recognition Technologies.

Science.gov (United States)

Lee, Yooyoung; Micheals, Ross J; Filliben, James J; Phillips, P Jonathon

2013-01-01

The performance of iris recognition systems is frequently affected by input image quality, which in turn is vulnerable to less-than-optimal conditions due to illuminations, environments, and subject characteristics (e.g., distance, movement, face/body visibility, blinking, etc.). VASIR (Video-based Automatic System for Iris Recognition) is a state-of-the-art NIST-developed iris recognition software platform designed to systematically address these vulnerabilities. We developed VASIR as a research tool that will not only provide a reference (to assess the relative performance of alternative algorithms) for the biometrics community, but will also advance (via this new emerging iris recognition paradigm) NIST's measurement mission. VASIR is designed to accommodate both ideal (e.g., classical still images) and less-than-ideal images (e.g., face-visible videos). VASIR has three primary modules: 1) Image Acquisition 2) Video Processing, and 3) Iris Recognition. Each module consists of several sub-components that have been optimized by use of rigorous orthogonal experiment design and analysis techniques. We evaluated VASIR performance using the MBGC (Multiple Biometric Grand Challenge) NIR (Near-Infrared) face-visible video dataset and the ICE (Iris Challenge Evaluation) 2005 still-based dataset. The results showed that even though VASIR was primarily developed and optimized for the less-constrained video case, it still achieved high verification rates for the traditional still-image case. For this reason, VASIR may be used as an effective baseline for the biometrics community to evaluate their algorithm performance, and thus serves as a valuable research platform.

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

Science.gov (United States)

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

2018-03-01

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

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

Directory of Open Access Journals (Sweden)

Feng Qin

Full Text Available Common leaf spot (caused by Pseudopeziza medicaginis, rust (caused by Uromyces striatus, Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana and Cercospora leaf spot (caused by Cercospora medicaginis are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis. After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection, disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features was the optimal model. For this SVM model, the

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

Science.gov (United States)

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the

Evaluation of context effects in sentence recognition

NARCIS (Netherlands)

Bronkhorst, A.W.; Brand, T.; Wagener, K.

2002-01-01

It was investigated whether the model for context effects, developed earlier by Bronkhorst et al. [J. Acoust. Soc. Am. 93, 499-509 (1993)], can be applied to results of sentence tests, used for the evaluation of speech recognition. Data for two German sentence tests, that differed with respect to

Evaluating structural pattern recognition for handwritten math via primitive label graphs

Science.gov (United States)

Zanibbi, Richard; Mouchère, Harold; Viard-Gaudin, Christian

2013-01-01

Currently, structural pattern recognizer evaluations compare graphs of detected structure to target structures (i.e. ground truth) using recognition rates, recall and precision for object segmentation, classification and relationships. In document recognition, these target objects (e.g. symbols) are frequently comprised of multiple primitives (e.g. connected components, or strokes for online handwritten data), but current metrics do not characterize errors at the primitive level, from which object-level structure is obtained. Primitive label graphs are directed graphs defined over primitives and primitive pairs. We define new metrics obtained by Hamming distances over label graphs, which allow classification, segmentation and parsing errors to be characterized separately, or using a single measure. Recall and precision for detected objects may also be computed directly from label graphs. We illustrate the new metrics by comparing a new primitive-level evaluation to the symbol-level evaluation performed for the CROHME 2012 handwritten math recognition competition. A Python-based set of utilities for evaluating, visualizing and translating label graphs is publicly available.

The Affordance of Speech Recognition Technology for EFL Learning in an Elementary School Setting

Science.gov (United States)

Liaw, Meei-Ling

2014-01-01

This study examined the use of speech recognition (SR) technology to support a group of elementary school children's learning of English as a foreign language (EFL). SR technology has been used in various language learning contexts. Its application to EFL teaching and learning is still relatively recent, but a solid understanding of its…

A formative evaluation of a staff reward and recognition programme

Directory of Open Access Journals (Sweden)

Saleemah Salie

2012-07-01

Research purpose: The main aim of this evaluation was to test the plausibility of the programme theory underlying a staff reward and recognition programme within a retail setting. Secondary aims were to assess whether or not the programme was implemented as intended and whether or not its outcomes were well defined. Motivation for the study: Different groups of people may have different assumptions about whether a reward and recognition programme works or not. This evaluation was motivated by the different assumptions held by programme stakeholders, programme recipients and social science researchers regarding the programme. Research design, approach and method: This formative evaluation used a descriptive design. Primary qualitative data were collected by means of structured interviews with the Human Resource Development (HRD Facilitator and ten programme participants. Main findings: The results showed that the programme theory was not plausible and that the programme was not implemented as intended. Although the HRD Facilitator and the participants agreed that the programme led to improved customer service, they disagreed about the other programme outcomes. Practical/managerial implications: This evaluation contains practical suggestions for improving the programme theory, the programme implementation process and the redefinition of the outcomes of the programme as standard performance indicators. Contribution/value-add: This evaluation contributed to the limited literature on the effect of reward and recognition programmes. Whilst there is a vast amount of literature pertaining to such programmes, very few formal evaluations exist about them.

Basics of identification measurement technology

Science.gov (United States)

Klikushin, Yu N.; Kobenko, V. Yu; Stepanov, P. P.

2018-01-01

All available algorithms and suitable for pattern recognition do not give 100% guarantee, therefore there is a field of scientific night activity in this direction, studies are relevant. It is proposed to develop existing technologies for pattern recognition in the form of application of identification measurements. The purpose of the study is to identify the possibility of recognizing images using identification measurement technologies. In solving problems of pattern recognition, neural networks and hidden Markov models are mainly used. A fundamentally new approach to the solution of problems of pattern recognition based on the technology of identification signal measurements (IIS) is proposed. The essence of IIS technology is the quantitative evaluation of the shape of images using special tools and algorithms.

Iris recognition via plenoptic imaging

Science.gov (United States)

Santos-Villalobos, Hector J.; Boehnen, Chris Bensing; Bolme, David S.

2017-11-07

Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios.

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

Science.gov (United States)

Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

A Survey of Evaluation in Music Genre Recognition

DEFF Research Database (Denmark)

Sturm, Bob L.

2012-01-01

Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic data, and other modalities. While reviews have been written of some of this work before, no survey has been made of the approaches to evaluating approaches to MGR. This paper compiles a bibliography of work...

Non-Cooperative Facial Recognition Video Dataset Collection Plan

Energy Technology Data Exchange (ETDEWEB)

Kimura, Marcia L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Erikson, Rebecca L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lombardo, Nicholas J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2013-08-31

The Pacific Northwest National Laboratory (PNNL) will produce a non-cooperative (i.e. not posing for the camera) facial recognition video data set for research purposes to evaluate and enhance facial recognition systems technology. The aggregate data set consists of 1) videos capturing PNNL role players and public volunteers in three key operational settings, 2) photographs of the role players for enrolling in an evaluation database, and 3) ground truth data that documents when the role player is within various camera fields of view. PNNL will deliver the aggregate data set to DHS who may then choose to make it available to other government agencies interested in evaluating and enhancing facial recognition systems. The three operational settings that will be the focus of the video collection effort include: 1) unidirectional crowd flow 2) bi-directional crowd flow, and 3) linear and/or serpentine queues.

A Compact Methodology to Understand, Evaluate, and Predict the Performance of Automatic Target Recognition

Science.gov (United States)

Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Chen, Yiping; Zhuang, Zhaowen; Cheng, Yongqiang; Deng, Bin; Wang, Liandong; Zeng, Yonghu; Gao, Lei

2014-01-01

This paper offers a compacted mechanism to carry out the performance evaluation work for an automatic target recognition (ATR) system: (a) a standard description of the ATR system's output is suggested, a quantity to indicate the operating condition is presented based on the principle of feature extraction in pattern recognition, and a series of indexes to assess the output in different aspects are developed with the application of statistics; (b) performance of the ATR system is interpreted by a quality factor based on knowledge of engineering mathematics; (c) through a novel utility called “context-probability” estimation proposed based on probability, performance prediction for an ATR system is realized. The simulation result shows that the performance of an ATR system can be accounted for and forecasted by the above-mentioned measures. Compared to existing technologies, the novel method can offer more objective performance conclusions for an ATR system. These conclusions may be helpful in knowing the practical capability of the tested ATR system. At the same time, the generalization performance of the proposed method is good. PMID:24967605

Development of Personalized Urination Recognition Technology Using Smart Bands

Directory of Open Access Journals (Sweden)

Sung-Jong Eun

2017-04-01

Full Text Available Purpose This study collected and analyzed activity data sensed through smart bands worn by patients in order to resolve the clinical issues posed by using voiding charts. By developing a smart band-based algorithm for recognizing urination activity in patients, this study aimed to explore the feasibility of urination monitoring systems. Methods This study aimed to develop an algorithm that recognizes urination based on a patient’s posture and changes in posture. Motion data was obtained from a smart band on the arm. An algorithm that recognizes the 3 stages of urination (forward movement, urination, backward movement was developed based on data collected from a 3-axis accelerometer and from tilt angle data. Real-time data were acquired from the smart band, and for data corresponding to a certain duration, the absolute value of the signals was calculated and then compared with the set threshold value to determine the occurrence of vibration signals. In feature extraction, the most essential information describing each pattern was identified after analyzing the characteristics of the data. The results of the feature extraction process were sorted using a classifier to detect urination. Results An experiment was carried out to assess the performance of the recognition technology proposed in this study. The final accuracy of the algorithm was calculated based on clinical guidelines for urologists. The experiment showed a high average accuracy of 90.4%, proving the robustness of the proposed algorithm. Conclusions The proposed urination recognition technology draws on acceleration data and tilt angle data collected via a smart band; these data were then analyzed using a classifier after comparative analyses with standardized feature patterns.

Object/Shape Recognition Technology: An Assessment of the Feasibility of Implementation at Defense Logistics Agency Disposition Services

Science.gov (United States)

2015-02-25

provide efficiency and effectively manufacture or inventory items. The industries that benefit from Cognex technology are automotive, food and beverage ...recognition tedmology, Tedmology Readiness Level, PAGES Cost Benefit Analysis, Tedmology Commercialization, Technology Transition 139 16. PRICE CODE 17...Technology Development & Transition Strategy Guidebook xvii UD Ultimate Disposal U.S. United States USAF United States Air Force xviii THIS

Automatic Speech Recognition Systems for the Evaluation of Voice and Speech Disorders in Head and Neck Cancer

Directory of Open Access Journals (Sweden)

Andreas Maier

2010-01-01

Full Text Available In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of intelligibility. In this study we investigate the applicability of the method to speech disorders caused by head and neck cancer. Intelligibility was quantified by speech recognition on recordings of a standard text read by 41 German laryngectomized patients with cancer of the larynx or hypopharynx and 49 German patients who had suffered from oral cancer. The speech recognition provides the percentage of correctly recognized words of a sequence, that is, the word recognition rate. Automatic evaluation was compared to perceptual ratings by a panel of experts and to an age-matched control group. Both patient groups showed significantly lower word recognition rates than the control group. Automatic speech recognition yielded word recognition rates which complied with experts' evaluation of intelligibility on a significant level. Automatic speech recognition serves as a good means with low effort to objectify and quantify the most important aspect of pathologic speech—the intelligibility. The system was successfully applied to voice and speech disorders.

MINERGY CORPORATION GLASS FURNACE TECHNOLOGY EVALUATION: INNOVATION TECHNOLOGY EVALUATION REPORT

Science.gov (United States)

This report presents performance and economic data for a U.S. Environmental Protection Agency (EPA) Superfund Innovative Technology Evaluation (SITE) Program demonstration of the Minergy Corporation (Minergy) Glass Furnace Technology (GFT). The demonstration evaluated the techno...

Analysis of Feature Extraction Methods for Speaker Dependent Speech Recognition

Directory of Open Access Journals (Sweden)

Gurpreet Kaur

2017-02-01

Full Text Available Speech recognition is about what is being said, irrespective of who is saying. Speech recognition is a growing field. Major progress is taking place on the technology of automatic speech recognition (ASR. Still, there are lots of barriers in this field in terms of recognition rate, background noise, speaker variability, speaking rate, accent etc. Speech recognition rate mainly depends on the selection of features and feature extraction methods. This paper outlines the feature extraction techniques for speaker dependent speech recognition for isolated words. A brief survey of different feature extraction techniques like Mel-Frequency Cepstral Coefficients (MFCC, Linear Predictive Coding Coefficients (LPCC, Perceptual Linear Prediction (PLP, Relative Spectra Perceptual linear Predictive (RASTA-PLP analysis are presented and evaluation is done. Speech recognition has various applications from daily use to commercial use. We have made a speaker dependent system and this system can be useful in many areas like controlling a patient vehicle using simple commands.

Evaluation of calix[4]arene tethered Schiff bases for anion recognition

International Nuclear Information System (INIS)

Chawla, H.M.; Munjal, Priyanka

2016-01-01

Two calix[4]arene tethered Schiff base derivatives (L1 and L2) have been synthesized and their ion recognition capability has been evaluated through NMR, UV–vis and fluorescence spectroscopy. L1 interacts with cyanide ions very selectively to usher a significant change in color and fluorescence intensity. On the other hand L2 does not show selectivity for anion sensing despite having the same functional groups as those present in L1. The differential observations may be attributed to plausible stereo control of anion recognition and tautomerization in the synthesized Schiff base derivatives.

Evaluation of calix[4]arene tethered Schiff bases for anion recognition

Energy Technology Data Exchange (ETDEWEB)

Chawla, H.M., E-mail: hmchawla@chemistry.iitd.ac.in; Munjal, Priyanka

2016-11-15

Two calix[4]arene tethered Schiff base derivatives (L1 and L2) have been synthesized and their ion recognition capability has been evaluated through NMR, UV–vis and fluorescence spectroscopy. L1 interacts with cyanide ions very selectively to usher a significant change in color and fluorescence intensity. On the other hand L2 does not show selectivity for anion sensing despite having the same functional groups as those present in L1. The differential observations may be attributed to plausible stereo control of anion recognition and tautomerization in the synthesized Schiff base derivatives.

An introduction to application-independent evaluation of speaker recognition systems

NARCIS (Netherlands)

Leeuwen, D.A. van; Brümmer, N.

2007-01-01

In the evaluation of speaker recognition systems - an important part of speaker classification [1], the trade-off between missed speakers and false alarms has always been an important diagnostic tool. NIST has defined the task of speaker detection with the associated Detection Cost Function (DCF) to

ROBIN: a platform for evaluating automatic target recognition algorithms: I. Overview of the project and presentation of the SAGEM DS competition

Science.gov (United States)

Duclos, D.; Lonnoy, J.; Guillerm, Q.; Jurie, F.; Herbin, S.; D'Angelo, E.

2008-04-01

The last five years have seen a renewal of Automatic Target Recognition applications, mainly because of the latest advances in machine learning techniques. In this context, large collections of image datasets are essential for training algorithms as well as for their evaluation. Indeed, the recent proliferation of recognition algorithms, generally applied to slightly different problems, make their comparisons through clean evaluation campaigns necessary. The ROBIN project tries to fulfil these two needs by putting unclassified datasets, ground truths, competitions and metrics for the evaluation of ATR algorithms at the disposition of the scientific community. The scope of this project includes single and multi-class generic target detection and generic target recognition, in military and security contexts. From our knowledge, it is the first time that a database of this importance (several hundred thousands of visible and infrared hand annotated images) has been publicly released. Funded by the French Ministry of Defence (DGA) and by the French Ministry of Research, ROBIN is one of the ten Techno-vision projects. Techno-vision is a large and ambitious government initiative for building evaluation means for computer vision technologies, for various application contexts. ROBIN's consortium includes major companies and research centres involved in Computer Vision R&D in the field of defence: Bertin Technologies, CNES, ECA, DGA, EADS, INRIA, ONERA, MBDA, SAGEM, THALES. This paper, which first gives an overview of the whole project, is focused on one of ROBIN's key competitions, the SAGEM Defence Security database. This dataset contains more than eight hundred ground and aerial infrared images of six different vehicles in cluttered scenes including distracters. Two different sets of data are available for each target. The first set includes different views of each vehicle at close range in a "simple" background, and can be used to train algorithms. The second set

The use of open and machine vision technologies for development of gesture recognition intelligent systems

Science.gov (United States)

Cherkasov, Kirill V.; Gavrilova, Irina V.; Chernova, Elena V.; Dokolin, Andrey S.

2018-05-01

The article is devoted to reflection of separate aspects of intellectual system gesture recognition development. The peculiarity of the system is its intellectual block which completely based on open technologies: OpenCV library and Microsoft Cognitive Toolkit (CNTK) platform. The article presents the rationale for the choice of such set of tools, as well as the functional scheme of the system and the hierarchy of its modules. Experiments have shown that the system correctly recognizes about 85% of images received from sensors. The authors assume that the improvement of the algorithmic block of the system will increase the accuracy of gesture recognition up to 95%.

Evaluation of missing data techniques for in-car automatic speech recognition

OpenAIRE

Wang, Y.; Vuerinckx, R.; Gemmeke, J.F.; Cranen, B.; Hamme, H. Van

2009-01-01

Wang Y., Vuerinckx R., Gemmeke J., Cranen B., Van hamme H., ''Evaluation of missing data techniques for in-car automatic speech recognition'', Proceedings NAG/DAGA 2009 - international conference on acoustics, 4 pp., March 23-26, 2009, Rotterdam, The Netherlands.

Finger Vein Recognition Based on Personalized Weight Maps

Science.gov (United States)

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Finger Vein Recognition Based on Personalized Weight Maps

Directory of Open Access Journals (Sweden)

Lu Yang

2013-09-01

Full Text Available Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs. The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons.

Science.gov (United States)

Filippoupolitis, Avgoustinos; Oliff, William; Takand, Babak; Loukas, George

2017-05-27

Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of body-worn sensors. As this approach suffers with respect to practicality, we propose the use of commercial off-the-shelf devices. In this work, we design and evaluate an activity recognition system composed of a smart watch, which is enhanced with location information coming from Bluetooth Low Energy (BLE) beacons. We evaluate the performance of this approach for a variety of activities performed in an indoor laboratory environment, using four supervised machine learning algorithms. Our experimental results indicate that our location-enhanced activity recognition system is able to reach a classification accuracy ranging from 92% to 100%, while without location information classification accuracy it can drop to as low as 50% in some cases, depending on the window size chosen for data segmentation.

Supervised and Unsupervised Speaker Adaptation in the NIST 2005 Speaker Recognition Evaluation

National Research Council Canada - National Science Library

Hansen, Eric G; Slyh, Raymond E; Anderson, Timothy R

2006-01-01

Starting in 2004, the annual NIST Speaker Recognition Evaluation (SRE) has added an optional unsupervised speaker adaptation track where test files are processed sequentially and one may update the target model...

Smartphone based face recognition tool for the blind.

Science.gov (United States)

Kramer, K M; Hedin, D S; Rolkosky, D J

2010-01-01

The inability to identify people during group meetings is a disadvantage for blind people in many professional and educational situations. To explore the efficacy of face recognition using smartphones in these settings, we have prototyped and tested a face recognition tool for blind users. The tool utilizes Smartphone technology in conjunction with a wireless network to provide audio feedback of the people in front of the blind user. Testing indicated that the face recognition technology can tolerate up to a 40 degree angle between the direction a person is looking and the camera's axis and a 96% success rate with no false positives. Future work will be done to further develop the technology for local face recognition on the smartphone in addition to remote server based face recognition.

Document recognition serving people with disabilities

Science.gov (United States)

Fruchterman, James R.

2007-01-01

Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

Evaluative conditioning of food technologies

DEFF Research Database (Denmark)

Loebnitz, Natascha; Grunert, Klaus G

2015-01-01

Consumer attitudes play an important role in the acceptance of new technologies. The success of food innovations depends on understanding how consumers form and change attitudes toward food technologies. Earlier post hoc explanations suggest that evaluative conditioning can change consumer...... attitudes toward food technologies. The present study tests how evaluative conditioning can affect consumer acceptance of new food technologies. Furthermore, authors investigate whether evaluative conditioning is resistant to extinction after a two-month period and whether the evaluative conditioning effect...... prevails in a product-related context. Within an evaluative conditioning paradigm including between-subjects control groups in addition to standard within-subjects control conditions, participants were presented with three food technologies (conventional, enzyme, and genetic technology) paired...

An effective approach for iris recognition using phase-based image matching.

Science.gov (United States)

Miyazawa, Kazuyuki; Ito, Koichi; Aoki, Takafumi; Kobayashi, Koji; Nakajima, Hiroshi

2008-10-01

This paper presents an efficient algorithm for iris recognition using phase-based image matching--an image matching technique using phase components in 2D Discrete Fourier Transforms (DFTs) of given images. Experimental evaluation using CASIA iris image databases (versions 1.0 and 2.0) and Iris Challenge Evaluation (ICE) 2005 database clearly demonstrates that the use of phase components of iris images makes possible to achieve highly accurate iris recognition with a simple matching algorithm. This paper also discusses major implementation issues of our algorithm. In order to reduce the size of iris data and to prevent the visibility of iris images, we introduce the idea of 2D Fourier Phase Code (FPC) for representing iris information. The 2D FPC is particularly useful for implementing compact iris recognition devices using state-of-the-art Digital Signal Processing (DSP) technology.

[Development of image quality assurance support system using image recognition technology in radiography in lacked images of chest and abdomen].

Science.gov (United States)

Shibuya, Toru; Kato, Kyouichi; Eshima, Hidekazu; Sumi, Shinichirou; Kubo, Tadashi; Ishida, Hideki; Nakazawa, Yasuo

2012-01-01

In order to provide a precise radiography for diagnosis, it is required that we avoid radiography with defects by having enough evaluation. Conventionally, evaluation was performed only by observation of a radiological technologist (RT). The evaluation support system was developed for providing a high quality assurance without depending on RT observation only. The evaluation support system, called as the Image Quality Assurance Support System (IQASS), is characterized in that "image recognition technology" for the purpose of diagnostic radiography of chest and abdomen areas. The technique of the system used in this study. Of the 259 samples of posterior-anterior (AP) chest, lateral chest, and upright abdominal x-rays, the sensitivity and specificity was 93.1% and 91.8% in the chest AP, 93.3% and 93.6% in the chest lateral, and 95.0% and 93.8% in the upright abdominal x-rays. In the light of these results, it is suggested that AIQAS could be applied to practical usage for the RT.

Speech Recognition on Mobile Devices

DEFF Research Database (Denmark)

Tan, Zheng-Hua; Lindberg, Børge

2010-01-01

in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within......The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...

Evaluating New Technology.

Science.gov (United States)

Carniol, Paul J; Heffelfinger, Ryan N; Grunebaum, Lisa D

2018-05-01

There are multiple complex issues to consider when evaluating any new technology. First evaluate the efficacy of the device. Then considering your patient population decide whether this technology brings an added benefit to your patients. If it meets these 2 criteria, then proceed to the financial analysis of acquiring this technology. The complete financial analysis has several important components that include but are not limited to cost, value, alternatives, return on investment, and associated marketing expense. Copyright © 2018 Elsevier Inc. All rights reserved.

Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons

Directory of Open Access Journals (Sweden)

Avgoustinos Filippoupolitis

2017-05-01

Full Text Available Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of body-worn sensors. As this approach suffers with respect to practicality, we propose the use of commercial off-the-shelf devices. In this work, we design and evaluate an activity recognition system composed of a smart watch, which is enhanced with location information coming from Bluetooth Low Energy (BLE beacons. We evaluate the performance of this approach for a variety of activities performed in an indoor laboratory environment, using four supervised machine learning algorithms. Our experimental results indicate that our location-enhanced activity recognition system is able to reach a classification accuracy ranging from 92% to 100%, while without location information classification accuracy it can drop to as low as 50% in some cases, depending on the window size chosen for data segmentation.

Interfacing COTS Speech Recognition and Synthesis Software to a Lotus Notes Military Command and Control Database

Science.gov (United States)

Carr, Oliver

2002-10-01

Speech recognition and synthesis technologies have become commercially viable over recent years. Two current market leading products in speech recognition technology are Dragon NaturallySpeaking and IBM ViaVoice. This report describes the development of speech user interfaces incorporating these products with Lotus Notes and Java applications. These interfaces enable data entry using speech recognition and allow warnings and instructions to be issued via speech synthesis. The development of a military vocabulary to improve user interaction is discussed. The report also describes an evaluation in terms of speed of the various speech user interfaces developed using Dragon NaturallySpeaking and IBM ViaVoice with a Lotus Notes Command and Control Support System Log database.

Soil washing technology evaluation

International Nuclear Information System (INIS)

Suer, A.

1995-04-01

Environmental Restoration Engineering (ERE) continues to review innovative, efficient, and cost effective technologies for SRS soil and/or groundwater remediation. As part of this effort, this technical evaluation provides review and the latest information on the technology for SRS soil remediation. Additional technology evaluation reports will be issued periodically to update these reports. The purpose of this report is to review the soil washing technology and its potential application to SRS soil remediation. To assess whether the Soil Washing technology is a viable option for SRS soil remediation, it is necessary to review the technology/process, technology advantages/limitations, performance, applications, and cost analysis

Implementation of a Tour Guide Robot System Using RFID Technology and Viterbi Algorithm-Based HMM for Speech Recognition

Directory of Open Access Journals (Sweden)

Neng-Sheng Pai

2014-01-01

Full Text Available This paper applied speech recognition and RFID technologies to develop an omni-directional mobile robot into a robot with voice control and guide introduction functions. For speech recognition, the speech signals were captured by short-time processing. The speaker first recorded the isolated words for the robot to create speech database of specific speakers. After the speech pre-processing of this speech database, the feature parameters of cepstrum and delta-cepstrum were obtained using linear predictive coefficient (LPC. Then, the Hidden Markov Model (HMM was used for model training of the speech database, and the Viterbi algorithm was used to find an optimal state sequence as the reference sample for speech recognition. The trained reference model was put into the industrial computer on the robot platform, and the user entered the isolated words to be tested. After processing by the same reference model and comparing with previous reference model, the path of the maximum total probability in various models found using the Viterbi algorithm in the recognition was the recognition result. Finally, the speech recognition and RFID systems were achieved in an actual environment to prove its feasibility and stability, and implemented into the omni-directional mobile robot.

Face Recognition in Humans and Machines

Science.gov (United States)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

Evaluating Technology Transfer and Diffusion.

Science.gov (United States)

Bozeman, Barry; And Others

1988-01-01

Four articles discuss the evaluation of technology transfer and diffusion: (1) "Technology Transfer at the U.S. National Laboratories: A Framework for Evaluation"; (2) "Application of Social Psychological and Evaluation Research: Lessons from Energy Information Programs"; (3) "Technology and Knowledge Transfer in Energy R and D Laboratories: An…

Non Audio-Video gesture recognition system

DEFF Research Database (Denmark)

Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis

2016-01-01

Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device...

Study on municipal road cracking and surface deformation based on image recognition

Science.gov (United States)

Yuan, Haitao; Wang, Shuai; Tan, Jizong

2017-05-01

In recent years, the digital image recognition technology of concrete structure cracks and deformation of binocular vision technology detection of civil engineering structure have made substantial development. As a result, people's understanding of the road engineering structure cracking and surface deformation recognition gives rise to a new situation. For the research on digital image concrete structure cracking and masonry structure surface deformation recognition technology, the key is to break through in the method, and to improve the traditional recognition technology and mode. Only in this way can we continuously improve the security level of the highway, to adapt to the new requirements of the development of new urbanization and modernization. This thesis focuses on and systematically analyzes the digital image road engineering structure cracking and key technologies of surface deformation recognition and its engineering applications. In addition, we change the concrete structure cracking and masonry structure surface deformation recognition pattern, and realize the breakthrough and innovation of the road structure safety testing means and methods.

76 FR 30696 - Technology Evaluation Process

Science.gov (United States)

2011-05-26

...-NOA-0039] Technology Evaluation Process AGENCY: Office of Energy Efficiency and Renewable Energy... (DOE) seeks comments and information related to a commercial buildings technology evaluation process... evaluation efforts. The goal of creating this standard process is to evaluate energy-saving technologies in a...

Robust and Effective Component-based Banknote Recognition by SURF Features.

Science.gov (United States)

Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, YingLi

2011-01-01

Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work for restricted conditions. In this paper we propose a component-based framework for banknote recognition by using Speeded Up Robust Features (SURF). The component-based framework is effective in collecting more class-specific information and robust in dealing with partial occlusion and viewpoint changes. Furthermore, the evaluation of SURF demonstrates its effectiveness in handling background noise, image rotation, scale, and illumination changes. To authenticate the robustness and generalizability of the proposed approach, we have collected a large dataset of banknotes from a variety of conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves 100% recognition rate on our challenging dataset.

Robust and Effective Component-based Banknote Recognition for the Blind.

Science.gov (United States)

Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, Yingli

2012-11-01

We develop a novel camera-based computer vision technology to automatically recognize banknotes for assisting visually impaired people. Our banknote recognition system is robust and effective with the following features: 1) high accuracy: high true recognition rate and low false recognition rate, 2) robustness: handles a variety of currency designs and bills in various conditions, 3) high efficiency: recognizes banknotes quickly, and 4) ease of use: helps blind users to aim the target for image capture. To make the system robust to a variety of conditions including occlusion, rotation, scaling, cluttered background, illumination change, viewpoint variation, and worn or wrinkled bills, we propose a component-based framework by using Speeded Up Robust Features (SURF). Furthermore, we employ the spatial relationship of matched SURF features to detect if there is a bill in the camera view. This process largely alleviates false recognition and can guide the user to correctly aim at the bill to be recognized. The robustness and generalizability of the proposed system is evaluated on a dataset including both positive images (with U.S. banknotes) and negative images (no U.S. banknotes) collected under a variety of conditions. The proposed algorithm, achieves 100% true recognition rate and 0% false recognition rate. Our banknote recognition system is also tested by blind users.

Speech Recognition Technology for Disabilities Education

Science.gov (United States)

Tang, K. Wendy; Kamoua, Ridha; Sutan, Victor; Farooq, Omer; Eng, Gilbert; Chu, Wei Chern; Hou, Guofeng

2005-01-01

Speech recognition is an alternative to traditional methods of interacting with a computer, such as textual input through a keyboard. An effective system can replace or reduce the reliability on standard keyboard and mouse input. This can especially assist dyslexic students who have problems with character or word use and manipulation in a textual…

A novel dataset for real-life evaluation of facial expression recognition methodologies

NARCIS (Netherlands)

Siddiqi, Muhammad Hameed; Ali, Maqbool; Idris, Muhammad; Banos Legran, Oresti; Lee, Sungyoung; Choo, Hyunseung

2016-01-01

One limitation seen among most of the previous methods is that they were evaluated under settings that are far from real-life scenarios. The reason is that the existing facial expression recognition (FER) datasets are mostly pose-based and assume a predefined setup. The expressions in these datasets

Novel approaches to improve iris recognition system performance based on local quality evaluation and feature fusion.

Science.gov (United States)

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; Chen, Huiling; He, Fei; Pang, Yutong

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

Speaker Recognition

DEFF Research Database (Denmark)

Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther

2005-01-01

Speaker recognition is basically divided into speaker identification and speaker verification. Verification is the task of automatically determining if a person really is the person he or she claims to be. This technology can be used as a biometric feature for verifying the identity of a person...

A Review on Video-Based Human Activity Recognition

Directory of Open Access Journals (Sweden)

Shian-Ru Ke

2013-06-01

Full Text Available This review article surveys extensively the current progresses made toward video-based human activity recognition. Three aspects for human activity recognition are addressed including core technology, human activity recognition systems, and applications from low-level to high-level representation. In the core technology, three critical processing stages are thoroughly discussed mainly: human object segmentation, feature extraction and representation, activity detection and classification algorithms. In the human activity recognition systems, three main types are mentioned, including single person activity recognition, multiple people interaction and crowd behavior, and abnormal activity recognition. Finally the domains of applications are discussed in detail, specifically, on surveillance environments, entertainment environments and healthcare systems. Our survey, which aims to provide a comprehensive state-of-the-art review of the field, also addresses several challenges associated with these systems and applications. Moreover, in this survey, various applications are discussed in great detail, specifically, a survey on the applications in healthcare monitoring systems.

76 FR 37344 - Technology Evaluation Process

Science.gov (United States)

2011-06-27

...-NOA-0039] Technology Evaluation Process AGENCY: Office of Energy Efficiency and Renewable Energy... seeks comments and information related to a commercial buildings technology evaluation process. DOE is seeking to create a process for evaluating emerging and underutilized energy efficient technologies for...

License plate recognition (phase B).

Science.gov (United States)

2010-06-01

License Plate Recognition (LPR) technology has been used for off-line automobile enforcement purposes. The technology has seen mixed success with correct reading rate as high as 60 to 80% depending on the specific application and environment. This li...

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

Science.gov (United States)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network

Directory of Open Access Journals (Sweden)

Fatchul Arifin

2010-08-01

Full Text Available The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.

The nuclear fuel rod character recognition system based on neural network technique

International Nuclear Information System (INIS)

Kim, Woong-Ki; Park, Soon-Yong; Lee, Yong-Bum; Kim, Seung-Ho; Lee, Jong-Min; Chien, Sung-Il.

1994-01-01

The nuclear fuel rods should be discriminated and managed systematically by numeric characters which are printed at the end part of each rod in the process of producing fuel assembly. The characters are used to examine manufacturing process of the fuel rods in the inspection process of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies to establish automatic manufacturing process of fuel assembly. In the developed character recognition system, mesh feature set extracted from each character written in the fuel rod is employed to train a neural network based on back-propagation algorithm as a classifier for character recognition system. Performance evaluation has been achieved on a test set which is not included in a training character set. (author)

Facial recognition in education system

Science.gov (United States)

Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

2017-11-01

Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

Man-system interface based on automatic speech recognition: integration to a virtual control desk

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b, E-mail: cmnap@ien.gov.b, E-mail: mag@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Nomiya, Diogo V., E-mail: diogonomiya@gmail.co [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

2009-07-01

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

Man-system interface based on automatic speech recognition: integration to a virtual control desk

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C.; Nomiya, Diogo V.

2009-01-01

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

A Training Technology Evaluation Tool

National Research Council Canada - National Science Library

Livingston, Stephen C; Dyer, Jean L; Swinson, Diadra

2005-01-01

A Training Technology Evaluation Tool was developed to help procurers and developers of training technologies to make informed decisions and to improve the overall effectiveness of training technologies...

Cost-Sensitive Learning for Emotion Robust Speaker Recognition

Directory of Open Access Journals (Sweden)

Dongdong Li

2014-01-01

Full Text Available In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

Cost-sensitive learning for emotion robust speaker recognition.

Science.gov (United States)

Li, Dongdong; Yang, Yingchun; Dai, Weihui

2014-01-01

In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Directory of Open Access Journals (Sweden)

Tobias Nef

2015-05-01

Full Text Available Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB, support vector machine (SVM and random forest (RF. Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data.

Science.gov (United States)

Nef, Tobias; Urwyler, Prabitha; Büchler, Marcel; Tarnanas, Ioannis; Stucki, Reto; Cazzoli, Dario; Müri, René; Mosimann, Urs

2015-05-21

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our

Face Recognition and Tracking in Videos

Directory of Open Access Journals (Sweden)

Swapnil Vitthal Tathe

2017-07-01

Full Text Available Advancement in computer vision technology and availability of video capturing devices such as surveillance cameras has evoked new video processing applications. The research in video face recognition is mostly biased towards law enforcement applications. Applications involves human recognition based on face and iris, human computer interaction, behavior analysis, video surveillance etc. This paper presents face tracking framework that is capable of face detection using Haar features, recognition using Gabor feature extraction, matching using correlation score and tracking using Kalman filter. The method has good recognition rate for real-life videos and robust performance to changes due to illumination, environmental factors, scale, pose and orientations.

Threats of Password Pattern Leakage Using Smartwatch Motion Recognition Sensors

Directory of Open Access Journals (Sweden)

Jihun Kim

2017-06-01

Full Text Available Thanks to the development of Internet of Things (IoT technologies, wearable markets have been growing rapidly. Smartwatches can be said to be the most representative product in wearable markets, and involve various hardware technologies in order to overcome the limitations of small hardware. Motion recognition sensors are a representative example of those hardware technologies. However, smartwatches and motion recognition sensors that can be worn by users may pose security threats of password pattern leakage. In the present paper, passwords are inferred through experiments to obtain password patterns inputted by users using motion recognition sensors, and verification of the results and the accuracy of the results is shown.

Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

Science.gov (United States)

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Using speech recognition to enhance the Tongue Drive System functionality in computer access.

Science.gov (United States)

Huo, Xueliang; Ghovanloo, Maysam

2011-01-01

Tongue Drive System (TDS) is a wireless tongue operated assistive technology (AT), which can enable people with severe physical disabilities to access computers and drive powered wheelchairs using their volitional tongue movements. TDS offers six discrete commands, simultaneously available to the users, for pointing and typing as a substitute for mouse and keyboard in computer access, respectively. To enhance the TDS performance in typing, we have added a microphone, an audio codec, and a wireless audio link to its readily available 3-axial magnetic sensor array, and combined it with a commercially available speech recognition software, the Dragon Naturally Speaking, which is regarded as one of the most efficient ways for text entry. Our preliminary evaluations indicate that the combined TDS and speech recognition technologies can provide end users with significantly higher performance than using each technology alone, particularly in completing tasks that require both pointing and text entry, such as web surfing.

Recognition of familiar people with a mobile cloud architecture for Alzheimer patients.

Science.gov (United States)

Fardoun, Habib M; Mashat, Abdullah A; Ramirez Castillo, Jaime

2017-02-01

This article aims to the evaluation of a prototypal assistive technology for Alzheimer's disease (AD) patients that helps them to remember personal details of familiar people they meet in their daily lives. An architecture is proposed for a personal information system powered by face recognition, where the main AD patient's interaction is performed in a smart watch device and the face recognition is carried out on the Cloud. A prototype was developed to perform some tests in a real-life scenario. The prototype showed correct results as a personal information system based on face recognition. However, usability flaws were identified in the interaction with the smart watch. Our architecture showed correct performance and we realized that it could be introduced in other fields, apart from assistive technology. However, when being targeted to patients with dementia some usability problems appeared, such as difficulties to read information in a small screen or take a proper photo. These problems should be addressed in further research. Implications for Rehabilitation This article presents a prototypal assistive technology for Alzheimer's disease (AD) patients. It targets AD patients to recognize their familiars, especially in medium-advanced stages of the disease. Analysing pictures taken by a smart watch, which the patient carries, the person in front is recognized and information about him is sent to the watch. This technology enables patients to have all the information of any close person, as a remainder, easing their daily lives, improving their self-esteem and stimulating the patient with novel technology.

Preliminary Analysis of Automatic Speech Recognition and Synthesis Technology.

Science.gov (United States)

1983-05-01

ANDELES CA 0 SHDAP ET AL MAY 93 UNCISSIFED UCG -020-8 MDA04-8’-C-415F/ 17/2 N mE = h IEEE 11111 10’ ~ 2.0 11-41 & 11111I25IID MICROCOPY RESOLUTION TEST...speech. Private industry, which sees a major market for improved speech recognition systems, is attempting to solve the problems involved in...manufacturer is able to market such a recognition system. A second requirement for the spotting of keywords in distress signals concerns the need for a

Three-dimensional fingerprint recognition by using convolution neural network

Science.gov (United States)

Tian, Qianyu; Gao, Nan; Zhang, Zonghua

2018-01-01

With the development of science and technology and the improvement of social information, fingerprint recognition technology has become a hot research direction and been widely applied in many actual fields because of its feasibility and reliability. The traditional two-dimensional (2D) fingerprint recognition method relies on matching feature points. This method is not only time-consuming, but also lost three-dimensional (3D) information of fingerprint, with the fingerprint rotation, scaling, damage and other issues, a serious decline in robustness. To solve these problems, 3D fingerprint has been used to recognize human being. Because it is a new research field, there are still lots of challenging problems in 3D fingerprint recognition. This paper presents a new 3D fingerprint recognition method by using a convolution neural network (CNN). By combining 2D fingerprint and fingerprint depth map into CNN, and then through another CNN feature fusion, the characteristics of the fusion complete 3D fingerprint recognition after classification. This method not only can preserve 3D information of fingerprints, but also solves the problem of CNN input. Moreover, the recognition process is simpler than traditional feature point matching algorithm. 3D fingerprint recognition rate by using CNN is compared with other fingerprint recognition algorithms. The experimental results show that the proposed 3D fingerprint recognition method has good recognition rate and robustness.

Evaluating deep learning architectures for Speech Emotion Recognition.

Science.gov (United States)

Fayek, Haytham M; Lech, Margaret; Cavedon, Lawrence

2017-08-01

Speech Emotion Recognition (SER) can be regarded as a static or dynamic classification problem, which makes SER an excellent test bed for investigating and comparing various deep learning architectures. We describe a frame-based formulation to SER that relies on minimal speech processing and end-to-end deep learning to model intra-utterance dynamics. We use the proposed SER system to empirically explore feed-forward and recurrent neural network architectures and their variants. Experiments conducted illuminate the advantages and limitations of these architectures in paralinguistic speech recognition and emotion recognition in particular. As a result of our exploration, we report state-of-the-art results on the IEMOCAP database for speaker-independent SER and present quantitative and qualitative assessments of the models' performances. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intangible Wealth, between Recognition and Evaluation

Directory of Open Access Journals (Sweden)

Florentina Moisescu

2016-07-01

Full Text Available The theme of this work is the recognition, assessment and importance of intangible property in the financial statements of an enterprise. The paper presents an insight into intangible assets recognition of causality, with highlight relevant aspects of how education contribute in a decisive manner, through the generation and dissemination of knowledge in order to achieve specific strategic goals of economic policy. This issue has also been a challenge and it still represents one for companies that have intangible assets overstated or that have kept in their balance sheet intangible assets without aproperly assessed market value. The paper also addresses the issue by restricting the proposed theoretical aspects in favor of those which are directly related to the accounting practice in line with International Accounting Standards and with the accounting regulations of our country.

Iris recognition in the presence of ocular disease.

Science.gov (United States)

Aslam, Tariq Mehmood; Tan, Shi Zhuan; Dhillon, Baljean

2009-05-06

Iris recognition systems are among the most accurate of all biometric technologies with immense potential for use in worldwide security applications. This study examined the effect of eye pathology on iris recognition and in particular whether eye disease could cause iris recognition systems to fail. The experiment involved a prospective cohort of 54 patients with anterior segment eye disease who were seen at the acute referral unit of the Princess Alexandra Eye Pavilion in Edinburgh. Iris camera images were obtained from patients before treatment was commenced and again at follow-up appointments after treatment had been given. The principal outcome measure was that of mathematical difference in the iris recognition templates obtained from patients' eyes before and after treatment of the eye disease. Results showed that the performance of iris recognition was remarkably resilient to most ophthalmic disease states, including corneal oedema, iridotomies (laser puncture of iris) and conjunctivitis. Problems were, however, encountered in some patients with acute inflammation of the iris (iritis/anterior uveitis). The effects of a subject developing anterior uveitis may cause current recognition systems to fail. Those developing and deploying iris recognition should be aware of the potential problems that this could cause to this key biometric technology.

Evaluating Internal Technological Capabilities in Energy Companies

Directory of Open Access Journals (Sweden)

Mingook Lee

2016-03-01

Full Text Available As global competition increases, technological capability must be evaluated objectively as one of the most important factors for predominance in technological competition and to ensure sustainable business excellence. Most existing capability evaluation models utilize either quantitative methods, such as patent analysis, or qualitative methods, such as expert panels. Accordingly, they may be in danger of reflecting only fragmentary aspects of technological capabilities, and produce inconsistent results when different models are used. To solve these problems, this paper proposes a comprehensive framework for evaluating technological capabilities in energy companies by considering the complex properties of technological knowledge. For this purpose, we first explored various factors affecting technological capabilities and divided the factors into three categories: individual, organizational, and technology competitiveness. Second, we identified appropriate evaluation items for each category to measure the technological capability. Finally, by using a hybrid approach of qualitative and quantitative methods, we developed an evaluation method for each item and suggested a method to combine the results. The proposed framework was then verified with an energy generation and supply company to investigate its practicality. As one of the earliest attempts to evaluate multi-faceted technological capabilities, the suggested model can support technology and strategic planning.

Movement recognition technology as a method of assessing spontaneous general movements in high risk infants

Directory of Open Access Journals (Sweden)

Claire eMarcroft

2015-01-01

Full Text Available Preterm birth is associated with increased risks of neurological and motor impairments such as cerebral palsy. The risks are highest in those born at the lowest gestations. Early identification of those most at risk is challenging meaning that a critical window of opportunity to improve outcomes through therapy-based interventions may be missed. Clinically, the assessment of spontaneous general movements is an important tool which can be used for the prediction of movement impairments in high risk infants.Movement recognition aims to capture and analyze relevant limb movements through computerized approaches focusing on continuous, objective, and quantitative assessment. Different methods of recording and analyzing infant movements have recently been explored in high risk infants. These range from camera-based solutions to body-worn miniaturized movement sensors used to record continuous time-series data that represent the dynamics of limb movements. Various machine learning methods have been developed and applied to the analysis of the recorded movement data. This analysis has focused on the detection and classification of atypical spontaneous general movements. This paper aims to identify recent translational studies using movement recognition technology as a method of assessing movement in high risk infants. The application of this technology within pediatric practice represents a growing area of inter-disciplinary collaboration which may lead to a greater understanding of the development of the nervous system in infants at high risk of motor impairment.

Literature review of voice recognition and generation technology for Army helicopter applications

Science.gov (United States)

Christ, K. A.

1984-08-01

This report is a literature review on the topics of voice recognition and generation. Areas covered are: manual versus vocal data input, vocabulary, stress and workload, noise, protective masks, feedback, and voice warning systems. Results of the studies presented in this report indicate that voice data entry has less of an impact on a pilot's flight performance, during low-level flying and other difficult missions, than manual data entry. However, the stress resulting from such missions may cause the pilot's voice to change, reducing the recognition accuracy of the system. The noise present in helicopter cockpits also causes the recognition accuracy to decrease. Noise-cancelling devices are being developed and improved upon to increase the recognition performance in noisy environments. Future research in the fields of voice recognition and generation should be conducted in the areas of stress and workload, vocabulary, and the types of voice generation best suited for the helicopter cockpit. Also, specific tasks should be studied to determine whether voice recognition and generation can be effectively applied.

Evaluation of a smartphone human activity recognition application with able-bodied and stroke participants.

Science.gov (United States)

Capela, N A; Lemaire, E D; Baddour, N; Rudolf, M; Goljar, N; Burger, H

2016-01-20

Mobile health monitoring using wearable sensors is a growing area of interest. As the world's population ages and locomotor capabilities decrease, the ability to report on a person's mobility activities outside a hospital setting becomes a valuable tool for clinical decision-making and evaluating healthcare interventions. Smartphones are omnipresent in society and offer convenient and suitable sensors for mobility monitoring applications. To enhance our understanding of human activity recognition (HAR) system performance for able-bodied and populations with gait deviations, this research evaluated a custom smartphone-based HAR classifier on fifteen able-bodied participants and fifteen participants who suffered a stroke. Participants performed a consecutive series of mobility tasks and daily living activities while wearing a BlackBerry Z10 smartphone on their waist to collect accelerometer and gyroscope data. Five features were derived from the sensor data and used to classify participant activities (decision tree). Sensitivity, specificity and F-scores were calculated to evaluate HAR classifier performance. The classifier performed well for both populations when differentiating mobile from immobile states (F-score > 94 %). As activity recognition complexity increased, HAR system sensitivity and specificity decreased for the stroke population, particularly when using information derived from participant posture to make classification decisions. Human activity recognition using a smartphone based system can be accomplished for both able-bodied and stroke populations; however, an increase in activity classification complexity leads to a decrease in HAR performance with a stroke population. The study results can be used to guide smartphone HAR system development for populations with differing movement characteristics.

Pelvic insufficiency fractures associated with radiation atrophy: clinical recognition and diagnostic evaluation

International Nuclear Information System (INIS)

Mumber, M.P.; Greven, K.M.; Haygood, T.M.

1997-01-01

Pelvic bone injuries are infrequent complications of radiotherapy. However, insufficiency fractures in irradiated pelvic bones may be underdetected, particularly in postmenopausal women. We describe the clinical presentation, radiologic evaluation, and course of disease in three patients with postradiation pelvic insufficiency fractures. Differential diagnosis included metastatic disease, tumor recurrence, and second malignancy. Recognition of radiographic features may prevent unnecessary, possibly morbid treatments. (orig.). With 6 figs

On-device mobile speech recognition

OpenAIRE

Mustafa, MK

2016-01-01

Despite many years of research, Speech Recognition remains an active area of research in Artificial Intelligence. Currently, the most common commercial application of this technology on mobile devices uses a wireless client – server approach to meet the computational and memory demands of the speech recognition process. Unfortunately, such an approach is unlikely to remain viable when fully applied over the approximately 7.22 Billion mobile phones currently in circulation. In this thesis we p...

An Evaluation of PC-Based Optical Character Recognition Systems.

Science.gov (United States)

Schreier, E. M.; Uslan, M. M.

1991-01-01

The review examines six personal computer-based optical character recognition (OCR) systems designed for use by blind and visually impaired people. Considered are OCR components and terms, documentation, scanning and reading, command structure, conversion, unique features, accuracy of recognition, scanning time, speed, and cost. (DB)

National Security Technology Incubator Evaluation Process

Energy Technology Data Exchange (ETDEWEB)

None, None

2007-12-31

This report describes the process by which the National Security Technology Incubator (NSTI) will be evaluated. The technology incubator is being developed as part of the National Security Preparedness Project (NSPP), funded by a Department of Energy (DOE)/National Nuclear Security Administration (NNSA) grant. This report includes a brief description of the components, steps, and measures of the proposed evaluation process. The purpose of the NSPP is to promote national security technologies through business incubation, technology demonstration and validation, and workforce development. The NSTI will focus on serving businesses with national security technology applications by nurturing them through critical stages of early development. An effective evaluation process of the NSTI is an important step as it can provide qualitative and quantitative information on incubator performance over a given period. The vision of the NSTI is to be a successful incubator of technologies and private enterprise that assist the NNSA in meeting new challenges in national safety and security. The mission of the NSTI is to identify, incubate, and accelerate technologies with national security applications at various stages of development by providing hands-on mentoring and business assistance to small businesses and emerging or growing companies. To achieve success for both incubator businesses and the NSTI program, an evaluation process is essential to effectively measure results and implement corrective processes in the incubation design if needed. The evaluation process design will collect and analyze qualitative and quantitative data through performance evaluation system.

Evaluation of iris recognition system for wavefront-guided laser in situ keratomileusis for myopic astigmatism.

Science.gov (United States)

Ghosh, Sudipta; Couper, Terry A; Lamoureux, Ecosse; Jhanji, Vishal; Taylor, Hugh R; Vajpayee, Rasik B

2008-02-01

To evaluate the visual and refractive outcomes of wavefront-guided laser in situ keratomileusis (LASIK) using an iris recognition system for the correction of myopic astigmatism. Centre for Eye Research Australia, Melbourne Excimer Laser Research Group, and Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia. A comparative analysis of wavefront-guided LASIK was performed with an iris recognition system (iris recognition group) and without iris recognition (control group). The main parameters were uncorrected visual acuity (UCVA), best spectacle-corrected visual acuity, amount of residual cylinder, manifest spherical equivalent (SE), and the index of success using the Alpins method of astigmatism analysis 1 and 3 months postoperatively. A P value less than 0.05 was considered statistically significant. Preoperatively, the mean SE was -4.32 diopters (D) +/- 1.59 (SD) in the iris recognition group (100 eyes) and -4.55 +/- 1.87 D in the control group (98 eyes) (P = .84). At 3 months, the mean SE was -0.05 +/- 0.21 D and -0.20 +/- 0.40 D, respectively (P = .001), and an SE within +/-0.50 D of emmetropia was achieved in 92.0% and 85.7% of eyes, respectively (P = .07). At 3 months, the UCVA was 20/20 or better in 90.0% and 76.5% of eyes, respectively. A statistically significant difference in the amount of astigmatic correction was seen between the 2 groups (P = .00 and P = .01 at 1 and 3 months, respectively). The index of success was 98.0% in the iris recognition group and 81.6% in the control group (P = .03). Iris recognition software may achieve better visual and refractive outcomes in wavefront-guided LASIK for myopic astigmatism.

Rapid determination of 239Pu in urine samples using molecular recognition technology product AnaLigRPu-02 gel

International Nuclear Information System (INIS)

Silvia Dulanska; Boris Remenec; Jan Bilohuscin; Miroslav Labaska; Bianka Horvathova; Andrej Matel

2013-01-01

This paper describes the use of IBC's AnaLig R Pu-02 molecular recognition technology product to effectively and selectively pre-concentrate, separate and recover plutonium from urine samples. This method uses two-stage column separations consisting of two different commercial products, Eichrom's Pre-filter Material and AnaLig R Pu-02 resin from IBC Advanced Technologies. By eliminating the co-precipitation techniques and the ashing steps to remove residual organics, the analysis time was reduced significantly. The method was successfully tested by adding known activities of reference solutions of 242 Pu and 239 Pu to urine samples. (author)

Digital Technologies for Social Innovation: An Empirical Recognition on the New Enablers

Directory of Open Access Journals (Sweden)

Riccardo Maiolini

2016-12-01

Full Text Available Even though scholars’ attention has been placed on Social Innovation (SI, little evidence has been provided with regards to which tools are actually used to address social needs and foster Social Innovation initiatives. The purpose of the article is twofold. Firstly, the article offers empirical recognition to SI by investigating, on a large-scale, social and innovative activities conducted by start-ups and small and medium-sized enterprises (SMEs across the world between 2001 and 2014. Secondly, the article intends to capture SI core businesses and underlying complementarities between products, markets, and technologies and show in which way digital media and IT are essentially tracing innovation trajectories over a multitude of industries, leading the current industrial patterns of SI, and continually fostering its cross-industry nature.

A real time mobile-based face recognition with fisherface methods

Science.gov (United States)

Arisandi, D.; Syahputra, M. F.; Putri, I. L.; Purnamawati, S.; Rahmat, R. F.; Sari, P. P.

2018-03-01

Face Recognition is a field research in Computer Vision that study about learning face and determine the identity of the face from a picture sent to the system. By utilizing this face recognition technology, learning process about people’s identity between students in a university will become simpler. With this technology, student won’t need to browse student directory in university’s server site and look for the person with certain face trait. To obtain this goal, face recognition application use image processing methods consist of two phase, pre-processing phase and recognition phase. In pre-processing phase, system will process input image into the best image for recognition phase. Purpose of this pre-processing phase is to reduce noise and increase signal in image. Next, to recognize face phase, we use Fisherface Methods. This methods is chosen because of its advantage that would help system of its limited data. Therefore from experiment the accuracy of face recognition using fisherface is 90%.

Memory evaluation in mild cognitive impairment using recall and recognition tests.

Science.gov (United States)

Bennett, Ilana J; Golob, Edward J; Parker, Elizabeth S; Starr, Arnold

2006-11-01

Amnestic mild cognitive impairment (MCI) is a selective episodic memory deficit that often indicates early Alzheimer's disease. Episodic memory function in MCI is typically defined by deficits in free recall, but can also be tested using recognition procedures. To assess both recall and recognition in MCI, MCI (n = 21) and older comparison (n = 30) groups completed the USC-Repeatable Episodic Memory Test. Subjects memorized two verbally presented 15-item lists. One list was used for three free recall trials, immediately followed by yes/no recognition. The second list was used for three-alternative forced-choice recognition. Relative to the comparison group, MCI had significantly fewer hits and more false alarms in yes/no recognition, and were less accurate in forced-choice recognition. Signal detection analysis showed that group differences were not due to response bias. Discriminant function analysis showed that yes/no recognition was a better predictor of group membership than free recall or forced-choice measures. MCI subjects recalled fewer items than comparison subjects, with no group differences in repetitions, intrusions, serial position effects, or measures of recall strategy (subjective organization, recall consistency). Performance deficits on free recall and recognition in MCI suggest a combination of both tests may be useful for defining episodic memory impairment associated with MCI and early Alzheimer's disease.

Object and event recognition for stroke rehabilitation

Science.gov (United States)

Ghali, Ahmed; Cunningham, Andrew S.; Pridmore, Tony P.

2003-06-01

Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient"s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient"s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.

Recognition

DEFF Research Database (Denmark)

Gimmler, Antje

2017-01-01

In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory mus...

Automatic Speech Recognition Systems for the Evaluation of Voice and Speech Disorders in Head and Neck Cancer

OpenAIRE

Andreas Maier; Tino Haderlein; Florian Stelzle; Elmar Nöth; Emeka Nkenke; Frank Rosanowski; Anne Schützenberger; Maria Schuster

2010-01-01

In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of intelligibility. In this study we investigate the applicability of the method to speech disorders caused by head and neck cancer. Intelligibility was quantified by speech recognition on recordings of a standard text read by 41 German laryngect...

[Respiratory handicap. Recognition, evaluation and social benefits].

Science.gov (United States)

Marsac, J; Pujet, J C

1983-01-01

The medico-social aspects of respiratory handicap pose some perplexing problems, notably in their recognition, rigorous evaluation and in the granting of social security benefits. The clinical and respiratory function data should be standardised and classified according to type and significance of respiratory disease and also according to the degree of co-operation and understanding of the patient. The respiratory handicap should be evaluated after considering the functional disability engendered by the disorder and their socio-professional repercussions. The abnormality in the lungs should be measured by resting tests; the degree of disability by exercise studies; the socio-professional handicap by ergonometric tests to assess the scale of the demands and requirements of family and social and professional life, indeed the cultural and economic style of the individual concerned. Such combined studies would enable recognition of severe chronic respiratory handicap leading to decisions for exemption certificates, such as cases of severe respiratory failure in patients requiring supplementary treatment for oxygen therapy or assisted ventilation. The benefits and grants offered to those with respiratory handicaps would involve a number of rights relating to: care, work, costs of replacement of workers in the event of prolonged sick leave or the benefits of an invalidity pension. There will be other allowances such as invalidity cards, lodging special studies and other rights particularly relating to lodging and special equipment. The present scale is difficult to use both because of its lack of specificity and its ill-chosen terminology. For better balance between the handicap and the benefits offered, a common and more flexible system, with a printed table should be at hand for the doctor to use for certain decisions: long term illness, period of invalidity or early retirement because of medical incapacity. Within each table a sub-section should exist to allow for

Facial Recognition in Uncontrolled Conditions for Information Security

Directory of Open Access Journals (Sweden)

Qinghan Xiao

2010-01-01

Full Text Available With the increasing use of computers nowadays, information security is becoming an important issue for private companies and government organizations. Various security technologies have been developed, such as authentication, authorization, and auditing. However, once a user logs on, it is assumed that the system would be controlled by the same person. To address this flaw, we developed a demonstration system that uses facial recognition technology to periodically verify the identity of the user. If the authenticated user's face disappears, the system automatically performs a log-off or screen-lock operation. This paper presents our further efforts in developing image preprocessing algorithms and dealing with angled facial images. The objective is to improve the accuracy of facial recognition under uncontrolled conditions. To compare the results with others, the frontal pose subset of the Face Recognition Technology (FERET database was used for the test. The experiments showed that the proposed algorithms provided promising results.

Facial Recognition in Uncontrolled Conditions for Information Security

Science.gov (United States)

Xiao, Qinghan; Yang, Xue-Dong

2010-12-01

With the increasing use of computers nowadays, information security is becoming an important issue for private companies and government organizations. Various security technologies have been developed, such as authentication, authorization, and auditing. However, once a user logs on, it is assumed that the system would be controlled by the same person. To address this flaw, we developed a demonstration system that uses facial recognition technology to periodically verify the identity of the user. If the authenticated user's face disappears, the system automatically performs a log-off or screen-lock operation. This paper presents our further efforts in developing image preprocessing algorithms and dealing with angled facial images. The objective is to improve the accuracy of facial recognition under uncontrolled conditions. To compare the results with others, the frontal pose subset of the Face Recognition Technology (FERET) database was used for the test. The experiments showed that the proposed algorithms provided promising results.

Evaluation of the cleaner technology programme

DEFF Research Database (Denmark)

Andersen, Mikael Skou; Jørgensen, Ulrik

The report presents an independent evaluation of the Danish development programme for cleaner technology 1986-1989 and of the Action Plan for Cleaner Technology 1990-1992. The evaluation focuses on the results of technology development and implementation projects, on an examination...... of the dissemination of cleaner technology solutions achieved in six industrial branches, and on the overall programme and its effects, in particular environmental impacts, but also results in the form of employment, environmental export, strenghtening of Danish know-how etc....

FaceIt: face recognition from static and live video for law enforcement

Science.gov (United States)

Atick, Joseph J.; Griffin, Paul M.; Redlich, A. N.

1997-01-01

Recent advances in image and pattern recognition technology- -especially face recognition--are leading to the development of a new generation of information systems of great value to the law enforcement community. With these systems it is now possible to pool and manage vast amounts of biometric intelligence such as face and finger print records and conduct computerized searches on them. We review one of the enabling technologies underlying these systems: the FaceIt face recognition engine; and discuss three applications that illustrate its benefits as a problem-solving technology and an efficient and cost effective investigative tool.

An Evaluation of Project iRead: A Program Created to Improve Sight Word Recognition

Science.gov (United States)

Marshall, Theresa Meade

2014-01-01

This program evaluation was undertaken to examine the relationship between participation in Project iRead and student gains in word recognition, fluency, and comprehension as measured by the Phonological Awareness Literacy Screening (PALS) Test. Linear regressions compared the 2012-13 PALS results from 5,140 first and second grade students at…

Survey Analysis on Nuclear Security Culture Recognition of Nuclear Facility in 2014

International Nuclear Information System (INIS)

Hong, Yunjeong; Lee, Jeongho; Kim, Jaekwang

2015-01-01

All organizations involved in implementing physical protection should give due priority to the security culture, to its development and maintenance necessary to ensure its effective implementation in the entire organization. In this context, Korea Institute of Non-proliferation and Control(KINAC) confirms recognition about protection of people who work in nuclear field and developed questionnaire for utilizing fundamental data for nuclear security culture enhancement activity and conducted a survey. As a result, systematic education needs to employees. Choosing differentiated topic is required to consider employees because recognition level of age, position and division is different. And a variety of education technology as obligatory education such as filling the course time or the one-off thing has limitation. And taking complementary measures needs since there were many opinions that employees feel difficult to understand papers such as regulation and guidelines and so on related security. Finally, we hope to make fundament available to evaluate nuclear security culture recognition level based on the existing questionnaire would be changed to realistic and enhancement in recognition survey for future nuclear security culture

Survey Analysis on Nuclear Security Culture Recognition of Nuclear Facility in 2014

Energy Technology Data Exchange (ETDEWEB)

Hong, Yunjeong; Lee, Jeongho; Kim, Jaekwang [Korea Institute of Nonproliferation and Control International Nuclear Security Academy, Daejeon (Korea, Republic of)

2015-05-15

All organizations involved in implementing physical protection should give due priority to the security culture, to its development and maintenance necessary to ensure its effective implementation in the entire organization. In this context, Korea Institute of Non-proliferation and Control(KINAC) confirms recognition about protection of people who work in nuclear field and developed questionnaire for utilizing fundamental data for nuclear security culture enhancement activity and conducted a survey. As a result, systematic education needs to employees. Choosing differentiated topic is required to consider employees because recognition level of age, position and division is different. And a variety of education technology as obligatory education such as filling the course time or the one-off thing has limitation. And taking complementary measures needs since there were many opinions that employees feel difficult to understand papers such as regulation and guidelines and so on related security. Finally, we hope to make fundament available to evaluate nuclear security culture recognition level based on the existing questionnaire would be changed to realistic and enhancement in recognition survey for future nuclear security culture.

Application of pattern recognition methods for evaluating the immune status in patients

International Nuclear Information System (INIS)

Stavitsky, R.B.; Guslistyj, I.V.; Miroshnichenko, I.V.; Karklinskaya, O.N.; Ryabinina, I.D.; Kosova, I.P.; Stolpnikova, V.N.; Malaeva, N.S.; Latypova, I.I.; Lebedev, L.A.

2001-01-01

The effectiveness of mathematical tools for pattern recognition as applied to numerical assessments of the immune status of patients exposed to ecological hazards is evaluated by experimentation. The immune status is estimated according to a two-class scheme (norm/abnormality) based on blood indicators of immunity for the patients examined. The task of categorizing patients by immunological parameters of blood is shown to be resolved with high effectiveness for determining the immune status [ru

Kazakh Traditional Dance Gesture Recognition

Science.gov (United States)

Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

2014-04-01

Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

GENERAL ENVIRONMENTAL CORPORATION; CURE ELECTROCOAGULATION TECHNOLOGY: INNOVATIVE TECHNOLOGY EVALUATION REPORT

Science.gov (United States)

The CURE electrocoagulation technology was demonstrated under the Superfund Innovative Technology Evaluation (SITE) program at the U.S. Department of Energy (DOE) Rocky Flats Environmental Technology Site (RFETS), where water from the solar evaporation ponds (SEPs) was contaminat...

Technology evaluation for time sensitive data transport

DEFF Research Database (Denmark)

Wessing, Henrik; Breach, Tony; Colmenero, Alberto

. The NREN communities must provide underlying network infrastructures and transport technologies to facilitate ser-vices with such requirements to the network. In this paper we investigate and evaluate circuit and packet based transport technologies from classic best effort IP over MPLS flavours, Provider...... Backbone Bridging (PBB), “Transparent Interconnect of Lots of Links” (TRILL) to Optical Transport Network (OTN) and SDH. The transport technologies are evaluated theoreti-cally, using simulations and/or experimentally. Each transport technology is evaluated based on its performances and capabilities...... overhead and restoration time. Thirdly, complexity and automation possibilities for establishment of paths for high demanding applica-tions, and finally how the technologies are backed by research communities and major vendors like Ciena, Alcatel-Lucent, Nokia-Siemens and Huawei. The technologies...

An integrated impact assessment and weighting methodology: evaluation of the environmental consequences of computer display technology substitution.

Science.gov (United States)

Zhou, Xiaoying; Schoenung, Julie M

2007-04-01

Computer display technology is currently in a state of transition, as the traditional technology of cathode ray tubes is being replaced by liquid crystal display flat-panel technology. Technology substitution and process innovation require the evaluation of the trade-offs among environmental impact, cost, and engineering performance attributes. General impact assessment methodologies, decision analysis and management tools, and optimization methods commonly used in engineering cannot efficiently address the issues needed for such evaluation. The conventional Life Cycle Assessment (LCA) process often generates results that can be subject to multiple interpretations, although the advantages of the LCA concept and framework obtain wide recognition. In the present work, the LCA concept is integrated with Quality Function Deployment (QFD), a popular industrial quality management tool, which is used as the framework for the development of our integrated model. The problem of weighting is addressed by using pairwise comparison of stakeholder preferences. Thus, this paper presents a new integrated analytical approach, Integrated Industrial Ecology Function Deployment (I2-EFD), to assess the environmental behavior of alternative technologies in correlation with their performance and economic characteristics. Computer display technology is used as the case study to further develop our methodology through the modification and integration of various quality management tools (e.g., process mapping, prioritization matrix) and statistical methods (e.g., multi-attribute analysis, cluster analysis). Life cycle thinking provides the foundation for our methodology, as we utilize a published LCA report, which stopped at the characterization step, as our starting point. Further, we evaluate the validity and feasibility of our methodology by considering uncertainty and conducting sensitivity analysis.

Evaluating color descriptors for object and scene recognition.

Science.gov (United States)

van de Sande, Koen E A; Gevers, Theo; Snoek, Cees G M

2010-09-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been proposed. Because many different descriptors exist, a structured overview is required of color invariant descriptors in the context of image category recognition. Therefore, this paper studies the invariance properties and the distinctiveness of color descriptors (software to compute the color descriptors from this paper is available from http://www.colordescriptors.com) in a structured way. The analytical invariance properties of color descriptors are explored, using a taxonomy based on invariance properties with respect to photometric transformations, and tested experimentally using a data set with known illumination conditions. In addition, the distinctiveness of color descriptors is assessed experimentally using two benchmarks, one from the image domain and one from the video domain. From the theoretical and experimental results, it can be derived that invariance to light intensity changes and light color changes affects category recognition. The results further reveal that, for light intensity shifts, the usefulness of invariance is category-specific. Overall, when choosing a single descriptor and no prior knowledge about the data set and object and scene categories is available, the OpponentSIFT is recommended. Furthermore, a combined set of color descriptors outperforms intensity-based SIFT and improves category recognition by 8 percent on the PASCAL VOC 2007 and by 7 percent on the Mediamill Challenge.

Familiar Person Recognition: Is Autonoetic Consciousness More Likely to Accompany Face Recognition Than Voice Recognition?

Science.gov (United States)

Barsics, Catherine; Brédart, Serge

2010-11-01

Autonoetic consciousness is a fundamental property of human memory, enabling us to experience mental time travel, to recollect past events with a feeling of self-involvement, and to project ourselves in the future. Autonoetic consciousness is a characteristic of episodic memory. By contrast, awareness of the past associated with a mere feeling of familiarity or knowing relies on noetic consciousness, depending on semantic memory integrity. Present research was aimed at evaluating whether conscious recollection of episodic memories is more likely to occur following the recognition of a familiar face than following the recognition of a familiar voice. Recall of semantic information (biographical information) was also assessed. Previous studies that investigated the recall of biographical information following person recognition used faces and voices of famous people as stimuli. In this study, the participants were presented with personally familiar people's voices and faces, thus avoiding the presence of identity cues in the spoken extracts and allowing a stricter control of frequency exposure with both types of stimuli (voices and faces). In the present study, the rate of retrieved episodic memories, associated with autonoetic awareness, was significantly higher from familiar faces than familiar voices even though the level of overall recognition was similar for both these stimuli domains. The same pattern was observed regarding semantic information retrieval. These results and their implications for current Interactive Activation and Competition person recognition models are discussed.

Hidden neural networks: application to speech recognition

DEFF Research Database (Denmark)

Riis, Søren Kamaric

1998-01-01

We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...

Pattern recognition and string matching

CERN Document Server

Cheng, Xiuzhen

2002-01-01

The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

Ethical aspects of face recognition systems in public places.

NARCIS (Netherlands)

Brey, Philip A.E.

2004-01-01

This essay examines ethical aspects of the use of facial recognition technology for surveillance purposes in public and semipublic areas, focusing particularly on the balance between security and privacy and civil liberties. As a case study, the FaceIt facial recognition engine of Identix

Practice-centred evaluation and the privileging of care in health information technology evaluation.

Science.gov (United States)

Darking, Mary; Anson, Rachel; Bravo, Ferdinand; Davis, Julie; Flowers, Steve; Gillingham, Emma; Goldberg, Lawrence; Helliwell, Paul; Henwood, Flis; Hudson, Claire; Latimer, Simon; Lowes, Paul; Stirling, Ian

2014-06-05

Our contribution, drawn from our experience of the case study provided, is a protocol for practice-centred, participative evaluation of technology in the clinical setting that privileges care. In this context 'practice-centred' evaluation acts as a scalable, coordinating framework for evaluation that recognises health information technology supported care as an achievement that is contingent and ongoing. We argue that if complex programmes of technology-enabled service innovation are understood in terms of their contribution to patient care and supported by participative, capability-building evaluation methodologies, conditions are created for practitioners and patients to realise the potential of technologies and make substantive contributions to the evidence base underpinning health innovation programmes. Electronic Patient Records (EPRs) and telemedicine are positioned by policymakers as health information technologies that are integral to achieving improved clinical outcomes and efficiency savings. However, evaluating the extent to which these aims are met poses distinct evaluation challenges, particularly where clinical and cost outcomes form the sole focus of evaluation design. We propose that a practice-centred approach to evaluation - in which those whose day-to-day care practice is altered (or not) by the introduction of new technologies are placed at the centre of evaluation efforts - can complement and in some instances offer advantages over, outcome-centric evaluation models. We carried out a regional programme of innovation in renal services where a participative approach was taken to the introduction of new technologies, including: a regional EPR system and a system to support video clinics. An 'action learning' approach was taken to procurement, pre-implementation planning, implementation, ongoing development and evaluation. Participants included clinicians, technology specialists, patients and external academic researchers. Whilst undergoing these

Sustainability evaluation of water supply technologies

DEFF Research Database (Denmark)

Godskesen, Berit

Sustainability evaluation of water supply systems is important to include in the decision making process when planning new technologies or resources for water supply. In Denmark the motivations may be many and different for changing technology, but since water supply is based on groundwater...... the main driver is the limitations of the available resource from the groundwater bodies. The environmental impact of products and systems can be evaluated by life-cycle assessment (LCA) which is a comprehensive and dominant decision support tool capable of evaluating a water system from the cradle......-criteria decision analysis method was used to develop a decision support system and applied to the study. In this thesis a standard LCA of the drinking water supply technology of today (base case) and 4 alternative cases for water supply technologies is conducted. The standard LCA points at the case rain...

New technique for real-time distortion-invariant multiobject recognition and classification

Science.gov (United States)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

Interprofessional, simulation-based technology-enhanced learning to improve physical health care in psychiatry: The recognition and assessment of medical problems in psychiatric settings course.

Science.gov (United States)

Akroyd, Mike; Jordan, Gary; Rowlands, Paul

2016-06-01

People with serious mental illness have reduced life expectancy compared with a control population, much of which is accounted for by significant physical comorbidity. Frontline clinical staff in mental health often lack confidence in recognition, assessment and management of such 'medical' problems. Simulation provides one way for staff to practise these skills in a safe setting. We produced a multidisciplinary simulation course around recognition and assessment of medical problems in psychiatric settings. We describe an audit of strategic and design aspects of the recognition and assessment of medical problems in psychiatric settings course, using the Department of Health's 'Framework for Technology Enhanced Learning' as our audit standards. At the same time as highlighting areas where recognition and assessment of medical problems in psychiatric settings adheres to these identified principles, such as the strategic underpinning of the approach, and the means by which information is collected, reviewed and shared, it also helps us to identify areas where we can improve. © The Author(s) 2014.

Development of technology for next generation reactor - Research of evaluation technology for nuclear power plant -

Energy Technology Data Exchange (ETDEWEB)

Park, Jong Kyun; Chang, Moon Heuy; Hwang, Yung Dong [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)] [and others

1993-09-01

For development of next generation reactor, a project for evaluation technology for nuclear power plant is performed. Evaluation technology is essential to next generation reactor for reactor safety and system analysis. For design concept, detailed evaluation technologies are studied as follows: evaluation of safety margin, evaluation of safety facilities, evaluation of measurement and control technology; man-machine interface. Especially for thermal efficiency, thermal properties and chemical composition of inconel 690 tube, instead of inconel 600 tube, are measured for steam generator. (Author).

Human action recognition with depth cameras

CERN Document Server

Wang, Jiang; Wu, Ying

2014-01-01

Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, includi

Type-2 fuzzy graphical models for pattern recognition

CERN Document Server

Zeng, Jia

2015-01-01

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

English for Science and Technology - Stylistics and Methods

DEFF Research Database (Denmark)

Mousten, Birthe

The book covers basic methods for summarizing and editing of EST writing (English for Science and Technology). In addition, translation of basically technically oriented texts is covered with a view to an evaluation of formality, complexity and audience recognition in connection with different text...

A New Database for Speaker Recognition

DEFF Research Database (Denmark)

Feng, Ling; Hansen, Lars Kai

2005-01-01

In this paper we discuss properties of speech databases used for speaker recognition research and evaluation, and we characterize some popular standard databases. The paper presents a new database called ELSDSR dedicated to speaker recognition applications. The main characteristics of this database...

Weapons of Mass Destruction Technology Evaluation and Training Range

Energy Technology Data Exchange (ETDEWEB)

Kevin Larry Young

2009-05-01

The Idaho National Laboratory (INL) has a long history for providing technology evaluation and training for military and other federal level Weapons of Mass Destruction (WMD) response agencies. Currently there are many federal organizations and commercial companies developing technologies related to detecting, assessing, mitigating and protecting against hazards associated with a WMD event. Unfortunately, very few locations exist within the United States where WMD response technologies are realistically field tested and evaluated using real chemical, biological, radiological, nuclear and explosive materials. This is particularly true with biological and radiological hazards. Related to this lack of adequate WMD, multi-hazard technology testing capability is the shortage of locations where WMD response teams can train using actual chemical, biological, and radiological material or highly realistic simulates. In response to these technology evaluation and training needs, the INL has assembled a consortium of subject matter experts from existing programs and identified dedicated resources for the purpose of establishing an all-hazards, WMD technology evaluation and training range. The author describes the challenges associated with creating the all-hazards WMD technology evaluation and training range and lists the technical, logistical and financial benefits of an all-hazards technology evaluation and training range. Current resources and capabilities for conducting all-hazard technology evaluation and training at the INL are identified. Existing technology evaluation and training programs at the INL related to radiological, biological and chemical hazards are highlighted, including successes and lessons learned. Finally, remaining gaps in WMD technology evaluation and training capabilities are identified along with recommendations for closing those gaps.

Factors that influence the recognition, reporting and resolution of incidents related to medical devices and other healthcare technologies: a systematic review.

Science.gov (United States)

Polisena, Julie; Gagliardi, Anna; Urbach, David; Clifford, Tammy; Fiander, Michelle

2015-03-29

Medical devices have improved the treatment of many medical conditions. Despite their benefit, the use of devices can lead to unintended incidents, potentially resulting in unnecessary harm, injury or complications to the patient, a complaint, loss or damage. Devices are used in hospitals on a routine basis. Research to date, however, has been primarily limited to describing incidents rates, so the optimal design of a hospital-based surveillance system remains unclear. Our research objectives were twofold: i) to explore factors that influence device-related incident recognition, reporting and resolution and ii) to investigate interventions or strategies to improve the recognition, reporting and resolution of medical device-related incidents. We searched the bibliographic databases: MEDLINE, Embase, the Cochrane Central Register of Controlled Trials and PsycINFO database. Grey literature (literature that is not commercially available) was searched for studies on factors that influence incident recognition, reporting and resolution published and interventions or strategies for their improvement from 2003 to 2014. Although we focused on medical devices, other health technologies were eligible for inclusion. Thirty studies were included in our systematic review, but most studies were concentrated on other health technologies. The study findings indicate that fear of punishment, uncertainty of what should be reported and how incident reports will be used and time constraints to incident reporting are common barriers to incident recognition and reporting. Relevant studies on the resolution of medical errors were not found. Strategies to improve error reporting include the use of an electronic error reporting system, increased training and feedback to frontline clinicians about the reported error. The available evidence on factors influencing medical device-related incident recognition, reporting and resolution by healthcare professionals can inform data collection and

Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

Science.gov (United States)

Chherawala, Youssouf; Roy, Partha Pratim; Cheriet, Mohamed

2016-12-01

The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than a straightforward comparison based on the recognition rate. In this paper, we propose a framework for feature set evaluation based on a collaborative setting. We use a weighted vote combination of recurrent neural network (RNN) classifiers, each trained with a particular feature set. This combination is modeled in a probabilistic framework as a mixture model and two methods for weight estimation are described. The main contribution of this paper is to quantify the importance of feature sets through the combination weights, which reflect their strength and complementarity. We chose the RNN classifier because of its state-of-the-art performance. Also, we provide the first feature set benchmark for this classifier. We evaluated several feature sets on the IFN/ENIT and RIMES databases of Arabic and Latin script, respectively. The resulting combination model is competitive with state-of-the-art systems.

Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

Directory of Open Access Journals (Sweden)

Marc Wieland

2014-03-01

Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

Technology Evaluation Report: Non-destructive ...

Science.gov (United States)

Technology Evaluation Report HSRP is working to develop tools and information that will help detect the intentional introduction of chemical or biological contaminants in buildings or water systems, the containment of these contaminants, the decontamination of buildings and/or water systems, and the management of wastes generated from decontamination and cleanup operations. Evaluation of the performance of CBI Polymers’ DeconGelTM 1108, Environmental Alternatives, Inc.’s (EAI’s) Rad-Release II (RRII), Environmental Alternatives, Inc.’s SuperGel, and Intek Technologies’ LH-21. The objective of evaluating these technologies was to test their ability to remove radioactive cesium (Cs)-137 from the mixed building material coupons of brick with mortar, tile with grout, granite with mortar, all mortar and all grout coupons.

High Speed Railway Environment Safety Evaluation Based on Measurement Attribute Recognition Model

Directory of Open Access Journals (Sweden)

Qizhou Hu

2014-01-01

Full Text Available In order to rationally evaluate the high speed railway operation safety level, the environmental safety evaluation index system of high speed railway should be well established by means of analyzing the impact mechanism of severe weather such as raining, thundering, lightning, earthquake, winding, and snowing. In addition to that, the attribute recognition will be identified to determine the similarity between samples and their corresponding attribute classes on the multidimensional space, which is on the basis of the Mahalanobis distance measurement function in terms of Mahalanobis distance with the characteristics of noncorrelation and nondimensionless influence. On top of the assumption, the high speed railway of China environment safety situation will be well elaborated by the suggested methods. The results from the detailed analysis show that the evaluation is basically matched up with the actual situation and could lay a scientific foundation for the high speed railway operation safety.

Window Size Impact in Human Activity Recognition

Directory of Open Access Journals (Sweden)

Oresti Banos

2014-04-01

Full Text Available Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.

Speech recognition implementation in radiology

International Nuclear Information System (INIS)

White, Keith S.

2005-01-01

Continuous speech recognition (SR) is an emerging technology that allows direct digital transcription of dictated radiology reports. The SR systems are being widely deployed in the radiology community. This is a review of technical and practical issues that should be considered when implementing an SR system. (orig.)

Mobile Application Development for Quran Verse Recognition and Interpretations

Directory of Open Access Journals (Sweden)

Maha Alqahtani

2015-01-01

Full Text Available Mobile learning or “m-learning” is the process of learning when learners are not at a fixed location or time and can exploit the advantage of learning opportunities using mobile technologies. Nowadays, speech recognition is being used in many mobile applications. Speech recognition helps people to interact with the device as if were they talking to another person. This technology helps people to learn anything using computers by promoting self-study over extended periods of time. The objective of this study is focusing on designing and developing a mobile application for the Arabic recognition of spoken Quranic verses. The application is suitable for Android-based devices. The application is called Say Quran and is available on Google Play Store. Moreover, this paper presents the results of a preliminary experimentation to gather feedback from students regarding the developed application

Improving early cycle economic evaluation of diagnostic technologies

NARCIS (Netherlands)

Steuten, Lotte Maria Gertruda; Ramsey, Scott D.

2014-01-01

The rapidly increasing range and expense of new diagnostics, compels consideration of a different, more proactive approach to health economic evaluation of diagnostic technologies. Early cycle economic evaluation is a decision analytic approach to evaluate technologies in development so as to

Finger vein recognition based on convolutional neural network

Directory of Open Access Journals (Sweden)

Meng Gesi

2017-01-01

Full Text Available Biometric Authentication Technology has been widely used in this information age. As one of the most important technology of authentication, finger vein recognition attracts our attention because of its high security, reliable accuracy and excellent performance. However, the current finger vein recognition system is difficult to be applied widely because its complicated image pre-processing and not representative feature vectors. To solve this problem, a finger vein recognition method based on the convolution neural network (CNN is proposed in the paper. The image samples are directly input into the CNN model to extract its feature vector so that we can make authentication by comparing the Euclidean distance between these vectors. Finally, the Deep Learning Framework Caffe is adopted to verify this method. The result shows that there are great improvements in both speed and accuracy rate compared to the previous research. And the model has nice robustness in illumination and rotation.

Combining users' activity survey and simulators to evaluate human activity recognition systems.

Science.gov (United States)

Azkune, Gorka; Almeida, Aitor; López-de-Ipiña, Diego; Chen, Liming

2015-04-08

Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant.

Combining Users’ Activity Survey and Simulators to Evaluate Human Activity Recognition Systems

Directory of Open Access Journals (Sweden)

Gorka Azkune

2015-04-01

Full Text Available Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant.

Combining Users' Activity Survey and Simulators to Evaluate Human Activity Recognition Systems

Science.gov (United States)

Azkune, Gorka; Almeida, Aitor; López-de-Ipiña, Diego; Chen, Liming

2015-01-01

Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies, where experiments with humans are run with the consequent ethical and legal issues. We propose a novel evaluation methodology to overcome the enumerated problems, which is based on surveys for users and a synthetic dataset generator tool. Surveys allow capturing how different users perform activities of daily living, while the synthetic dataset generator is used to create properly labelled activity datasets modelled with the information extracted from surveys. Important aspects, such as sensor noise, varying time lapses and user erratic behaviour, can also be simulated using the tool. The proposed methodology is shown to have very important advantages that allow researchers to carry out their work more efficiently. To evaluate the approach, a synthetic dataset generated following the proposed methodology is compared to a real dataset computing the similarity between sensor occurrence frequencies. It is concluded that the similarity between both datasets is more than significant. PMID:25856329

Gabor Weber Local Descriptor for Bovine Iris Recognition

OpenAIRE

Sun, Shengnan; Zhao, Lindu; Yang, Shicai

2013-01-01

Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD). We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersectio...

Decision support software technology demonstration plan

Energy Technology Data Exchange (ETDEWEB)

SULLIVAN,T.; ARMSTRONG,A.

1998-09-01

The performance evaluation of innovative and alternative environmental technologies is an integral part of the US Environmental Protection Agency's (EPA) mission. Early efforts focused on evaluating technologies that supported the implementation of the Clean Air and Clean Water Acts. In 1986 the Agency began to demonstrate and evaluate the cost and performance of remediation and monitoring technologies under the Superfund Innovative Technology Evaluation (SITE) program (in response to the mandate in the Superfund Amendments and Reauthorization Act of 1986 (SARA)). In 1990, the US Technology Policy was announced. This policy placed a renewed emphasis on making the best use of technology in achieving the national goals of improved quality of life for all Americans, continued economic growth, and national security. In the spirit of the technology policy, the Agency began to direct a portion of its resources toward the promotion, recognition, acceptance, and use of US-developed innovative environmental technologies both domestically and abroad. Decision Support Software (DSS) packages integrate environmental data and simulation models into a framework for making site characterization, monitoring, and cleanup decisions. To limit the scope which will be addressed in this demonstration, three endpoints have been selected for evaluation: Visualization; Sample Optimization; and Cost/Benefit Analysis. Five topics are covered in this report: the objectives of the demonstration; the elements of the demonstration plan; an overview of the Site Characterization and Monitoring Technology Pilot; an overview of the technology verification process; and the purpose of this demonstration plan.

Face recognition, a landmarks tale

NARCIS (Netherlands)

Beumer, G.M.

2009-01-01

Face recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their

Innovative technology transfer of nondestructive evaluation research

Science.gov (United States)

Brian Brashaw; Robert J. Ross; Xiping Wang

2008-01-01

Technology transfer is often an afterthought for many nondestructive evaluation (NDE) researchers. Effective technology transfer should be considered during the planning and execution of research projects. This paper outlines strategies for using technology transfer in NDE research and presents a wide variety of technology transfer methods used by a cooperative...

Students’ Perception on Teaching Practicum Evaluation using Video Technology

Science.gov (United States)

Chee Sern, Lai; ‘Ain Helan Nor, Nurul; Foong, Lee Ming; Hassan, Razali

2017-08-01

Video technology has been widely used in education especially in teaching and learning. However, the use of video technology for evaluation purpose especially in teaching practicum is extremely scarce and the benefits of video technology in teaching practicum evaluation have not yet been fully discovered. For that reason, this quantitative research aimed at identifying the perceptions of trainee teachers towards teaching practicum evaluation via video technology. A total of 260 students of Teacher Certification Programme (Program Pensiswazahan Guru - PPG) from the Faculty of Technical and Vocational Education (FPTV) of Universiti Tun Hussein Onn Malaysia (UTHM) had been randomly selected as respondents. A set of questionnaire was developed to assess the suitability, effectiveness and satisfaction of using video technology for teaching practicum. Conclusively, this research showed that the trainee teachers have positive perceptions in all three aspects related teaching practicum evaluation using video technology. Apart from that, no significant racial difference was found in the measured aspects. In addition, the trainee teachers also showed an understanding of the vast importance of teaching practicum evaluation via video. These research findings suggest that video technology can be a feasible and practical means of teaching practicum evaluation especially for distance learning program.

Subspace methods for pattern recognition in intelligent environment

CERN Document Server

Jain, Lakhmi

2014-01-01

This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

Man, society, technology

International Nuclear Information System (INIS)

Kistler, E.; Jaufmann, D.

1990-01-01

The acceptance of technological risks, which is discussed today mainly in the context of large-scale technologies, has become the subject of political argument, of power politics and also of negotiation. Its evaluation and assessment depend not least on the current atmosphere for decisions and the specific subject. Acceptance research - this is one of the central theses of this book - is not (only) a reactive instrument for later fine-tuning after the probability of risk is evident, but can also be more. However, it requires to this end 'cleaner' and more comprehensible methods; the recognition of its viability limits is also necessary. It provides then a possibility for a rational formulation of policies on the basis of a long-standing, and certainly partly superfluous technological-political dialogue. (orig.) [de

Improved Hip-Based Individual Recognition Using Wearable Motion Recording Sensor

Science.gov (United States)

Gafurov, Davrondzhon; Bours, Patrick

In todays society the demand for reliable verification of a user identity is increasing. Although biometric technologies based on fingerprint or iris can provide accurate and reliable recognition performance, they are inconvenient for periodic or frequent re-verification. In this paper we propose a hip-based user recognition method which can be suitable for implicit and periodic re-verification of the identity. In our approach we use a wearable accelerometer sensor attached to the hip of the person, and then the measured hip motion signal is analysed for identity verification purposes. The main analyses steps consists of detecting gait cycles in the signal and matching two sets of detected gait cycles. Evaluating the approach on a hip data set consisting of 400 gait sequences (samples) from 100 subjects, we obtained equal error rate (EER) of 7.5% and identification rate at rank 1 was 81.4%. These numbers are improvements by 37.5% and 11.2% respectively of the previous study using the same data set.

A rapid automatic analyzer and its methodology for effective bentonite content based on image recognition technology

Directory of Open Access Journals (Sweden)

Wei Long

2016-09-01

Full Text Available Fast and accurate determination of effective bentonite content in used clay bonded sand is very important for selecting the correct mixing ratio and mixing process to obtain high-performance molding sand. Currently, the effective bentonite content is determined by testing the ethylene blue absorbed in used clay bonded sand, which is usually a manual operation with some disadvantages including complicated process, long testing time and low accuracy. A rapid automatic analyzer of the effective bentonite content in used clay bonded sand was developed based on image recognition technology. The instrument consists of auto stirring, auto liquid removal, auto titration, step-rotation and image acquisition components, and processor. The principle of the image recognition method is first to decompose the color images into three-channel gray images based on the photosensitive degree difference of the light blue and dark blue in the three channels of red, green and blue, then to make the gray values subtraction calculation and gray level transformation of the gray images, and finally, to extract the outer circle light blue halo and the inner circle blue spot and calculate their area ratio. The titration process can be judged to reach the end-point while the area ratio is higher than the setting value.

The Army word recognition system

Science.gov (United States)

Hadden, David R.; Haratz, David

1977-01-01

The application of speech recognition technology in the Army command and control area is presented. The problems associated with this program are described as well as as its relevance in terms of the man/machine interactions, voice inflexions, and the amount of training needed to interact with and utilize the automated system.

Speech emotion recognition methods: A literature review

Science.gov (United States)

Basharirad, Babak; Moradhaseli, Mohammadreza

2017-10-01

Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to identify the emotional state through speech. Selection of suitable feature sets, design of a proper classifications methods and prepare an appropriate dataset are the main key issues of speech emotion recognition systems. This paper critically analyzed the current available approaches of speech emotion recognition methods based on the three evaluating parameters (feature set, classification of features, accurately usage). In addition, this paper also evaluates the performance and limitations of available methods. Furthermore, it highlights the current promising direction for improvement of speech emotion recognition systems.

Hybrid gesture recognition system for short-range use

Science.gov (United States)

Minagawa, Akihiro; Fan, Wei; Katsuyama, Yutaka; Takebe, Hiroaki; Ozawa, Noriaki; Hotta, Yoshinobu; Sun, Jun

2012-03-01

In recent years, various gesture recognition systems have been studied for use in television and video games[1]. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated[2]. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach)[3] and motion analysis using image frame differences (motion-based approach)(for example, see[4]). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.

Transferability of economic evaluations of medical technologies: a new technology for orthopedic surgery.

Science.gov (United States)

Steuten, Lotte; Vallejo-Torres, Laura; Young, Terry; Buxton, Martin

2008-05-01

Transferring results of economic evaluations across countries or jurisdictions can potentially save scarce evaluation resources while helping to make market access and reimbursement decisions in a timely fashion. This article points out why transferring results of economic evaluations is particularly important in the field of medical technologies. It then provides an overview of factors that are previously identified in the literature as affecting transferability of economic evaluations, as well as methods for transferring results in a scientifically sound way. As the current literature almost exclusively relates to transferability of pharmacoeconomic evaluations, this article highlights those factors and methodologies that are of particular relevance to transferring medical technology assessments. Considering the state-of-the-art literature and a worked, real life, example of transferring an economic evaluation of a product used in orthopedic surgery, we provide recommendations for future work in this important area of medical technology assessment.

Evaluative conditioning of food technologies in China

DEFF Research Database (Denmark)

Loebnitz, Natascha; Grunert, Klaus G

2014-01-01

This study provides an initial examination of the evaluative conditioning (EC) of consumers’ attitudes toward food technologies in China, including how EC can affect consumer acceptance of new technology when participants possess different levels of social trust. In a study using the EC paradigm...... and a combination of between-subjects control groups and within-subjects control conditions, participants considered three food technologies (conventional, enzyme, and genetic), paired with affectively positive, neutral, and negative images. Subsequent evaluative measurements revealed that EC can explain attitude...... formation toward food technologies in China when consumers see affective images, but the strength of the effects varies at different levels of social trust. Participants with a high level of trust in the institutions that promote and regulate the technologies can be conditioned both positively...

Implementation and preliminary evaluation of 'C-tone': A novel algorithm to improve lexical tone recognition in Mandarin-speaking cochlear implant users.

Science.gov (United States)

Ping, Lichuan; Wang, Ningyuan; Tang, Guofang; Lu, Thomas; Yin, Li; Tu, Wenhe; Fu, Qian-Jie

2017-09-01

Because of limited spectral resolution, Mandarin-speaking cochlear implant (CI) users have difficulty perceiving fundamental frequency (F0) cues that are important to lexical tone recognition. To improve Mandarin tone recognition in CI users, we implemented and evaluated a novel real-time algorithm (C-tone) to enhance the amplitude contour, which is strongly correlated with the F0 contour. The C-tone algorithm was implemented in clinical processors and evaluated in eight users of the Nurotron NSP-60 CI system. Subjects were given 2 weeks of experience with C-tone. Recognition of Chinese tones, monosyllables, and disyllables in quiet was measured with and without the C-tone algorithm. Subjective quality ratings were also obtained for C-tone. After 2 weeks of experience with C-tone, there were small but significant improvements in recognition of lexical tones, monosyllables, and disyllables (P C-tone were greater for disyllables than for monosyllables. Subjective quality ratings showed no strong preference for or against C-tone, except for perception of own voice, where C-tone was preferred. The real-time C-tone algorithm provided small but significant improvements for speech performance in quiet with no change in sound quality. Pre-processing algorithms to reduce noise and better real-time F0 extraction would improve the benefits of C-tone in complex listening environments. Chinese CI users' speech recognition in quiet can be significantly improved by modifying the amplitude contour to better resemble the F0 contour.

Improving early cycle economic evaluation of diagnostic technologies.

Science.gov (United States)

Steuten, Lotte M G; Ramsey, Scott D

2014-08-01

The rapidly increasing range and expense of new diagnostics, compels consideration of a different, more proactive approach to health economic evaluation of diagnostic technologies. Early cycle economic evaluation is a decision analytic approach to evaluate technologies in development so as to increase the return on investment as well as patient and societal impact. This paper describes examples of 'early cycle economic evaluations' as applied to diagnostic technologies and highlights challenges in its real-time application. It shows that especially in the field of diagnostics, with rapid technological developments and a changing regulatory climate, early cycle economic evaluation can have a guiding role to improve the efficiency of the diagnostics innovation process. In the next five years the attention will move beyond the methodological and analytic challenges of early cycle economic evaluation towards the challenge of effectively applying it to improve diagnostic research and development and patient value. Future work in this area should therefore be 'strong on principles and soft on metrics', that is, the metrics that resonate most clearly with the various decision makers in this field.

Evaluating Color Descriptors for Object and Scene Recognition

NARCIS (Netherlands)

van de Sande, K.E.A.; Gevers, T.; Snoek, C.G.M.

2010-01-01

Image category recognition is important to access visual information on the level of objects and scene types. So far, intensity-based descriptors have been widely used for feature extraction at salient points. To increase illumination invariance and discriminative power, color descriptors have been

Review of Design of Speech Recognition and Text Analytics based Digital Banking Customer Interface and Future Directions of Technology Adoption

OpenAIRE

Saha, Amal K

2017-01-01

Banking is one of the most significant adopters of cutting-edge information technologies. Since its modern era beginning in the form of paper based accounting maintained in the branch, adoption of computerized system made it possible to centralize the processing in data centre and improve customer experience by making a more available and efficient system. The latest twist in this evolution is adoption of natural language processing and speech recognition in the user interface between the hum...

Analysis and evaluation of the applicability of green energy technology

Science.gov (United States)

Xu, Z. J.; Song, Y. K.

2017-11-01

With the seriousness of environmental issues and the shortage of resources, the applicability of green energy technology has been paid more and more attention by scholars in different fields. However, the current researches are often single in perspective and simple in method. According to the Theory of Applicable Technology, this paper analyzes and defines the green energy technology and its applicability from the all-around perspectives of symbiosis of economy, society, environment and science & technology etc., and correspondingly constructs the evaluation index system. The paper further applies the Fuzzy Comprehensive Evaluation to the evaluation of its applicability, discusses in depth the evaluation models and methods, and explains in detail with an example. The author holds that the applicability of green energy technology involves many aspects of economy, society, environment and science & technology and can be evaluated comprehensively by an index system composed of a number of independent indexes. The evaluation is multi-object, multi-factor, multi-level and fuzzy comprehensive, which is undoubtedly correct, effective and feasible by the Fuzzy Comprehensive Evaluation. It is of vital theoretical and practical significance to understand and evaluate comprehensively the applicability of green energy technology for the rational development and utilization of green energy technology and for the better promotion of sustainable development of human and nature.

Research on Three-dimensional Motion History Image Model and Extreme Learning Machine for Human Body Movement Trajectory Recognition

Directory of Open Access Journals (Sweden)

Zheng Chang

2015-01-01

Full Text Available Based on the traditional machine vision recognition technology and traditional artificial neural networks about body movement trajectory, this paper finds out the shortcomings of the traditional recognition technology. By combining the invariant moments of the three-dimensional motion history image (computed as the eigenvector of body movements and the extreme learning machine (constructed as the classification artificial neural network of body movements, the paper applies the method to the machine vision of the body movement trajectory. In detail, the paper gives a detailed introduction about the algorithm and realization scheme of the body movement trajectory recognition based on the three-dimensional motion history image and the extreme learning machine. Finally, by comparing with the results of the recognition experiments, it attempts to verify that the method of body movement trajectory recognition technology based on the three-dimensional motion history image and extreme learning machine has a more accurate recognition rate and better robustness.

Performance Evaluation Methods for Assistive Robotic Technology

Science.gov (United States)

Tsui, Katherine M.; Feil-Seifer, David J.; Matarić, Maja J.; Yanco, Holly A.

Robots have been developed for several assistive technology domains, including intervention for Autism Spectrum Disorders, eldercare, and post-stroke rehabilitation. Assistive robots have also been used to promote independent living through the use of devices such as intelligent wheelchairs, assistive robotic arms, and external limb prostheses. Work in the broad field of assistive robotic technology can be divided into two major research phases: technology development, in which new devices, software, and interfaces are created; and clinical, in which assistive technology is applied to a given end-user population. Moving from technology development towards clinical applications is a significant challenge. Developing performance metrics for assistive robots poses a related set of challenges. In this paper, we survey several areas of assistive robotic technology in order to derive and demonstrate domain-specific means for evaluating the performance of such systems. We also present two case studies of applied performance measures and a discussion regarding the ubiquity of functional performance measures across the sampled domains. Finally, we present guidelines for incorporating human performance metrics into end-user evaluations of assistive robotic technologies.

Technology Games: Using Wittgenstein for Understanding and Evaluating Technology.

Science.gov (United States)

Coeckelbergh, Mark

2017-08-15

In the philosophy of technology after the empirical turn, little attention has been paid to language and its relation to technology. In this programmatic and explorative paper, it is proposed to use the later Wittgenstein, not only to pay more attention to language use in philosophy of technology, but also to rethink technology itself-at least technology in its aspect of tool, technology-in-use. This is done by outlining a working account of Wittgenstein's view of language (as articulated mainly in the Investigations) and by then applying that account to technology-turning around Wittgenstein's metaphor of the toolbox. Using Wittgenstein's concepts of language games and form of life and coining the term 'technology games', the paper proposes and argues for a use-oriented, holistic, transcendental, social, and historical approach to technology which is empirically but also normatively sensitive, and which takes into account implicit knowledge and know-how. It gives examples of interaction with social robots to support the relevance of this project for understanding and evaluating today's technologies, makes comparisons with authors in philosophy of technology such as Winner and Ihde, and sketches the contours of a phenomenology and hermeneutics of technology use that may help us to understand but also to gain a more critical relation to specific uses of concrete technologies in everyday contexts. Ultimately, given the holism argued for, it also promises a more critical relation to the games and forms of life technologies are embedded in-to the ways we do things.

Energy technology evaluation report: Energy security

Science.gov (United States)

Koopman, R.; Lamont, A.; Schock, R.

1992-09-01

Energy security was identified in the National Energy Strategy (NES) as a major issue for the Department of Energy (DOE). As part of a process designed by the DOE to identify technologies important to implementing the NES, an expert working group was convened to consider which technologies can best contribute to reducing the nation's economic vulnerability to future disruptions of world oil supplies, the working definition of energy security. Other working groups were established to deal with economic growth, environmental quality, and technical foundations. Energy Security working group members were chosen to represent as broad a spectrum of energy supply and end-use technologies as possible and were selected for their established reputations as experienced experts with an ability to be objective. The time available for this evaluation was very short. The group evaluated technologies using criteria taken from the NES which can be summarized for energy security as follows: diversifying sources of world oil supply so as to decrease the increasing monopoly status of the Persian Gulf region; reducing the importance of oil use in the US economy to diminish the impact of future disruptions in oil supply; and increasing the preparedness of the US to deal with oil supply disruptions by having alternatives available at a known price. The result of the first phase of the evaluation process was the identification of technology groups determined to be clearly important for reducing US vulnerability to oil supply disruptions. The important technologies were mostly within the high leverage areas of oil and gas supply and transportation demand but also included hydrogen utilization, biomass, diversion resistant nuclear power, and substitute industrial feedstocks.

Cyber security evaluation of II&C technologies

Energy Technology Data Exchange (ETDEWEB)

Thomas, Ken [Idaho National Laboratory (INL), Idaho Falls, ID (United States)

2014-11-01

The Light Water Reactor Sustainability (LWRS) Program is a research and development program sponsored by the Department of Energy, which is conducted in close collaboration with industry to provide the technical foundations for licensing and managing the long-term, safe and economical operation of current nuclear power plants The LWRS Program serves to help the US nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of the plants and extension of the current operating licenses. Within the LWRS Program, the Advanced Instrumentation, Information, and Control (II&C) Systems Technologies Pathway conducts targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. operating light water reactor (LWR) fleet. The II&C Pathway is conducted by Idaho National Laboratory (INL). Cyber security is a common concern among nuclear utilities and other nuclear industry stakeholders regarding the digital technologies that are being developed under this program. This concern extends to the point of calling into question whether these types of technologies could ever be deployed in nuclear plants given the possibility that the information in them can be compromised and the technologies themselves can potentially be exploited to serve as attack vectors for adversaries. To this end, a cyber security evaluation has been conducted of these technologies to determine whether they constitute a threat beyond what the nuclear plants already manage within their regulatory-required cyber security programs. Specifically, the evaluation is based on NEI 08-09, which is the industry’s template for cyber security programs and evaluations, accepted by the Nuclear Regulatory Commission (NRC) as responsive to the requirements of the nuclear power plant cyber security regulation found in 10 CFR 73.54. The evaluation was conducted by a

FY 1991 report on the results of the contract R and D of the human sense measuring application technology. 4. R and D of correlation/evaluation technology (1); 1991 nendo ningen kankaku keisoku oyo gijutsu no kenkyu kaihatsu seika hokokusho. 4. Sokan hyoka gijutsu no kenkyu kaihatsu (1)

Energy Technology Data Exchange (ETDEWEB)

NONE

1991-03-01

As a part of the R and D of correlation/evaluation technology, the following R and D were conducted in this paper: (1) high accuracy real sense visual recognition; (2) working environment at nuclear power plant with human sense and affinity; (3) amenity correlation technology in the combined environment mainly of thermal environment. In (1), the following seven items were studied: software for high accuracy real sense visual recognition; software for detecting contact of human movement with object, etc.; improvement of performance of speed of CG image indicator; harmony between image expression and video presentation; software technology for high speed modeling; measuring system under the virtual reality; production of a set of prototype system. In (2), as the environment of nuclear power plant site, visual environment of centralized control room; audio-environment of machinery room, etc., and radio-environment; environment where people have to put on special working ware, etc. In (3), development of a system to examine correlations among external stimulus environment/physiological effect/sensory quantity based on physiological reaction models; development of technology to quantitatively estimate amenity in the combined environment mainly of thermal environment. (NEDO)

Opportunity recognition and international new venture creation in University spin-offs

DEFF Research Database (Denmark)

Hannibal, Martin; Evers, Natasha; Servais, Per

2016-01-01

Extant research suggests that the founder’s activities and interactions are considered pivotal in driving the opportunity recognition process leading to international new venture emergence. This paper aims to explore the opportunity recognition process and international new venture emergence...... in the context of university high-technology spin-offs that are internationally market driven from inception. University spin-offs (USOs) are defined as ‘new firms created to exploit commercially some knowledge, technology or research results developed within a university’ (Pirnay et al., Small Bus Econ 21...... that the inventor-founders are typically engaged in opportunity recognition processes that are characterized as creative, driven by scientific innovations. It is indicated that the process of USO emergence and continuous development involves activities and interactions similar to typical international new ventures...

Clean Technology Evaluation & Workforce Development Program

Energy Technology Data Exchange (ETDEWEB)

Patricia Glaza

2012-12-01

The overall objective of the Clean Technology Evaluation portion of the award was to design a process to speed up the identification of new clean energy technologies and match organizations to testing and early adoption partners. The project was successful in identifying new technologies targeted to utilities and utility technology integrators, in developing a process to review and rank the new technologies, and in facilitating new partnerships for technology testing and adoption. The purpose of the Workforce Development portion of the award was to create an education outreach program for middle & high-school students focused on clean technology science and engineering. While originally targeting San Diego, California and Cambridge, Massachusetts, the scope of the program was expanded to include a major clean technology speaking series and expo as part of the USA Science & Engineering Festival on the National Mall in Washington, D.C.

Comparison and evaluation of datasets for off-angle iris recognition

Science.gov (United States)

Kurtuncu, Osman M.; Cerme, Gamze N.; Karakaya, Mahmut

2016-05-01

In this paper, we investigated the publicly available iris recognition datasets and their data capture procedures in order to determine if they are suitable for the stand-off iris recognition research. Majority of the iris recognition datasets include only frontal iris images. Even if a few datasets include off-angle iris images, the frontal and off-angle iris images are not captured at the same time. The comparison of the frontal and off-angle iris images shows not only differences in the gaze angle but also change in pupil dilation and accommodation as well. In order to isolate the effect of the gaze angle from other challenging issues including dilation and accommodation, the frontal and off-angle iris images are supposed to be captured at the same time by using two different cameras. Therefore, we developed an iris image acquisition platform by using two cameras in this work where one camera captures frontal iris image and the other one captures iris images from off-angle. Based on the comparison of Hamming distance between frontal and off-angle iris images captured with the two-camera- setup and one-camera-setup, we observed that Hamming distance in two-camera-setup is less than one-camera-setup ranging from 0.05 to 0.001. These results show that in order to have accurate results in the off-angle iris recognition research, two-camera-setup is necessary in order to distinguish the challenging issues from each other.

Vehicle logo recognition using multi-level fusion model

Science.gov (United States)

Ming, Wei; Xiao, Jianli

2018-04-01

Vehicle logo recognition plays an important role in manufacturer identification and vehicle recognition. This paper proposes a new vehicle logo recognition algorithm. It has a hierarchical framework, which consists of two fusion levels. At the first level, a feature fusion model is employed to map the original features to a higher dimension feature space. In this space, the vehicle logos become more recognizable. At the second level, a weighted voting strategy is proposed to promote the accuracy and the robustness of the recognition results. To evaluate the performance of the proposed algorithm, extensive experiments are performed, which demonstrate that the proposed algorithm can achieve high recognition accuracy and work robustly.

Image preprocessing study on KPCA-based face recognition

Science.gov (United States)

Li, Xuan; Li, Dehua

2015-12-01

Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

Standoff Detection Technology Evaluation Facility

Data.gov (United States)

Federal Laboratory Consortium — The Standoff Detection Technology Evaluation facility is the only one of its kind in the country and allows researchers to release a known amount of material while...

Use of iris recognition camera technology for the quantification of corneal opacification in mucopolysaccharidoses.

Science.gov (United States)

Aslam, Tariq Mehmood; Shakir, Savana; Wong, James; Au, Leon; Ashworth, Jane

2012-12-01

Mucopolysaccharidoses (MPS) can cause corneal opacification that is currently difficult to objectively quantify. With newer treatments for MPS comes an increased need for a more objective, valid and reliable index of disease severity for clinical and research use. Clinical evaluation by slit lamp is very subjective and techniques based on colour photography are difficult to standardise. In this article the authors present evidence for the utility of dedicated image analysis algorithms applied to images obtained by a highly sophisticated iris recognition camera that is small, manoeuvrable and adapted to achieve rapid, reliable and standardised objective imaging in a wide variety of patients while minimising artefactual interference in image quality.

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

Application of biomolecular recognition via magnetic nanoparticle in nanobiotechnology

Science.gov (United States)

Shen, Wei-Zheng; Cetinel, Sibel; Montemagno, Carlo

2018-05-01

The marriage of biomolecular recognition and magnetic nanoparticle creates tremendous opportunities in the development of advanced technology both in academic research and in industrial sectors. In this paper, we review current progress on the magnetic nanoparticle-biomolecule hybrid systems, particularly employing the recognition pairs of DNA-DNA, DNA-protein, protein-protein, and protein-inorganics in several nanobiotechnology application areas, including molecular biology, diagnostics, medical treatment, industrial biocatalysts, and environmental separations.

Research of convolutional neural networks for traffic sign recognition

OpenAIRE

Stadalnikas, Kasparas

2017-01-01

In this thesis the convolutional neural networks application for traffic sign recognition is analyzed. Thesis describes the basic operations, techniques that are commonly used to apply in the image classification using convolutional neural networks. Also, this paper describes the data sets used for traffic sign recognition, their problems affecting the final training results. The paper reviews most popular existing technologies – frameworks for developing the solution for traffic sign recogni...

Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

Self-organization comprehensive real-time state evaluation model for oil pump unit on the basis of operating condition classification and recognition

Science.gov (United States)

Liang, Wei; Yu, Xuchao; Zhang, Laibin; Lu, Wenqing

2018-05-01

In oil transmission station, the operating condition (OC) of an oil pump unit sometimes switches accordingly, which will lead to changes in operating parameters. If not taking the switching of OCs into consideration while performing a state evaluation on the pump unit, the accuracy of evaluation would be largely influenced. Hence, in this paper, a self-organization Comprehensive Real-Time State Evaluation Model (self-organization CRTSEM) is proposed based on OC classification and recognition. However, the underlying model CRTSEM is built through incorporating the advantages of Gaussian Mixture Model (GMM) and Fuzzy Comprehensive Evaluation Model (FCEM) first. That is to say, independent state models are established for every state characteristic parameter according to their distribution types (i.e. the Gaussian distribution and logistic regression distribution). Meanwhile, Analytic Hierarchy Process (AHP) is utilized to calculate the weights of state characteristic parameters. Then, the OC classification is determined by the types of oil delivery tasks, and CRTSEMs of different standard OCs are built to constitute the CRTSEM matrix. On the other side, the OC recognition is realized by a self-organization model that is established on the basis of Back Propagation (BP) model. After the self-organization CRTSEM is derived through integration, real-time monitoring data can be inputted for OC recognition. At the end, the current state of the pump unit can be evaluated by using the right CRTSEM. The case study manifests that the proposed self-organization CRTSEM can provide reasonable and accurate state evaluation results for the pump unit. Besides, the assumption that the switching of OCs will influence the results of state evaluation is also verified.

IgE recognition of chimeric isoforms of the honeybee (Apis mellifera) venom allergen Api m 10 evaluated by protein array technology.

Science.gov (United States)

Van Vaerenbergh, Matthias; De Smet, Lina; Rafei-Shamsabadi, David; Blank, Simon; Spillner, Edzard; Ebo, Didier G; Devreese, Bart; Jakob, Thilo; de Graaf, Dirk C

2015-02-01

Api m 10 has recently been established as novel major allergen that is recognized by more than 60% of honeybee venom (HBV) allergic patients. Previous studies suggest Api m 10 protein heterogeneity which may have implications for diagnosis and immunotherapy of HBV allergy. In the present study, RT-PCR revealed the expression of at least nine additional Api m 10 transcript isoforms by the venom glands. Two distinct mechanisms are responsible for the generation of these isoforms: while the previously known variant 2 is produced by an alternative splicing event, novel identified isoforms are intragenic chimeric transcripts. To the best of our knowledge, this is the first report of the identification of chimeric transcripts generated by the honeybee. By a retrospective proteomic analysis we found evidence for the presence of several of these isoforms in the venom proteome. Additionally, we analyzed IgE reactivity to different isoforms by protein array technology using sera from HBV allergic patients, which revealed that IgE recognition of Api m 10 is both isoform- and patient-specific. While it was previously demonstrated that the majority of HBV allergic patients display IgE reactivity to variant 2, our study also shows that some patients lacking IgE antibodies for variant 2 display IgE reactivity to two of the novel identified Api m 10 variants, i.e. variants 3 and 4. Copyright © 2014 Elsevier Ltd. All rights reserved.

Probabilistic Open Set Recognition

Science.gov (United States)

Jain, Lalit Prithviraj

support vector machines. Building from the success of statistical EVT based recognition methods such as PI-SVM and W-SVM on the open set problem, we present a new general supervised learning algorithm for multi-class classification and multi-class open set recognition called the Extreme Value Local Basis (EVLB). The design of this algorithm is motivated by the observation that extrema from known negative class distributions are the closest negative points to any positive sample during training, and thus should be used to define the parameters of a probabilistic decision model. In the EVLB, the kernel distribution for each positive training sample is estimated via an EVT distribution fit over the distances to the separating hyperplane between positive training sample and closest negative samples, with a subset of the overall positive training data retained to form a probabilistic decision boundary. Using this subset as a frame of reference, the probability of a sample at test time decreases as it moves away from the positive class. Possessing this property, the EVLB is well-suited to open set recognition problems where samples from unknown or novel classes are encountered at test. Our experimental evaluation shows that the EVLB provides a substantial improvement in scalability compared to standard radial basis function kernel machines, as well as P I-SVM and W-SVM, with improved accuracy in many cases. We evaluate our algorithm on open set variations of the standard visual learning benchmarks, as well as with an open subset of classes from Caltech 256 and ImageNet. Our experiments show that PI-SVM, WSVM and EVLB provide significant advances over the previous state-of-the-art solutions for the same tasks.

Plastic surgery and the biometric e-passport: implications for facial recognition.

Science.gov (United States)

Ologunde, Rele

2015-04-01

This correspondence comments on the challenges of plastic reconstructive and aesthetic surgery on the facial recognition algorithms employed by biometric passports. The limitations of facial recognition technology in patients who have undergone facial plastic surgery are also discussed. Finally, the advice of the UK HM passport office to people who undergo facial surgery is reported.

An Approach to Object Recognition: Aligning Pictorial Descriptions.

Science.gov (United States)

1986-12-01

PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

Nanomechanical recognition of prognostic biomarker suPAR with DVD-ROM optical technology

International Nuclear Information System (INIS)

Bache, Michael; Bosco, Filippo G; Brøgger, Anna L; Frøhling, Kasper B; Boisen, Anja; Alstrøm, Tommy Sonne; Hwu, En-Te; Chen, Ching-Hsiu; Hwang, Ing-Shouh; Eugen-Olsen, Jesper

2013-01-01

In this work the use of a high-throughput nanomechanical detection system based on a DVD-ROM optical drive and cantilever sensors is presented for the detection of urokinase plasminogen activator receptor inflammatory biomarker (uPAR). Several large scale studies have linked elevated levels of soluble uPAR (suPAR) to infectious diseases, such as HIV, and certain types of cancer. Using hundreds of cantilevers and a DVD-based platform, cantilever deflection response from antibody–antigen recognition is investigated as a function of suPAR concentration. The goal is to provide a cheap and portable detection platform which can carry valuable prognostic information. In order to optimize the cantilever response the antibody immobilization and unspecific binding are initially characterized using quartz crystal microbalance technology. Also, the choice of antibody is explored in order to generate the largest surface stress on the cantilevers, thus increasing the signal. Using optimized experimental conditions the lowest detectable suPAR concentration is currently around 5 nM. The results reveal promising research strategies for the implementation of specific biochemical assays in a portable and high-throughput microsensor-based detection platform. (paper)

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Chen, H; Tan, J; Kavanaugh, J; Dolly, S; Gay, H; Thorstad, W; Anastasio, M; Altman, M; Mutic, S; Li, H [Washington University School of Medicine, Saint Louis, MO (United States)

2014-06-15

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding

The recognition heuristic: A decade of research

Directory of Open Access Journals (Sweden)

Gerd Gigerenzer

2011-02-01

Full Text Available The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein and Gigerenzer, 1999, 2002, including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.

Fine-grained recognition of plants from images.

Science.gov (United States)

Šulc, Milan; Matas, Jiří

2017-01-01

Fine-grained recognition of plants from images is a challenging computer vision task, due to the diverse appearance and complex structure of plants, high intra-class variability and small inter-class differences. We review the state-of-the-art and discuss plant recognition tasks, from identification of plants from specific plant organs to general plant recognition "in the wild". We propose texture analysis and deep learning methods for different plant recognition tasks. The methods are evaluated and compared them to the state-of-the-art. Texture analysis is only applied to images with unambiguous segmentation (bark and leaf recognition), whereas CNNs are only applied when sufficiently large datasets are available. The results provide an insight in the complexity of different plant recognition tasks. The proposed methods outperform the state-of-the-art in leaf and bark classification and achieve very competitive results in plant recognition "in the wild". The results suggest that recognition of segmented leaves is practically a solved problem, when high volumes of training data are available. The generality and higher capacity of state-of-the-art CNNs makes them suitable for plant recognition "in the wild" where the views on plant organs or plants vary significantly and the difficulty is increased by occlusions and background clutter.

HIGH VOLTAGE ENVIRONMENTAL APPLICATIONS, INC.ELECTRON BEAM TECHNOLOGY - INNOVATIVE TECHNOLOGY EVALUATION REPORT

Science.gov (United States)

This report evaluates a high-voltage electron beam (E-beam) technology's ability to destroy volatile organic compounds (VOCs) and other contaminants present in liquid wastes. Specifically, this report discusses performance and economic data from a Superfund Innovative Technology...

Invariant Face recognition Using Infrared Images

International Nuclear Information System (INIS)

Zahran, E.G.

2012-01-01

Over the past few decades, face recognition has become a rapidly growing research topic due to the increasing demands in many applications of our daily life such as airport surveillance, personal identification in law enforcement, surveillance systems, information safety, securing financial transactions, and computer security. The objective of this thesis is to develop a face recognition system capable of recognizing persons with a high recognition capability, low processing time, and under different illumination conditions, and different facial expressions. The thesis presents a study for the performance of the face recognition system using two techniques; the Principal Component Analysis (PCA), and the Zernike Moments (ZM). The performance of the recognition system is evaluated according to several aspects including the recognition rate, and the processing time. Face recognition systems that use visual images are sensitive to variations in the lighting conditions and facial expressions. The performance of these systems may be degraded under poor illumination conditions or for subjects of various skin colors. Several solutions have been proposed to overcome these limitations. One of these solutions is to work in the Infrared (IR) spectrum. IR images have been suggested as an alternative source of information for detection and recognition of faces, when there is little or no control over lighting conditions. This arises from the fact that these images are formed due to thermal emissions from skin, which is an intrinsic property because these emissions depend on the distribution of blood vessels under the skin. On the other hand IR face recognition systems still have limitations with temperature variations and recognition of persons wearing eye glasses. In this thesis we will fuse IR images with visible images to enhance the performance of face recognition systems. Images are fused using the wavelet transform. Simulation results show that the fusion of visible and

Use of societal criteria in evaluation of medical technology assessment research proposals in the Netherlands: Development and testing of a checklist

NARCIS (Netherlands)

Oortwijn, W.J.; Ament, A.J.H.A.; Vondeling, H.

1996-01-01

Rising health care costs, and the recognition that medical technology is a significant contributor to these costs, have provided the stimulus to develop medical technology assessment programmes in the Netherlands. The most important programme in this field is the Investigational Medicine Programme

New Technologies, New Approaches to Evaluating Academic Productivity

Science.gov (United States)

Rich, Peter J.; West, Richard E.

2012-01-01

Technology has enabled a proliferation of publication venues for disseminating academic work. The task of evaluating the relative quality of each of these venues is simultaneously exacerbated and resolved by the use of new technologies. In this article, the authors propose a three-pronged framework for evaluating the quality of scholarly work that…

On the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition

Directory of Open Access Journals (Sweden)

Marco Zennaro

2010-12-01

Full Text Available Achieving situation recognition in ubiquitous sensor networks (USNs is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

Health technology assessment. Evaluation of biomedical innovative technologies.

Science.gov (United States)

Turchetti, Giuseppe; Spadoni, Enza; Geisler, Eliezer Elie

2010-01-01

This article describes health technology assessment (HTA) as an evaluation tool that applies systematic methods of inquiry to the generation and use of health technologies and new products. The focus of this article is on the contributions of HTA to the management of the new product development effort in the biomedical organization. Critical success factors (CSFs) are listed, and their role in assessing success is defined and explained. One of the conclusions of this article is that HTA is a powerful tool for managers in the biomedical sector, allowing them to better manage their innovation effort in their continuing struggle for competitiveness and survival.

Superpixel-Based Feature for Aerial Image Scene Recognition

Directory of Open Access Journals (Sweden)

Hongguang Li

2018-01-01

Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

Research of Obstacle Recognition Technology in Cross-Country Environment for Unmanned Ground Vehicle

Directory of Open Access Journals (Sweden)

Zhao Yibing

2014-01-01

Full Text Available Being aimed at the obstacle recognition problem of unmanned ground vehicles in cross-country environment, this paper uses monocular vision sensor to realize the obstacle recognition of typical obstacles. Firstly, median filtering algorithm is applied during image preprocessing that can eliminate the noise. Secondly, image segmentation method based on the Fisher criterion function is used to segment the region of interest. Then, morphological method is used to process the segmented image, which is preparing for the subsequent analysis. The next step is to extract the color feature S, color feature a and edge feature “verticality” of image are extracted based on the HSI color space, the Lab color space, and two value images. Finally multifeature fusion algorithm based on Bayes classification theory is used for obstacle recognition. Test results show that the algorithm has good robustness and accuracy.

Emotion recognition a pattern analysis approach

CERN Document Server

Konar, Amit

2014-01-01

Offers both foundations and advances on emotion recognition in a single volumeProvides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domainsInspires young researchers to prepare themselves for their own researchDemonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.

Stereo vision with distance and gradient recognition

Science.gov (United States)

Kim, Soo-Hyun; Kang, Suk-Bum; Yang, Tae-Kyu

2007-12-01

Robot vision technology is needed for the stable walking, object recognition and the movement to the target spot. By some sensors which use infrared rays and ultrasonic, robot can overcome the urgent state or dangerous time. But stereo vision of three dimensional space would make robot have powerful artificial intelligence. In this paper we consider about the stereo vision for stable and correct movement of a biped robot. When a robot confront with an inclination plane or steps, particular algorithms are needed to go on without failure. This study developed the recognition algorithm of distance and gradient of environment by stereo matching process.

Optical Character Recognition.

Science.gov (United States)

Converso, L.; Hocek, S.

1990-01-01

This paper describes computer-based optical character recognition (OCR) systems, focusing on their components (the computer, the scanner, the OCR, and the output device); how the systems work; and features to consider in selecting a system. A list of 26 questions to ask to evaluate systems for potential purchase is included. (JDD)

Evaluation of the research diagnostic criteria for temporomandibular disorders for the recognition of an anterior disc displacement with reduction

NARCIS (Netherlands)

Naeije, M.; Kalaykova, S.; Visscher, C.M.; Lobbezoo, F.

2009-01-01

The aim of this Focus Article is to review critically the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) for the recognition of an anterior disc displacement with reduction (ADDR) in the temporomandibular joint (TMJ). This evaluation is based upon the experience gained

Recognition, evaluation, and control of indoor air pollution

International Nuclear Information System (INIS)

Chastain, B.

1993-01-01

Indoor air pollution is typically associated with terms sick building syndrome, tight building syndrome, building related illness, and problem building. Indoor air pollution is a relatively new public health concern (approximately 15 years old) although this issue is an age-old problem dating back to prehistoric times when humans came to live indoors. This presentation summarizes indoor air quality issues in order to provide you with usable information concerning the recognition and evaluation of indoor air quality (IAQ) problems and the subsequent control measures which can be used for maintaining or improving the indoor air environment for better occupant health and comfort control. Why has the subject become so vocalized in the last fifteen years? Why the sudden interest and awareness concerning indoor air quality issues? During the last half of the 1970's and all of the 1980's, buildings were built or remodeled to minimize air handling, heating, and cooling costs, often limiting the amount of outside air brought into the buildings to near minimums. Paralleling these developments, complaints related to modern buildings increased. The new terms tight building syndrome, sick building syndrome, and indoor air quality became widely used by health and safety professionals and subsequently by newspaper columnist and the general public

Hybrid methodological approach to context-dependent speech recognition

Directory of Open Access Journals (Sweden)

Dragiša Mišković

2017-01-01

Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

1992 update of US EPA's Superfund Innovative Technology Evaluation (SITE) Emerging Technology Program

International Nuclear Information System (INIS)

Lewis, N.M.; Barkley, N.P.; Williams, T.

1992-01-01

The Superfund Innovative Technology Evaluation (SITE) Emerging Technology Program (ETP) has financially supported further development of bench- and pilot-scale testing and evaluation of innovative technologies for use at hazardous waste sites for five years. The ETP was established under the Superfund Amendments and Reauthorization Act (SARA) of 1986. The ETP complies with the goal of the SITE Program to promote, accelerate and make commercially available the development of alternative/innovative treatment technologies for use at Superfund sites. Technologies are submitted to the ETP through yearly solicitations for Preproposals. Applicants are asked to submit a detailed project proposal and a cooperative agreement application that requires Developer/EPA cost sharing. EPA co-funds selected Developers for one to two years. Second-year funding requires documentation of significant progress during the first year. Facilities, equipment, data collection, performance and development are monitored throughout the project. The US Department of Energy (DOE) and the US Air Force (USAF) are participants in the ETP. DOE has co-funded ETP projects since 1990 and the USAF since 1991. A goal of the ETP is to move developed technologies to the field-demonstration stage. A developer may be considered for participation in the SITE Demonstration Program if performance in the ETP indicates the technology is field-ready for evaluation. Six technology categories: biological, chemical, materials handling, physical, solidification/stabilization and thermal, are presently in the ETP. Technologies of primary interest to EPA are those that can treat complex mixtures of hazardous organic and inorganic contaminants and provide improved solids handling and/or pretreatment. An account of the background and progress of the ETP's first five years is presented in this paper. Technologies currently in the ETP are noted, and developers and EPA Project Managers, are listed. 4 refs., 11 figs., 6 tabs

Memory evaluation in mild cognitive impairment using recall and recognition tests

OpenAIRE

Bennett, IJ; Golob, EJ; Parker, ES; Starr, A

2006-01-01

Amnestic mild cognitive impairment (MCI) is a selective episodic memory deficit that often indicates early Alzheimer's disease. Episodic memory function in MCI is typically defined by deficits in free recall, but can also be tested using recognition procedures. To assess both recall and recognition in MCI, MCI (n = 21) and older comparison (n = 30) groups completed the USC-Repeatable Episodic Memory Test. Subjects memorized two verbally presented 15-item lists. One list was used for three fre...

Human motion sensing and recognition a fuzzy qualitative approach

CERN Document Server

Liu, Honghai; Ji, Xiaofei; Chan, Chee Seng; Khoury, Mehdi

2017-01-01

This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the ...

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

Application of Kinect Technology in Blind Aerobics Learning

Directory of Open Access Journals (Sweden)

Hui Qu

2017-12-01

Full Text Available In order for blind people to learn aerobics more conveniently, we combined Kinect skeletal tracking technology with aerobics-assisted training to design a Kinect-based aerobics-assisted training system. Through the Kinect somatosensory camera, the feature extraction method and recognition algorithm of sign language are improved, and the sign language recognition system is realized. Sign language is translated through the sign language recognition system and expressed in understandable terms, providing a sound way of learning. The experimental results show that the system can automatically collect and recognize the aerobics movements. By comparing with the standard movements in the database, the system evaluates the posture of trainers from the perspectives of joint coordinates and joint angles, followed by the provision of movements contrast graphics and corresponding advice. Therefore, the system can effectively help the blind to learn aerobics.

REMEDIATION TECHNOLOGY EVALUATION AT THE GILT EDGE MINE, SOUTH DAKOTA

Science.gov (United States)

This document reports the findings of the Mine Waste Technology Program's Activity III, Project 29,The Remediation Technology Evaluation Project at the Gilt Edge Mine, S.D. This project consisted of evaluating three emerging acidic waste rock stabilization technologies and compar...

[Measuring impairment of facial affects recognition in schizophrenia. Preliminary study of the facial emotions recognition task (TREF)].

Science.gov (United States)

Gaudelus, B; Virgile, J; Peyroux, E; Leleu, A; Baudouin, J-Y; Franck, N

2015-06-01

The impairment of social cognition, including facial affects recognition, is a well-established trait in schizophrenia, and specific cognitive remediation programs focusing on facial affects recognition have been developed by different teams worldwide. However, even though social cognitive impairments have been confirmed, previous studies have also shown heterogeneity of the results between different subjects. Therefore, assessment of personal abilities should be measured individually before proposing such programs. Most research teams apply tasks based on facial affects recognition by Ekman et al. or Gur et al. However, these tasks are not easily applicable in a clinical exercise. Here, we present the Facial Emotions Recognition Test (TREF), which is designed to identify facial affects recognition impairments in a clinical practice. The test is composed of 54 photos and evaluates abilities in the recognition of six universal emotions (joy, anger, sadness, fear, disgust and contempt). Each of these emotions is represented with colored photos of 4 different models (two men and two women) at nine intensity levels from 20 to 100%. Each photo is presented during 10 seconds; no time limit for responding is applied. The present study compared the scores of the TREF test in a sample of healthy controls (64 subjects) and people with stabilized schizophrenia (45 subjects) according to the DSM IV-TR criteria. We analysed global scores for all emotions, as well as sub scores for each emotion between these two groups, taking into account gender differences. Our results were coherent with previous findings. Applying TREF, we confirmed an impairment in facial affects recognition in schizophrenia by showing significant differences between the two groups in their global results (76.45% for healthy controls versus 61.28% for people with schizophrenia), as well as in sub scores for each emotion except for joy. Scores for women were significantly higher than for men in the population

Human activity recognition from wireless sensor network data: benchmark and software

NARCIS (Netherlands)

van Kasteren, T.L.M.; Englebienne, G.; Kröse, B.J.A.; Chen, L.; Nugent, C.; Biswas, J.; Hoey, J.

2011-01-01

Although activity recognition is an active area of research no common benchmark for evaluating the performance of activity recognition methods exists. In this chapter we present the state of the art probabilistic models used in activity recognition and show their performance on several real world

Extraction and fusion of spectral parameters for face recognition

Science.gov (United States)

Boisier, B.; Billiot, B.; Abdessalem, Z.; Gouton, P.; Hardeberg, J. Y.

2011-03-01

Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately in order to extract the most appropriate information for face recognition. We also verify the consistency of several keypoints extraction techniques in the Near Infrared (NIR) and in the Visible Spectrum.

Contribution to automatic image recognition. Application to analysis of plain scenes of overlapping parts in robot technology

International Nuclear Information System (INIS)

Tan, Shengbiao

1987-01-01

A method for object modeling and overlapped object automatic recognition is presented. Our work is composed of three essential parts: image processing, object modeling, and evaluation of the implementation of the stated concepts. In the first part, we present a method of edge encoding which is based on a re-sampling of the data encoded according to Freeman, this method generates an isotropic, homogenous and very precise representation. The second part relates to object modeling. This important step makes much easier the recognition work. The new method proposed characterizes a model with two groups of information: the description group containing the primitives, the discrimination group containing data packs, called 'transition vectors'. Based on this original method of information organization, a 'relative learning' is able to select, to ignore and to update the information concerning the objects already learned, according to the new information to be included into the data base. The recognition is a two-pass process: the first pass determines very efficiently the presence of objects by making use of each object's particularities, and this hypothesis is either confirmed or rejected by the following fine verification pass. The last part describes in detail the experimentation results. We demonstrate the robustness of the algorithms with images in both poor lighting and overlapping objects conditions. The system, named SOFIA, has been installed into an industrial vision system series and works in real time. (author) [fr

Transnational Geographies of Academic Distinction: The Role of Social Capital in the Recognition and Evaluation of "Overseas" Credentials

Science.gov (United States)

Waters, Johanna L.

2009-01-01

This paper examines the role of specific and place-based social capital in the recognition and evaluation of international credentials. Whilst research on labour market segmentation has contributed towards an understanding of the spatial variability of the value of human capital, very little attention has been paid to the ways in which the…

Automatic speech recognition (ASR) based approach for speech therapy of aphasic patients: A review

Science.gov (United States)

Jamal, Norezmi; Shanta, Shahnoor; Mahmud, Farhanahani; Sha'abani, MNAH

2017-09-01

This paper reviews the state-of-the-art an automatic speech recognition (ASR) based approach for speech therapy of aphasic patients. Aphasia is a condition in which the affected person suffers from speech and language disorder resulting from a stroke or brain injury. Since there is a growing body of evidence indicating the possibility of improving the symptoms at an early stage, ASR based solutions are increasingly being researched for speech and language therapy. ASR is a technology that transfers human speech into transcript text by matching with the system's library. This is particularly useful in speech rehabilitation therapies as they provide accurate, real-time evaluation for speech input from an individual with speech disorder. ASR based approaches for speech therapy recognize the speech input from the aphasic patient and provide real-time feedback response to their mistakes. However, the accuracy of ASR is dependent on many factors such as, phoneme recognition, speech continuity, speaker and environmental differences as well as our depth of knowledge on human language understanding. Hence, the review examines recent development of ASR technologies and its performance for individuals with speech and language disorders.

Initial evaluation of an interactive test of sentence gist recognition.

Science.gov (United States)

Tye-Murray, N; Witt, S; Castelloe, J

1996-12-01

The laser videodisc-based Sentence Gist Recognition (SGR) test consists of sets of topically related sentences that are cued by short film clips. Clients respond to test items by selecting picture illustrations and may interact with the talker by using repair strategies when they do not recognize a test item. The two experiments, involving 40 and 35 adult subjects, respectively, indicated that the SGR may better predict subjective measures of speechreading and listening performance than more traditional audiologic sentence and nonsense syllable tests. Data from cochlear implant users indicated that the SGR accounted for a greater percentage of the variance for selected items of the Communication Profile for the Hearing-Impaired and the Speechreading Questionnaire for Cochlear-Implant Users than two other audiologic tests. As in previous work, subjects were most apt to ask the talker to repeat an utterance that they did not recognize than to ask the talker to restructure it. It is suggested that the SGR may reflect the interactive nature of conversation and provide a simulated real-world listening and/or speechreading task. The principles underlaying this test are consistent with the development of other computer technologies and concepts, such as compact discinteractive and virtual reality.

[Decision modeling for economic evaluation of health technologies].

Science.gov (United States)

de Soárez, Patrícia Coelho; Soares, Marta Oliveira; Novaes, Hillegonda Maria Dutilh

2014-10-01

Most economic evaluations that participate in decision-making processes for incorporation and financing of technologies of health systems use decision models to assess the costs and benefits of the compared strategies. Despite the large number of economic evaluations conducted in Brazil, there is a pressing need to conduct an in-depth methodological study of the types of decision models and their applicability in our setting. The objective of this literature review is to contribute to the knowledge and use of decision models in the national context of economic evaluations of health technologies. This article presents general definitions about models and concerns with their use; it describes the main models: decision trees, Markov chains, micro-simulation, simulation of discrete and dynamic events; it discusses the elements involved in the choice of model; and exemplifies the models addressed in national economic evaluation studies of diagnostic and therapeutic preventive technologies and health programs.

SANDIA NATIONAL LABORATORIES IN SITU ELECTROKINETIC EXTRACTION TECHNOLOGY; INNOVATIVE TECHNOLOGY EVALUATION REPORT

Science.gov (United States)

As a part of the Superfund Innovative Technology Evaluation (SITE) Program, the U.S. Environmental Protection Agency evaluated the In-Situ Electrokinetic Extraction (ISEE) system at Sandia National Laboratories, Albuquerque, New Mexico.The SITE demonstration results show ...

A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.

Science.gov (United States)

Biondich, Paul G; Overhage, J Marc; Dexter, Paul R; Downs, Stephen M; Lemmon, Larry; McDonald, Clement J

2002-01-01

Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data.

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

An Embedded Application for Degraded Text Recognition

Directory of Open Access Journals (Sweden)

Thillou Céline

2005-01-01

Full Text Available This paper describes a mobile device which tries to give the blind or visually impaired access to text information. Three key technologies are required for this system: text detection, optical character recognition, and speech synthesis. Blind users and the mobile environment imply two strong constraints. First, pictures will be taken without control on camera settings and a priori information on text (font or size and background. The second issue is to link several techniques together with an optimal compromise between computational constraints and recognition efficiency. We will present the overall description of the system from text detection to OCR error correction.

Aggregating Local Descriptors for Epigraphs Recognition

OpenAIRE

Amato, Giuseppe; Falchi, Fabrizio; Rabitti, Fausto; Vadicamo, Lucia

2014-01-01

In this paper, we consider the task of recognizing epigraphs in images such as photos taken using mobile devices. Given a set of 17,155 photos related to 14,560 epigraphs, we used a k-NearestNeighbor approach in order to perform the recognition. The contribution of this work is in evaluating state-of-the-art visual object recognition techniques in this specific context. The experimental results conducted show that Vector of Locally Aggregated Descriptors obtained aggregating SIFT descriptors ...

Technologies in Computerized Lexicography

African Journals Online (AJOL)

guage technology, information technology and knowledge engineering, may .... character recognition (OCR) with computer-aided correction (Kruyt and Van ..... encoded for headword and part of speech by linguistic software developed at.

Impaired emotion recognition in music in Parkinson's disease.

Science.gov (United States)

van Tricht, Mirjam J; Smeding, Harriet M M; Speelman, Johannes D; Schmand, Ben A

2010-10-01

Music has the potential to evoke strong emotions and plays a significant role in the lives of many people. Music might therefore be an ideal medium to assess emotion recognition. We investigated emotion recognition in music in 20 patients with idiopathic Parkinson's disease (PD) and 20 matched healthy volunteers. The role of cognitive dysfunction and other disease characteristics in emotion recognition was also evaluated. We used 32 musical excerpts that expressed happiness, sadness, fear or anger. PD patients were impaired in recognizing fear and anger in music. Fear recognition was associated with executive functions in PD patients and in healthy controls, but the emotion recognition impairments of PD patients persisted after adjusting for executive functioning. We found no differences in the recognition of happy or sad music. Emotion recognition was not related to depressive symptoms, disease duration or severity of motor symptoms. We conclude that PD patients are impaired in recognizing complex emotions in music. Although this impairment is related to executive dysfunction, our findings most likely reflect an additional primary deficit in emotional processing. 2010 Elsevier Inc. All rights reserved.

Evaluation of User Acceptance of Mixed Reality Technology

Science.gov (United States)

Yusoff, Rasimah Che Mohd; Zaman, Halimah Badioze; Ahmad, Azlina

2011-01-01

This study investigates users' perception and acceptance of mixed reality (MR) technology. Acceptance of new information technologies has been important research area since 1990s. It is important to understand the reasons why people accept information technologies, as this can help to improve design, evaluation and prediction how users will…

The Suitability of Cloud-Based Speech Recognition Engines for Language Learning

Science.gov (United States)

Daniels, Paul; Iwago, Koji

2017-01-01

As online automatic speech recognition (ASR) engines become more accurate and more widely implemented with call software, it becomes important to evaluate the effectiveness and the accuracy of these recognition engines using authentic speech samples. This study investigates two of the most prominent cloud-based speech recognition engines--Apple's…

PROMOTING EQUALITY THROUGH ASSISTIVE TECHNOLOGIES, A SOCIOECONOMIC PERSPECTIVE

Directory of Open Access Journals (Sweden)

Ana-Maria NEAGU

2015-04-01

Full Text Available The aim of the proposed paper is to identify a possible cost benefit evaluation of assistive technologies in the context of promoting equal opportunities in life. Equal opportunities represent more than just ensuring an equitable framework for all individuals; equality represents recognition and respect for all individuals no matter the differences among us. The paper debates the issues of equality in the context of assistive technologies advance. The use of assistive technology was found to be predictive of enjoyment of human rights and increased capabilities for those with special needs. Because promoting equality among individuals necessitates more than doing nothing it is obvious that we should think of evaluating the costs and the benefits of such actions taking into consideration socio and economic aspects. The topic has a novelty and an applicability character mostly for our country.

On speech recognition during anaesthesia

DEFF Research Database (Denmark)

Alapetite, Alexandre

2007-01-01

This PhD thesis in human-computer interfaces (informatics) studies the case of the anaesthesia record used during medical operations and the possibility to supplement it with speech recognition facilities. Problems and limitations have been identified with the traditional paper-based anaesthesia...... and inaccuracies in the anaesthesia record. Supplementing the electronic anaesthesia record interface with speech input facilities is proposed as one possible solution to a part of the problem. The testing of the various hypotheses has involved the development of a prototype of an electronic anaesthesia record...... interface with speech input facilities in Danish. The evaluation of the new interface was carried out in a full-scale anaesthesia simulator. This has been complemented by laboratory experiments on several aspects of speech recognition for this type of use, e.g. the effects of noise on speech recognition...

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

Science.gov (United States)

James, Alex Pappachen; Fedorova, Irina; Ibrayev, Timur; Kudithipudi, Dhireesha

2017-06-01

Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and temporal memory. In this work, we propose a new Spatial Pooler circuit design with parallel memristive crossbar arrays for the 2D columns. The proposed design was validated on two different benchmark datasets, face recognition, and speech recognition. The circuits are simulated and analyzed using a practical memristor device model and 0.18 μm IBM CMOS technology model. The databases AR, YALE, ORL, and UFI, are used to test the performance of the design in face recognition. TIMIT dataset is used for the speech recognition.

Face recognition using slow feature analysis and contourlet transform

Science.gov (United States)

Wang, Yuehao; Peng, Lingling; Zhe, Fuchuan

2018-04-01

In this paper we propose a novel face recognition approach based on slow feature analysis (SFA) in contourlet transform domain. This method firstly use contourlet transform to decompose the face image into low frequency and high frequency part, and then takes technological advantages of slow feature analysis for facial feature extraction. We named the new method combining the slow feature analysis and contourlet transform as CT-SFA. The experimental results on international standard face database demonstrate that the new face recognition method is effective and competitive.

Utilising digital technology for dialogue and evaluation

DEFF Research Database (Denmark)

Kjærgaard, Thomas

2016-01-01

This article investigates how digital technology can enhance evaluation and eflection through dialogue in a theory lesson in the context of university college teaching. The pedagogical designs in the article vary from synchronous classroom evaluation on smartphones, to online discussion fora...

Utilising digital technology for dialogue and evaluation

DEFF Research Database (Denmark)

Kjærgaard, Thomas

2016-01-01

This article investigates how digital technology can enhance evaluation and reflection through dialogue in a theory lesson in the context of university college teaching. The pedagogical designs in the article vary from synchronous classroom evaluation on smartphones, to online discussion fora...

TEXACO GASIFICATION PROCESS - INNOVATIVE TECHNOLOGY EVALUATION REPORT

Science.gov (United States)

This report summarizes the evaluation of the Texaco Gasification Process (TGP) conducted under the U.S. Environmental Protection Agency (EPA) Superfund Innovative Technology Evaluation (SITE) Program. The Texaco Gasification Process was developed by Texaco Inc. The TGP is a comm...

Quality based approach for adaptive face recognition

Science.gov (United States)

Abboud, Ali J.; Sellahewa, Harin; Jassim, Sabah A.

2009-05-01

Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary restore image quality according to the need of the intended application. In this paper, we present no-reference image quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance of adaptive face recognition system over the corresponding non-adaptive scheme.

Efficient Interaction Recognition through Positive Action Representation

Directory of Open Access Journals (Sweden)

Tao Hu

2013-01-01

Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.

A Study of KHNP Nuclear Power Plant Technology Level Evaluation

International Nuclear Information System (INIS)

Yang, Seung Han; Lee, Sung Jin; Kim, Yo Han

2016-01-01

KHNP's 2030 mid and long term plan goal in technology field is securing global No. 1 NPP technology level. Quantifying technology level for this purpose, technology level at present should be surveyed. Technology level of South Korea has been surveyed by KISTEP (Korea Institute of S and T Evaluation and Planning) every two year but the technology level of KHNP has not been surveyed by any organization including KHNP itself. Also the size of technology surveyed by KISTEP was too broad to quantifying technology level of KHNP. In this paper, technology level of KHNP and South Korea are presented. In this study, NPP related technologies were divided into Level I and Level II technologies and conducted a survey for each Level II technologies using Delphi questionnaire survey that is widely used in technology level evaluation. The results of technology level and gap will be used from strategic point of view and also as a reference data for technology improvement planning

A Study of KHNP Nuclear Power Plant Technology Level Evaluation

Energy Technology Data Exchange (ETDEWEB)

Yang, Seung Han; Lee, Sung Jin; Kim, Yo Han [KHNP, Daejeon (Korea, Republic of)

2016-05-15

KHNP's 2030 mid and long term plan goal in technology field is securing global No. 1 NPP technology level. Quantifying technology level for this purpose, technology level at present should be surveyed. Technology level of South Korea has been surveyed by KISTEP (Korea Institute of S and T Evaluation and Planning) every two year but the technology level of KHNP has not been surveyed by any organization including KHNP itself. Also the size of technology surveyed by KISTEP was too broad to quantifying technology level of KHNP. In this paper, technology level of KHNP and South Korea are presented. In this study, NPP related technologies were divided into Level I and Level II technologies and conducted a survey for each Level II technologies using Delphi questionnaire survey that is widely used in technology level evaluation. The results of technology level and gap will be used from strategic point of view and also as a reference data for technology improvement planning.

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Directory of Open Access Journals (Sweden)

Muhammad Hameed Siddiqi

2013-12-01

Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

Science.gov (United States)

Siddiqi, Muhammad Hameed; Lee, Sungyoung; Lee, Young-Koo; Khan, Adil Mehmood; Truc, Phan Tran Ho

2013-01-01

Over the last decade, human facial expressions recognition (FER) has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER) system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER. PMID:24316568

Virtualized Network Function Orchestration System and Experimental Network Based QR Recognition for a 5G Mobile Access Network

Directory of Open Access Journals (Sweden)

Misun Ahn

2017-12-01

Full Text Available This paper proposes a virtualized network function orchestration system based on Network Function Virtualization (NFV, one of the main technologies in 5G mobile networks. This system should provide connectivity between network devices and be able to create flexible network function and distribution. This system focuses more on access networks. By experimenting with various scenarios of user service established and activated in a network, we examine whether rapid adoption of new service is possible and whether network resources can be managed efficiently. The proposed method is based on Bluetooth transfer technology and mesh networking to provide automatic connections between network machines and on a Docker flat form, which is a container virtualization technology for setting and managing key functions. Additionally, the system includes a clustering and recovery measure regarding network function based on the Docker platform. We will briefly introduce the QR code perceived service as a user service to examine the proposal and based on this given service, we evaluate the function of the proposal and present analysis. Through the proposed approach, container relocation has been implemented according to a network device’s CPU usage and we confirm successful service through function evaluation on a real test bed. We estimate QR code recognition speed as the amount of network equipment is gradually increased, improving user service and confirm that the speed of recognition is increased as the assigned number of network devices is increased by the user service.

Gabor Weber Local Descriptor for Bovine Iris Recognition

Directory of Open Access Journals (Sweden)

Shengnan Sun

2013-01-01

Full Text Available Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD. We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersection is adopted to measure the similarity between different GWLD histograms. The experimental results on the SEU bovine iris database verify the representation power of our proposed local descriptor.

Dazzles, decoys, and deities : the Janus face of anti-facial recognition masks

NARCIS (Netherlands)

de Vries, P.B.

2017-01-01

Over the past few years a growing number of artists have critiqued the ubiquity of identity recognition technologies. Specifically, the use of these technologies by state security programs, tech-giants and multinational corporations has met with opposition and controversy. A popular form of

Enhancing emotion recognition in VIPs with haptic feedback

NARCIS (Netherlands)

Buimer, Hendrik; Bittner, Marian; Kostelijk, Tjerk; van der Geest, Thea; van Wezel, Richard Jack Anton; Zhao, Yan; Stephanidis, Constantine

2016-01-01

The rise of smart technologies has created new opportunities to support blind and visually impaired persons (VIPs). One of the biggest problems we identified in our previous research on problems VIPs face during activities of daily life concerned the recognition of persons and their facial

Let Me Relax: Toward Automated Sedentary State Recognition and Ubiquitous Mental Wellness Solutions

Directory of Open Access Journals (Sweden)

Vijay Rajanna

2018-12-01

Full Text Available Advances in ubiquitous computing technology improve workplace productivity, reduce physical exertion, but ultimately result in a sedentary work style. Sedentary behavior is associated with an increased risk of stress, obesity, and other health complications. Let Me Relax is a fully automated sedentary-state recognition framework using a smartwatch and smartphone, which encourages mental wellness through interventions in the form of simple relaxation techniques. The system was evaluated through a comparative user study of 22 participants split into a test and a control group. An analysis of NASA Task Load Index pre- and post- study survey revealed that test subjects who followed relaxation methods, showed a trend of both increased activity as well as reduced mental stress. Reduced mental stress was found even in those test subjects that had increased inactivity. These results suggest that repeated interventions, driven by an intelligent activity recognition system, is an effective strategy for promoting healthy habits, which reduce stress, anxiety, and other health risks associated with sedentary workplaces.

A Survey on Banknote Recognition Methods by Various Sensors

Science.gov (United States)

Lee, Ji Woo; Hong, Hyung Gil; Kim, Ki Wan; Park, Kang Ryoung

2017-01-01

Despite a decrease in the use of currency due to the recent growth in the use of electronic financial transactions, real money transactions remain very important in the global market. While performing transactions with real money, touching and counting notes by hand, is still a common practice in daily life, various types of automated machines, such as ATMs and banknote counters, are essential for large-scale and safe transactions. This paper presents studies that have been conducted in four major areas of research (banknote recognition, counterfeit banknote detection, serial number recognition, and fitness classification) in the accurate banknote recognition field by various sensors in such automated machines, and describes the advantages and drawbacks of the methods presented in those studies. While to a limited extent some surveys have been presented in previous studies in the areas of banknote recognition or counterfeit banknote recognition, this paper is the first of its kind to review all four areas. Techniques used in each of the four areas recognize banknote information (denomination, serial number, authenticity, and physical condition) based on image or sensor data, and are actually applied to banknote processing machines across the world. This study also describes the technological challenges faced by such banknote recognition techniques and presents future directions of research to overcome them. PMID:28208733

Black Ink and Red Ink (BIRI) Testing: A Testing Method to Evaluate Both Recall and Recognition Learning in Accelerated Adult-Learning Courses

Science.gov (United States)

Rodgers, Joseph Lee; Rodgers, Jacci L.

2011-01-01

We propose, develop, and evaluate the black ink-red ink (BIRI) method of testing. This approach uses two different methods within the same test administration setting, one that matches recognition learning and the other that matches recall learning. Students purposively define their own tradeoff between the two approaches. Evaluation of the method…

Methane mitigation timelines to inform energy technology evaluation

Science.gov (United States)

Roy, Mandira; Edwards, Morgan R.; Trancik, Jessika E.

2015-11-01

Energy technologies emitting differing proportions of methane (CH4) and carbon dioxide (CO2) vary significantly in their relative climate impacts over time, due to the distinct atmospheric lifetimes and radiative efficiencies of the two gases. Standard technology comparisons using the global warming potential (GWP) with a fixed time horizon do not account for the timing of emissions in relation to climate policy goals. Here we develop a portfolio optimization model that incorporates changes in technology impacts based on the temporal proximity of emissions to a radiative forcing (RF) stabilization target. An optimal portfolio, maximizing allowed energy consumption while meeting the RF target, is obtained by year-wise minimization of the marginal RF impact in an intended stabilization year. The optimal portfolio calls for using certain higher-CH4-emitting technologies prior to an optimal switching year, followed by CH4-light technologies as the stabilization year approaches. We apply the model to evaluate transportation technology pairs and find that accounting for dynamic emissions impacts, in place of using the static GWP, can result in CH4 mitigation timelines and technology transitions that allow for significantly greater energy consumption while meeting a climate policy target. The results can inform the forward-looking evaluation of energy technologies by engineers, private investors, and policy makers.

Methane mitigation timelines to inform energy technology evaluation

International Nuclear Information System (INIS)

Roy, Mandira; Edwards, Morgan R; Trancik, Jessika E

2015-01-01

Energy technologies emitting differing proportions of methane (CH 4 ) and carbon dioxide (CO 2 ) vary significantly in their relative climate impacts over time, due to the distinct atmospheric lifetimes and radiative efficiencies of the two gases. Standard technology comparisons using the global warming potential (GWP) with a fixed time horizon do not account for the timing of emissions in relation to climate policy goals. Here we develop a portfolio optimization model that incorporates changes in technology impacts based on the temporal proximity of emissions to a radiative forcing (RF) stabilization target. An optimal portfolio, maximizing allowed energy consumption while meeting the RF target, is obtained by year-wise minimization of the marginal RF impact in an intended stabilization year. The optimal portfolio calls for using certain higher-CH 4 -emitting technologies prior to an optimal switching year, followed by CH 4 -light technologies as the stabilization year approaches. We apply the model to evaluate transportation technology pairs and find that accounting for dynamic emissions impacts, in place of using the static GWP, can result in CH 4 mitigation timelines and technology transitions that allow for significantly greater energy consumption while meeting a climate policy target. The results can inform the forward-looking evaluation of energy technologies by engineers, private investors, and policy makers. (letter)

Local Feature Learning for Face Recognition under Varying Poses

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a local feature learning method for face recognition to deal with varying poses. As opposed to the commonly used approaches of recovering frontal face images from profile views, the proposed method extracts the subject related part from a local feature by removing the pose...... related part in it on the basis of a pose feature. The method has a closed-form solution, hence being time efficient. For performance evaluation, cross pose face recognition experiments are conducted on two public face recognition databases FERET and FEI. The proposed method shows a significant...... recognition improvement under varying poses over general local feature approaches and outperforms or is comparable with related state-of-the-art pose invariant face recognition approaches. Copyright ©2015 by IEEE....

Effects of compression and individual variability on face recognition performance

Science.gov (United States)

McGarry, Delia P.; Arndt, Craig M.; McCabe, Steven A.; D'Amato, Donald P.

2004-08-01

The Enhanced Border Security and Visa Entry Reform Act of 2002 requires that the Visa Waiver Program be available only to countries that have a program to issue to their nationals machine-readable passports incorporating biometric identifiers complying with applicable standards established by the International Civil Aviation Organization (ICAO). In June 2002, the New Technologies Working Group of ICAO unanimously endorsed the use of face recognition (FR) as the globally interoperable biometric for machine-assisted identity confirmation with machine-readable travel documents (MRTDs), although Member States may elect to use fingerprint and/or iris recognition as additional biometric technologies. The means and formats are still being developed through which biometric information might be stored in the constrained space of integrated circuit chips embedded within travel documents. Such information will be stored in an open, yet unalterable and very compact format, probably as digitally signed and efficiently compressed images. The objective of this research is to characterize the many factors that affect FR system performance with respect to the legislated mandates concerning FR. A photograph acquisition environment and a commercial face recognition system have been installed at Mitretek, and over 1,400 images have been collected of volunteers. The image database and FR system are being used to analyze the effects of lossy image compression, individual differences, such as eyeglasses and facial hair, and the acquisition environment on FR system performance. Images are compressed by varying ratios using JPEG2000 to determine the trade-off points between recognition accuracy and compression ratio. The various acquisition factors that contribute to differences in FR system performance among individuals are also being measured. The results of this study will be used to refine and test efficient face image interchange standards that ensure highly accurate recognition, both

Evaluation of innovative arsenic treatment technologies :the arsenic water technology partnership vendors forums summary report.

Energy Technology Data Exchange (ETDEWEB)

Everett, Randy L.; Siegel, Malcolm Dean; McConnell, Paul E.; Kirby, Carolyn (Comforce Technical Services, Inc.)

2006-09-01

The lowering of the drinking water standard (MCL) for arsenic from 50 {micro}g/L to 10 {micro}g/L in January 2006 could lead to significant increases in the cost of water for many rural systems throughout the United States. The Arsenic Water Technology Partnership (AWTP), a collaborative effort of Sandia National Laboratories, the Awwa Research Foundation (AwwaRF) and WERC: A Consortium for Environmental Education and Technology Development, was formed to address this problem by developing and testing novel treatment technologies that could potentially reduce the costs of arsenic treatment. As a member of the AWTP, Sandia National Laboratories evaluated cutting-edge commercial products in three annual Arsenic Treatment Technology Vendors Forums held during the annual New Mexico Environmental Health Conferences (NMEHC) in 2003, 2004 and 2005. The Forums were comprised of two parts. At the first session, open to all conference attendees, commercial developers of innovative treatment technologies gave 15-minute talks that described project histories demonstrating the effectiveness of their products. During the second part, these same technologies were evaluated and ranked in closed sessions by independent technical experts for possible use in pilot-scale field demonstrations being conducted by Sandia National Laboratories. The results of the evaluations including numerical rankings of the products, links to company websites and copies of presentations made by the representatives of the companies are posted on the project website at http://www.sandia.gov/water/arsenic.htm. This report summarizes the contents of the website by providing brief descriptions of the technologies represented at the Forums and the results of the evaluations.

Evaluation of Technologies for Retrieval of Waste from Leaking Tanks

International Nuclear Information System (INIS)

Bamberger, Judith A.; Hatchell, Brian K.; Lewis, Benjamin E.; Randolph, John D.; Killough, Stephen M.

2000-01-01

The US Department of Energy Environmental and Waste Management Tanks Focus Area selected as a strategic initiative the need to identify and develop technologies for remediation of tanks that are known or are suspected to leak. This investigation identified and evaluated technical options for single-shell tank waste retrieval applicable to retrieve waste from potentially leaking tanks. Technologies that minimize leakage use minimal water, and dry retrieval technologies were evaluated. Safety, cost, authorization basis, and schedule risks were identified for each technology to provide River Protection Program with information to evaluate technical and programmatic risk. A workshop was held to identify technology needs and solutions. These approaches grouped into five categories: those related to waste dislodging, waste conveyance, both waste dislodging and conveyance, the deployment platform, and technologies related to leak detection, monitoring, and mitigation. Based on the ranking, six technologies were selected as potential candidates for further evaluation. These items were prioritized into four technologies to recommend for further evaluation (1) Air assisted TORE(R). The TORE(R) produces a processing vortex core with the ability to convey solids at pre-determined slurry concentrations over great distances. The dry TORE(R) concept uses air to develop the vortex to fluidize dry solids. The TORE(R)the solids in a slurry transport line. (2) Sonication for waste dislodging utilizes ultrasonic energy to fracture and dislodge hard waste types such as salt cake and sludge. (3) Novel long-reach manipulators concept is to investigate novel cost effective approaches for long-reach manipulator technology. (4) Next generation crawler technology envisions a non-umbilical dislodger, possibly radio controlled and powered remotely to provide a deployment platform not affected by path, or the need to retrace steps

Chinese character recognition based on Gabor feature extraction and CNN

Science.gov (United States)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Technologies for developing an advanced intelligent ATM with self-defence capabilities

Science.gov (United States)

Sako, Hiroshi

2010-01-01

We have developed several technologies for protecting automated teller machines. These technologies are based mainly on pattern recognition and are used to implement various self-defence functions. They include (i) banknote recognition and information retrieval for preventing machines from accepting counterfeit and damaged banknotes and for retrieving information about detected counterfeits from a relational database, (ii) form processing and character recognition for preventing machines from accepting remittance forms without due dates and/or insufficient payment, (iii) person identification to prevent machines from transacting with non-customers, and (iv) object recognition to guard machines against foreign objects such as spy cams that might be surreptitiously attached to them and to protect users against someone attempting to peek at their user information such as their personal identification number. The person identification technology has been implemented in most ATMs in Japan, and field tests have demonstrated that the banknote recognition technology can recognise more then 200 types of banknote from 30 different countries. We are developing an "advanced intelligent ATM" that incorporates all of these technologies.

Technology

Directory of Open Access Journals (Sweden)

Xu Jing

2016-01-01

Full Text Available The traditional answer card reading method using OMR (Optical Mark Reader, most commonly, OMR special card special use, less versatile, high cost, aiming at the existing problems proposed a method based on pattern recognition of the answer card identification method. Using the method based on Line Segment Detector to detect the tilt of the image, the existence of tilt image rotation correction, and eventually achieve positioning and detection of answers to the answer sheet .Pattern recognition technology for automatic reading, high accuracy, detect faster

Evaluating a Computer Flash-Card Sight-Word Recognition Intervention with Self-Determined Response Intervals in Elementary Students with Intellectual Disability

Science.gov (United States)

Cazzell, Samantha; Skinner, Christopher H.; Ciancio, Dennis; Aspiranti, Kathleen; Watson, Tiffany; Taylor, Kala; McCurdy, Merilee; Skinner, Amy

2017-01-01

A concurrent multiple-baseline across-tasks design was used to evaluate the effectiveness of a computer flash-card sight-word recognition intervention with elementary-school students with intellectual disability. This intervention allowed the participants to self-determine each response interval and resulted in both participants acquiring…

Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review.

Science.gov (United States)

Poder, Thomas G; Fisette, Jean-François; Déry, Véronique

2018-04-03

Speech recognition is increasingly used in medical reporting. The aim of this article is to identify in the literature the strengths and weaknesses of this technology, as well as barriers to and facilitators of its implementation. A systematic review of systematic reviews was performed using PubMed, Scopus, the Cochrane Library and the Center for Reviews and Dissemination through August 2017. The gray literature has also been consulted. The quality of systematic reviews has been assessed with the AMSTAR checklist. The main inclusion criterion was use of speech recognition for medical reporting (front-end or back-end). A survey has also been conducted in Quebec, Canada, to identify the dissemination of this technology in this province, as well as the factors leading to the success or failure of its implementation. Five systematic reviews were identified. These reviews indicated a high level of heterogeneity across studies. The quality of the studies reported was generally poor. Speech recognition is not as accurate as human transcription, but it can dramatically reduce turnaround times for reporting. In front-end use, medical doctors need to spend more time on dictation and correction than required with human transcription. With speech recognition, major errors occur up to three times more frequently. In back-end use, a potential increase in productivity of transcriptionists was noted. In conclusion, speech recognition offers several advantages for medical reporting. However, these advantages are countered by an increased burden on medical doctors and by risks of additional errors in medical reports. It is also hard to identify for which medical specialties and which clinical activities the use of speech recognition will be the most beneficial.

Surface imprinted beads for the recognition of human serum albumin.

Science.gov (United States)

Bonini, Francesca; Piletsky, Sergey; Turner, Anthony P F; Speghini, Adolfo; Bossi, Alessandra

2007-04-15

The synthesis of poly-aminophenylboronic acid (ABPA) imprinted beads for the recognition of the protein human serum albumin (HSA) is reported. In order to create homogeneous recognition sites, covalent immobilisation of the template HSA was exploited. The resulting imprinted beads were selective for HSA. The indirect imprinting factor (IF) calculated from supernatant was 1.6 and the direct IF, evaluated from the protein recovered from the beads, was 1.9. The binding capacity was 1.4 mg/g, which is comparable to commercially available affinity materials. The specificity of the HSA recognition was evaluated with competitive experiments, indicating a molar ratio 4.5/1 of competitor was necessary to displace half of the bound HSA. The recognition and binding of the imprinted beads was also tested with a complex sample, human serum and targeted removal of HSA without a loss of the other protein components was demonstrated. The easy preparation protocol of derivatised beads and a good protein recognition properties make the approach an attractive solution to analytical and bio-analytical problems in the field of biotechnology.

Learning and Treatment of Anaphylaxis by Laypeople: A Simulation Study Using Pupilar Technology.

Science.gov (United States)

Fernandez-Mendez, Felipe; Saez-Gallego, Nieves Maria; Barcala-Furelos, Roberto; Abelairas-Gomez, Cristian; Padron-Cabo, Alexis; Perez-Ferreiros, Alexandra; Garcia-Magan, Carlos; Moure-Gonzalez, Jose; Contreras-Jordan, Onofre; Rodriguez-Nuñez, Antonio

2017-01-01

An anaphylactic shock is a time-critical emergency situation. The decision-making during emergencies is an important responsibility but difficult to study. Eye-tracking technology allows us to identify visual patterns involved in the decision-making. The aim of this pilot study was to evaluate two training models for the recognition and treatment of anaphylaxis by laypeople, based on expert assessment and eye-tracking technology. A cross-sectional quasi-experimental simulation study was made to evaluate the identification and treatment of anaphylaxis. 50 subjects were randomly assigned to four groups: three groups watching different training videos with content supervised by sanitary personnel and one control group who received face-to-face training during paediatric practice. To evaluate the learning, a simulation scenario represented by an anaphylaxis' victim was designed. A device capturing eye movement as well as expert valuation was used to evaluate the performance. The subjects that underwent paediatric face-to-face training achieved better and faster recognition of the anaphylaxis. They also used the adrenaline injector with better precision and less mistakes, and they needed a smaller number of visual fixations to recognise the anaphylaxis and to make the decision to inject epinephrine. Analysing the different video formats, mixed results were obtained. Therefore, they should be tested to evaluate their usability before implementation.

Image quality assessment for video stream recognition systems

Science.gov (United States)

Chernov, Timofey S.; Razumnuy, Nikita P.; Kozharinov, Alexander S.; Nikolaev, Dmitry P.; Arlazarov, Vladimir V.

2018-04-01

Recognition and machine vision systems have long been widely used in many disciplines to automate various processes of life and industry. Input images of optical recognition systems can be subjected to a large number of different distortions, especially in uncontrolled or natural shooting conditions, which leads to unpredictable results of recognition systems, making it impossible to assess their reliability. For this reason, it is necessary to perform quality control of the input data of recognition systems, which is facilitated by modern progress in the field of image quality evaluation. In this paper, we investigate the approach to designing optical recognition systems with built-in input image quality estimation modules and feedback, for which the necessary definitions are introduced and a model for describing such systems is constructed. The efficiency of this approach is illustrated by the example of solving the problem of selecting the best frames for recognition in a video stream for a system with limited resources. Experimental results are presented for the system for identity documents recognition, showing a significant increase in the accuracy and speed of the system under simulated conditions of automatic camera focusing, leading to blurring of frames.

BCI meeting 2005--workshop on technology: hardware and software.

Science.gov (United States)

Cincotti, Febo; Bianchi, Luigi; Birch, Gary; Guger, Christoph; Mellinger, Jürgen; Scherer, Reinhold; Schmidt, Robert N; Yáñez Suárez, Oscar; Schalk, Gerwin

2006-06-01

This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop to review and evaluate the current state of BCI-related hardware and software. Technical requirements and current technologies, standardization procedures and future trends are covered. The main conclusion was recognition of the need to focus technical requirements on the users' needs and the need for consistent standards in BCI research.

Very deep recurrent convolutional neural network for object recognition

Science.gov (United States)

Brahimi, Sourour; Ben Aoun, Najib; Ben Amar, Chokri

2017-03-01

In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.

Development and Evaluation of a Speech Recognition Test for Persian Speaking Adults

Directory of Open Access Journals (Sweden)

Mohammad Mosleh

2001-05-01

Full Text Available Method and Materials: This research is carried out for development and evaluation of 25 phonemically balanced word lists for Persian speaking adults in two separate stages: development and evaluation. In the first stage, in order to balance the lists phonemically, frequency -of- occurrences of each 29phonems (6 vowels and 23 Consonants of the Persian language in adults speech are determined. This section showed some significant differences between some phonemes' frequencies. Then, all Persian monosyllabic words extracted from the Mo ‘in Persian dictionary. The semantically difficult words were refused and the appropriate words choosed according to judgment of 5 adult native speakers of Persian with high school diploma. 12 openset 25 word lists are prepared. The lists were recorded on magnetic tapes in an audio studio by a professional speaker of IRIB. "nIn the second stage, in order to evaluate the test's validity and reliability, 60 normal hearing adults (30 male, 30 female, were randomly selected and evaluated as test and retest. Findings: 1- Normal hearing adults obtained 92-1 0O scores for each list at their MCL through test-retest. 2- No significant difference was observed a/ in test-retest scores in each list (‘P>O.05 b/ between the lists at test or retest scores (P>0.05, c/between sex (P>0.05. Conclusion: This research is reliable and valid, the lists are phonemically balanced and equal in difficulty and valuable for evaluation of Persian speaking adults speech recognition.

The A2iA French handwriting recognition system at the Rimes-ICDAR2011 competition

Science.gov (United States)

Menasri, Farès; Louradour, Jérôme; Bianne-Bernard, Anne-Laure; Kermorvant, Christopher

2012-01-01

This paper describes the system for the recognition of French handwriting submitted by A2iA to the competition organized at ICDAR2011 using the Rimes database. This system is composed of several recognizers based on three different recognition technologies, combined using a novel combination method. A framework multi-word recognition based on weighted finite state transducers is presented, using an explicit word segmentation, a combination of isolated word recognizers and a language model. The system was tested both for isolated word recognition and for multi-word line recognition and submitted to the RIMES-ICDAR2011 competition. This system outperformed all previously proposed systems on these tasks.

Warmth of familiarity and chill of error: affective consequences of recognition decisions.

Science.gov (United States)

Chetverikov, Andrey

2014-04-01

The present research aimed to assess the effect of recognition decision on subsequent affective evaluations of recognised and non-recognised objects. Consistent with the proposed account of post-decisional preferences, results showed that the effect of recognition on preferences depends upon objective familiarity. If stimuli are recognised, liking ratings are positively associated with exposure frequency; if stimuli are not recognised, this link is either absent (Experiment 1) or negative (Experiments 2 and 3). This interaction between familiarity and recognition exists even when recognition accuracy is at chance level and the "mere exposure" effect is absent. Finally, data obtained from repeated measurements of preferences and using manipulations of task order confirm that recognition decisions have a causal influence on preferences. The findings suggest that affective evaluation can provide fine-grained access to the efficacy of cognitive processing even in simple cognitive tasks.

Oak Ridge National Laboratory Technology Logic Diagram. Volume 1, Technology Evaluation: Part B, Remedial Action

Energy Technology Data Exchange (ETDEWEB)

1993-09-01

The Oak Ridge National Laboratory Technology Logic Diagram (TLD) was developed to provide a decision-support tool that relates environmental restoration (ER) and waste management (WM) problems at Oak Ridge National Laboratory (ORNL) to potential technologies that can remediate these problems. The TLD identifies the research, development, demonstration, testing, and evaluation needed to develop these technologies to a state that allows technology transfer and application to decontamination and decommissioning (D&D), remedial action (RA), and WM activities. The TLD consists of three fundamentally separate volumes: Vol. 1 (Technology Evaluation), Vol. 2 (Technology Logic Diagram), and Vol. 3 (Technology Evaluation Data Sheets). Part A of Vols. 1 and 2 focuses on D&D. Part B of Vols. 1 and 2 focuses on RA of contaminated facilities. Part C of Vols. 1 and 2 focuses on WM. Each part of Vol. 1 contains an overview of the TLD, an explanation of the program-specific responsibilities, a review of identified technologies, and the ranking os remedial technologies. Volume 2 (Pts. A, B, and C) contains the logic linkages among EM goals, environmental problems, and the various technologies that have the potential to solve these problems. Volume 3 (Pts. A, B, and C) contains the TLD data sheets. The focus of Vol. 1, Pt. B, is RA, and it has been divided into six chapters. The first chapter is an introduction, which defines problems specific to the ER Program for ORNL. Chapter 2 provides a general overview of the TLD. Chapters 3 through 5 are organized into necessary subelement categories: RA, characterization, and robotics and automation. The final chapter contains regulatory compliance information concerning RA.

Automatic speech recognition for report generation in computed tomography

International Nuclear Information System (INIS)

Teichgraeber, U.K.M.; Ehrenstein, T.; Lemke, M.; Liebig, T.; Stobbe, H.; Hosten, N.; Keske, U.; Felix, R.

1999-01-01

Purpose: A study was performed to compare the performance of automatic speech recognition (ASR) with conventional transcription. Materials and Methods: 100 CT reports were generated by using ASR and 100 CT reports were dictated and written by medical transcriptionists. The time for dictation and correction of errors by the radiologist was assessed and the type of mistakes was analysed. The text recognition rate was calculated in both groups and the average time between completion of the imaging study by the technologist and generation of the written report was assessed. A commercially available speech recognition technology (ASKA Software, IBM Via Voice) running of a personal computer was used. Results: The time for the dictation using digital voice recognition was 9.4±2.3 min compared to 4.5±3.6 min with an ordinary Dictaphone. The text recognition rate was 97% with digital voice recognition and 99% with medical transcriptionists. The average time from imaging completion to written report finalisation was reduced from 47.3 hours with medical transcriptionists to 12.7 hours with ASR. The analysis of misspellings demonstrated (ASR vs. medical transcriptionists): 3 vs. 4 for syntax errors, 0 vs. 37 orthographic mistakes, 16 vs. 22 mistakes in substance and 47 vs. erroneously applied terms. Conclusions: The use of digital voice recognition as a replacement for medical transcription is recommendable when an immediate availability of written reports is necessary. (orig.) [de

Energetic and economic evaluations on hydrogen storage technologies

Energy Technology Data Exchange (ETDEWEB)

Arca, S.; Di Profio, P.; Germani, R. [Perugia Univ., Perugia (Italy). Centro di Eccellenza Materiali Innovativi Nanostrutturati, Dip. Chimica; Savelli, G.; Cotana, F.; Rossi, F.; Amantini, M. [Universita degli Studi di Perugia, Perugia (Italy). Dipartimento di Ingegneria Industriale, Sezione di Fisica Tecnica

2008-07-01

With the development of the hydrogen economy and fuel cell vehicles, a major technological issue has emerged regarding the storage and delivery of large amounts of hydrogen. Several hydrogen storage methodologies are available while other technologies are being developed aside from the classical compression and liquefaction of hydrogen. A novel technology is also in rapid process, which is based on clathrate hydrates of hydrogen. The features and performances of available storage systems were evaluated in an effort to determine the best technology throughout the hydrogen chain. For each of the storage solutions presented, the key parameters were compared. These key parameters included interaction energy between hydrogen and support; real and practical storage capacity; and specific energy consumption. The paper presented the study methods and discussed hydrogen storage technologies using compressed hydrogen; metal hydrides; liquefied hydrogen; carbon nanotubes; ammonia; and gas hydrates. Carbon dioxide emissions were also evaluated for each storage system analyzed. The paper also presented the worst scenario. It was concluded that a technology based on clathrate hydrates of hydrogen, while being far from optimized, was highly competitive with the classical approaches. 21 refs., 9 figs.

Tracking Activities in Complex Settings Using Smart Environment Technologies.

Science.gov (United States)

Singla, Geetika; Cook, Diane J; Schmitter-Edgecombe, Maureen

2009-01-01

The pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. A primary challenge that needs to be tackled to meet this need is the ability to recognize and track functional activities that people perform in their own homes and everyday settings. In this paper we look at approaches to perform real-time recognition of Activities of Daily Living. We enhance other related research efforts to develop approaches that are effective when activities are interrupted and interleaved. To evaluate the accuracy of our recognition algorithms we assess them using real data collected from participants performing activities in our on-campus smart apartment testbed.

TECHNOLOGY EVALUATION REPORT: SILICATE TECHNOLOGY CORPORATION - SOLIDIFICATION/STABILIZATION OF PCP AND INORGANIC CONTAMINANTS IN SOILS - SELMA, CA

Science.gov (United States)

This Technolgy Evaluation Report evaluates the solidification/stabilization process of Silicate Technology Corporation (STC) for the on-site treatment of contaminated soil The STC immobilization technology uses a proprietary product (FMS Silicate) to chemically stabilize and ...

Impaired Odor Recognition Memory in Patients with Hippocampal Lesions

Science.gov (United States)

Levy, Daniel A.; Squire, Larry R.; Hopkins, Ramona O.

2004-01-01

In humans, impaired recognition memory following lesions thought to be limited to the hippocampal region has been demonstrated for a wide variety of tasks. However, the importance of the human hippocampus for olfactory recognition memory has scarcely been explored. We evaluated the ability of memory-impaired patients with damage thought to be…

Impact of multi-focused images on recognition of soft biometric traits

Science.gov (United States)

Chiesa, V.; Dugelay, J. L.

2016-09-01

In video surveillance semantic traits estimation as gender and age has always been debated topic because of the uncontrolled environment: while light or pose variations have been largely studied, defocused images are still rarely investigated. Recently the emergence of new technologies, as plenoptic cameras, yields to deal with these problems analyzing multi-focus images. Thanks to a microlens array arranged between the sensor and the main lens, light field cameras are able to record not only the RGB values but also the information related to the direction of light rays: the additional data make possible rendering the image with different focal plane after the acquisition. For our experiments, we use the GUC Light Field Face Database that includes pictures from the First Generation Lytro camera. Taking advantage of light field images, we explore the influence of defocusing on gender recognition and age estimation problems. Evaluations are computed on up-to-date and competitive technologies based on deep learning algorithms. After studying the relationship between focus and gender recognition and focus and age estimation, we compare the results obtained by images defocused by Lytro software with images blurred by more standard filters in order to explore the difference between defocusing and blurring effects. In addition we investigate the impact of deblurring on defocused images with the goal to better understand the different impacts of defocusing and standard blurring on gender and age estimation.

Embedding technology into inter-professional best practices in home safety evaluation.

Science.gov (United States)

Burns, Suzanne Perea; Pickens, Noralyn Davel

2017-08-01

To explore inter-professional home evaluators' perspectives and needs for building useful and acceptable decision-support tools for the field of home modifications. Twenty semi-structured interviews were conducted with a range of home modification professionals from different regions of the United States. The interview transcripts were analyzed with a qualitative, descriptive, perspective approach. Technology supports current best practice and has potential to inform decision making through features that could enhance home evaluation processes, quality, efficiency and inter-professional communication. Technological advances with app design have created numerous opportunities for the field of home modifications. Integrating technology and inter-professional best practices will improve home safety evaluation and intervention development to meet client-centred and societal needs. Implications for rehabilitation Understanding home evaluators technology needs for home safety evaluations contributes to the development of app-based assessments. Integrating inter-professional perspectives of best practice and technological needs in an app for home assessments improves processes. Novice and expert home evaluators would benefit from decision support systems embedded in app-based assessments. Adoption of app-based assessment would improve efficiency while remaining client-centred.

Application of pattern recognition techniques to crime analysis

Energy Technology Data Exchange (ETDEWEB)

Bender, C.F.; Cox, L.A. Jr.; Chappell, G.A.

1976-08-15

The initial goal was to evaluate the capabilities of current pattern recognition techniques when applied to existing computerized crime data. Performance was to be evaluated both in terms of the system's capability to predict crimes and to optimize police manpower allocation. A relation was sought to predict the crime's susceptibility to solution, based on knowledge of the crime type, location, time, etc. The preliminary results of this work are discussed. They indicate that automatic crime analysis involving pattern recognition techniques is feasible, and that efforts to determine optimum variables and techniques are warranted. 47 figures (RWR)

A study on the extraction of feature variables for the pattern recognition for welding flaws

International Nuclear Information System (INIS)

Kim, J. Y.; Kim, C. H.; Kim, B. H.

1996-01-01

In this study, the researches classifying the artificial and natural flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including the user defined function was developed and the total procedure including the digital signal processing, feature extraction, feature selection and classifier selection is treated by bulk. Specially it is composed with and discussed using the statistical classifier such as the linear discriminant function classifier, the empirical Bayesian classifier. Also, the pattern recognition technology is applied to classification problem of natural flaw(i.e multiple classification problem-crack, lack of penetration, lack of fusion, porosity, and slag inclusion, the planar and volumetric flaw classification problem). According to this results, if appropriately teamed the neural network classifier is better than stastical classifier in the classification problem of natural flaw. And it is possible to acquire the recognition rate of 80% above through it is different a little according to domain extracting the feature and the classifier.

Technology Evaluation Workshop Report for Tank Waste Chemical Characterization

International Nuclear Information System (INIS)

Eberlein, S.J.

1994-04-01

A Tank Waste Chemical Characterization Technology Evaluation Workshop was held August 24--26, 1993. The workshop was intended to identify and evaluate technologies appropriate for the in situ and hot cell characterization of the chemical composition of Hanford waste tank materials. The participants were asked to identify technologies that show applicability to the needs and good prospects for deployment in the hot cell or tanks. They were also asked to identify the tasks required to pursue the development of specific technologies to deployment readiness. This report describes the findings of the workshop. Three focus areas were identified for detailed discussion: (1) elemental analysis, (2) molecular analysis, and (3) gas analysis. The technologies were restricted to those which do not require sample preparation. Attachment 1 contains the final workshop agenda and a complete list of attendees. An information package (Attachment 2) was provided to all participants in advance to provide information about the Hanford tank environment, needs, current characterization practices, potential deployment approaches, and the evaluation procedure. The participants also received a summary of potential technologies (Attachment 3). The workshop opened with a plenary session, describing the background and issues in more detail. Copies of these presentations are contained in Attachments 4, 5 and 6. This session was followed by breakout sessions in each of the three focus areas. The workshop closed with a plenary session where each focus group presented its findings. This report summarizes the findings of each of the focus groups. The evaluation criteria and information about specific technologies are tabulated at the end of each section in the report. The detailed notes from each focus group are contained in Attachments 7, 8 and 9

Identification of strong earthquake ground motion by using pattern recognition

International Nuclear Information System (INIS)

Suzuki, Kohei; Tozawa, Shoji; Temmyo, Yoshiharu.

1983-01-01

The method of grasping adequately the technological features of complex waveform of earthquake ground motion and utilizing them as the input to structural systems has been proposed by many researchers, and the method of making artificial earthquake waves to be used for the aseismatic design of nuclear facilities has not been established in the unified form. In this research, earthquake ground motion was treated as an irregular process with unsteady amplitude and frequency, and the running power spectral density was expressed as a dark and light image on a plane of the orthogonal coordinate system with both time and frequency axes. The method of classifying this image into a number of technologically important categories by pattern recognition was proposed. This method is based on the concept called compound similarity method in the image technology, entirely different from voice diagnosis, and it has the feature that the result of identification can be quantitatively evaluated by the analysis of correlation of spatial images. Next, the standard pattern model of the simulated running power spectral density corresponding to the representative classification categories was proposed. Finally, the method of making unsteady simulated earthquake motion was shown. (Kako, I.)

Health services research evaluation principles. Broadening a general framework for evaluating health information technology.

Science.gov (United States)

Sockolow, P S; Crawford, P R; Lehmann, H P

2012-01-01

Our forthcoming national experiment in increased health information technology (HIT) adoption funded by the American Recovery and Reinvestment Act of 2009 will require a comprehensive approach to evaluating HIT. The quality of evaluation studies of HIT to date reveals a need for broader evaluation frameworks that limits the generalizability of findings and the depth of lessons learned. Develop an informatics evaluation framework for health information technology (HIT) integrating components of health services research (HSR) evaluation and informatics evaluation to address identified shortcomings in available HIT evaluation frameworks. A systematic literature review updated and expanded the exhaustive review by Ammenwerth and deKeizer (AdK). From retained studies, criteria were elicited and organized into classes within a framework. The resulting Health Information Technology Research-based Evaluation Framework (HITREF) was used to guide clinician satisfaction survey construction, multi-dimensional analysis of data, and interpretation of findings in an evaluation of a vanguard community health care EHR. The updated review identified 128 electronic health record (EHR) evaluation studies and seven evaluation criteria not in AdK: EHR Selection/Development/Training; Patient Privacy Concerns; Unintended Consequences/ Benefits; Functionality; Patient Satisfaction with EHR; Barriers/Facilitators to Adoption; and Patient Satisfaction with Care. HITREF was used productively and was a complete evaluation framework which included all themes that emerged. We can recommend to future EHR evaluators that they consider adding a complete, research-based HIT evaluation framework, such as HITREF, to their evaluation tools suite to monitor HIT challenges as the federal government strives to increase HIT adoption.

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Iris recognition as a biometric method after cataract surgery.

Science.gov (United States)

Roizenblatt, Roberto; Schor, Paulo; Dante, Fabio; Roizenblatt, Jaime; Belfort, Rubens

2004-01-28

Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical) distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

Science.gov (United States)

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

Hierarchical Context Modeling for Video Event Recognition.

Science.gov (United States)

Wang, Xiaoyang; Ji, Qiang

2016-10-11

Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.

Assessment and evaluation of technologies for environmental restoration. Progress report

Energy Technology Data Exchange (ETDEWEB)

Uzochukwu, G. A. [North Carolina A and T State Univ., Greensboro, NC (United States)

2000-06-30

Nuclear and commercial non-nuclear technologies that have the potential of meeting the environmental restoration objectives of the Department of Energy are being evaluated. A detailed comparison of innovative technologies available will be performed to determine the safest and most economical technology for meeting these objectives. Information derived from this effort will be matched with the multi-objective of the environmental restoration effort to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formatted and computerized for multimedia systems. The multimedia system will be made available to technology developers and evaluators to ensure that the safest and most economical technologies are developed for use at SRS and other DOE sites.

Assessment and evaluation of technologies for environmental restoration. Progress report

International Nuclear Information System (INIS)

Uzochukwu, G. A.

2000-01-01

Nuclear and commercial non-nuclear technologies that have the potential of meeting the environmental restoration objectives of the Department of Energy are being evaluated. A detailed comparison of innovative technologies available will be performed to determine the safest and most economical technology for meeting these objectives. Information derived from this effort will be matched with the multi-objective of the environmental restoration effort to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formatted and computerized for multimedia systems. The multimedia system will be made available to technology developers and evaluators to ensure that the safest and most economical technologies are developed for use at SRS and other DOE sites.

Assessment and evaluation of technologies for environmental restoration. Progress report

International Nuclear Information System (INIS)

Uzochukwu, G.A.

1999-01-01

Nuclear and commercial non-nuclear technologies that have the potential of meeting the environmental restoration objectives of the Department of Energy are being evaluated. A detailed comparison of innovative technologies available will be performed to determine the safest and most economical technology for meeting these objectives. Information derived from this effort will be matched with the multi-objective of the environmental restoration effort to ensure that the best, most economical, and the safest technologies are used in decision making at USDOE-SRS. Technology-related variables will be developed and the resulting data formatted and computerized for multimedia systems. The multimedia system will be made available to technology developers and evaluators to ensure that the safest and most economical technologies are developed for use at SRS and other DOE sites

A new selective developmental deficit: Impaired object recognition with normal face recognition.

Science.gov (United States)

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Involving stakeholders in evaluating environmental restoration technologies

International Nuclear Information System (INIS)

McCabe, G.H.; Serie, P.J.

1993-02-01

Involving citizens, interest groups, and regulators in environmental restoration and waste management programs is a challenge for government agencies and the organizations that support them. To be effective, such involvement activities must identify all individuals and groups who have a stake in the cleanup. Their participation must be early, substantive, and meaningful. Stockholders must be able to see how their input was considered and used, and feel that a good- faith effort was made to reconcile conflicting objectives. The Integrated Demonstration for Cleanup of Volatile Organic Compounds at Arid Sites (VOC-Arid ID) is a Department of Energy Office of Technology Development project located at Hanford. Along with technical evaluation of innovative cleanup technologies, the program is conducting an institutional assessment of regulatory and public acceptance of new technologies. Through a series of interviews and workshops, and use of a computerized information management tool, stakeholders are having a voice in the evaluation. Public and regulatory reaction has been positive

Facial and prosodic emotion recognition in social anxiety disorder.

Science.gov (United States)

Tseng, Huai-Hsuan; Huang, Yu-Lien; Chen, Jian-Ting; Liang, Kuei-Yu; Lin, Chao-Cheng; Chen, Sue-Huei

2017-07-01

Patients with social anxiety disorder (SAD) have a cognitive preference to negatively evaluate emotional information. In particular, the preferential biases in prosodic emotion recognition in SAD have been much less explored. The present study aims to investigate whether SAD patients retain negative evaluation biases across visual and auditory modalities when given sufficient response time to recognise emotions. Thirty-one SAD patients and 31 age- and gender-matched healthy participants completed a culturally suitable non-verbal emotion recognition task and received clinical assessments for social anxiety and depressive symptoms. A repeated measures analysis of variance was conducted to examine group differences in emotion recognition. Compared to healthy participants, SAD patients were significantly less accurate at recognising facial and prosodic emotions, and spent more time on emotion recognition. The differences were mainly driven by the lower accuracy and longer reaction times for recognising fearful emotions in SAD patients. Within the SAD patients, lower accuracy of sad face recognition was associated with higher severity of depressive and social anxiety symptoms, particularly with avoidance symptoms. These findings may represent a cross-modality pattern of avoidance in the later stage of identifying negative emotions in SAD. This pattern may be linked to clinical symptom severity.

A preliminary analysis of human factors affecting the recognition accuracy of a discrete word recognizer for C3 systems

Science.gov (United States)

Yellen, H. W.

1983-03-01

Literature pertaining to Voice Recognition abounds with information relevant to the assessment of transitory speech recognition devices. In the past, engineering requirements have dictated the path this technology followed. But, other factors do exist that influence recognition accuracy. This thesis explores the impact of Human Factors on the successful recognition of speech, principally addressing the differences or variability among users. A Threshold Technology T-600 was used for a 100 utterance vocubalary to test 44 subjects. A statistical analysis was conducted on 5 generic categories of Human Factors: Occupational, Operational, Psychological, Physiological and Personal. How the equipment is trained and the experience level of the speaker were found to be key characteristics influencing recognition accuracy. To a lesser extent computer experience, time or week, accent, vital capacity and rate of air flow, speaker cooperativeness and anxiety were found to affect overall error rates.

Pattern recognition for cache management in distributed medical imaging environments.

Science.gov (United States)

Viana-Ferreira, Carlos; Ribeiro, Luís; Matos, Sérgio; Costa, Carlos

2016-02-01

Traditionally, medical imaging repositories have been supported by indoor infrastructures with huge operational costs. This paradigm is changing thanks to cloud outsourcing which not only brings technological advantages but also facilitates inter-institutional workflows. However, communication latency is one main problem in this kind of approaches, since we are dealing with tremendous volumes of data. To minimize the impact of this issue, cache and prefetching are commonly used. The effectiveness of these mechanisms is highly dependent on their capability of accurately selecting the objects that will be needed soon. This paper describes a pattern recognition system based on artificial neural networks with incremental learning to evaluate, from a set of usage pattern, which one fits the user behavior at a given time. The accuracy of the pattern recognition model in distinct training conditions was also evaluated. The solution was tested with a real-world dataset and a synthesized dataset, showing that incremental learning is advantageous. Even with very immature initial models, trained with just 1 week of data samples, the overall accuracy was very similar to the value obtained when using 75% of the long-term data for training the models. Preliminary results demonstrate an effective reduction in communication latency when using the proposed solution to feed a prefetching mechanism. The proposed approach is very interesting for cache replacement and prefetching policies due to the good results obtained since the first deployment moments.

Selecting Molecular Recognition. What Can Existing Aptamers Tell Us about Their Inherent Recognition Capabilities and Modes of Interaction?

Directory of Open Access Journals (Sweden)

Ralf Landgraf

2012-05-01

Full Text Available The use of nucleic acid derived aptamers has rapidly expanded since the introduction of SELEX in 1990. Nucleic acid aptamers have demonstrated their ability to target a broad range of molecules in ways that rival antibodies, but advances have been very uneven for different biochemical classes of targets, and clinical applications have been slow to emerge. What sets different aptamers apart from each other and from rivaling molecular recognition platforms, specifically proteins? What advantages do aptamers as a reagent class offer, and how do the chemical properties and selection procedures of aptamers influence their function? Do the building blocks of nucleic acid aptamers dictate inherent limitations in the nature of molecular targets, and do existing aptamers give us insight in how these challenges might be overcome? This review is written as an introduction for potential endusers of aptamer technology who are evaluating the advantages of aptamers as a versatile, affordable, yet highly expandable platform to target a broad range of biological processes or interactions.

Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition.

Science.gov (United States)

Carvajal, Gonzalo; Figueroa, Miguel

2014-07-01

Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights

Evaluation Method for Service Branding Using Word-of-Mouth Data

Science.gov (United States)

Shirahada, Kunio; Kosaka, Michitaka

Development and spread of internet technology contributes service firms to obtaining the high capability of brand information transmission as well as relative customer feedback data collection. In this paper, we propose a new evaluation method for service branding using firms and consumers data on the internet. Based on service marketing 7Ps (Product, Price, Place, Promotion, People, Physical evidence, Process) which are the key viewpoints for branding, we develop a brand evaluation system including coding methods for Word-of-Mouth (WoM) and corporate introductory information on the internet to identify both customer's service value recognition vector and firm's service value proposition vector. Our system quantitatively clarify both customer's service value recognition of the firm and firm's strength in service value proposition, thereby analyzing service brand communication gaps between firm and consumers. We applied this system to Japanese Ryokan hotel industry. Using six ryokan-hotels' data on Jyaran-net and Rakuten travel, we made totally 983 codes from WoM information and analyzed their service brand value according to three price based categories. As a result, we found that the characteristics of customers' service value recognition vector differ according to the price categories. In addition, the system clarified that there is a firm that has a different service value proposition vector from customers' recognition vector. This helps to analyze corporate service brand strategy and has a significance as a system technology supporting service management.

Recognition and Evaluation of Clinical Section Headings in Clinical Documents Using Token-Based Formulation with Conditional Random Fields

Directory of Open Access Journals (Sweden)

Hong-Jie Dai

2015-01-01

Full Text Available Electronic health record (EHR is a digital data format that collects electronic health information about an individual patient or population. To enhance the meaningful use of EHRs, information extraction techniques have been developed to recognize clinical concepts mentioned in EHRs. Nevertheless, the clinical judgment of an EHR cannot be known solely based on the recognized concepts without considering its contextual information. In order to improve the readability and accessibility of EHRs, this work developed a section heading recognition system for clinical documents. In contrast to formulating the section heading recognition task as a sentence classification problem, this work proposed a token-based formulation with the conditional random field (CRF model. A standard section heading recognition corpus was compiled by annotators with clinical experience to evaluate the performance and compare it with sentence classification and dictionary-based approaches. The results of the experiments showed that the proposed method achieved a satisfactory F-score of 0.942, which outperformed the sentence-based approach and the best dictionary-based system by 0.087 and 0.096, respectively. One important advantage of our formulation over the sentence-based approach is that it presented an integrated solution without the need to develop additional heuristics rules for isolating the headings from the surrounding section contents.

Do we need an open face recognition search engine?

OpenAIRE

Cammozzo, Alberto

2012-01-01

The wide application of face recognition technology may expose us to unforeseen situations. Our ability to cope with this technological innovation may have important consequences for human rights and citizens privacy. One of the most bothering issues is information asymmetry being introduced not only in the web, but also in real life situations. Some imaginary situations are listed, along with the technical and normative means to restore information symmetry. One of the possible solutions ...

Advances in Computing and Information Technology : Proceedings of the Second International Conference on Advances in Computing and Information Technology

CERN Document Server

Nagamalai, Dhinaharan; Chaki, Nabendu

2013-01-01

The international conference on Advances in Computing and Information technology (ACITY 2012) provides an excellent international forum for both academics and professionals for sharing knowledge and results in theory, methodology and applications of Computer Science and Information Technology. The Second International Conference on Advances in Computing and Information technology (ACITY 2012), held in Chennai, India, during July 13-15, 2012, covered a number of topics in all major fields of Computer Science and Information Technology including: networking and communications, network security and applications, web and internet computing, ubiquitous computing, algorithms, bioinformatics, digital image processing and pattern recognition, artificial intelligence, soft computing and applications. Upon a strength review process, a number of high-quality, presenting not only innovative ideas but also a founded evaluation and a strong argumentation of the same, were selected and collected in the present proceedings, ...

Man, society, technology. Reference points in the debate on technology acceptance. Mensch - Gesellschaft - Technik. Orientierungspunkte in der Technikakzeptanzdebatte

Energy Technology Data Exchange (ETDEWEB)

Kistler, E.; Jaufmann, D. (Internationales Inst. fuer Empirische Sozialoekonomie, Stadtbergen (Germany, F.R.)) (eds.)

1990-01-01

The acceptance of technological risks, which is discussed today mainly in the context of large-scale technologies, has become the subject of political argument, of power politics and also of negotiation. Its evaluation and assessment depend not least on the current atmosphere for decisions and the specific subject. Acceptance research - this is one of the central theses of this book - is not (only) a reactive instrument for later fine-tuning after the probability of risk is evident, but can also be more. However, it requires to this end 'cleaner' and more comprehensible methods; the recognition of its viability limits is also necessary. It provides then a possibility for a rational formulation of policies on the basis of a long-standing, and certainly partly superfluous technological-political dialogue. (orig.).

Face recognition based on matching of local features on 3D dynamic range sequences

Science.gov (United States)

Echeagaray-Patrón, B. A.; Kober, Vitaly

2016-09-01

3D face recognition has attracted attention in the last decade due to improvement of technology of 3D image acquisition and its wide range of applications such as access control, surveillance, human-computer interaction and biometric identification systems. Most research on 3D face recognition has focused on analysis of 3D still data. In this work, a new method for face recognition using dynamic 3D range sequences is proposed. Experimental results are presented and discussed using 3D sequences in the presence of pose variation. The performance of the proposed method is compared with that of conventional face recognition algorithms based on descriptors.

Increased deficits in emotion recognition and regulation in children and adolescents with exogenous obesity.

Science.gov (United States)

Percinel, Ipek; Ozbaran, Burcu; Kose, Sezen; Simsek, Damla Goksen; Darcan, Sukran

2018-03-01

In this study we aimed to evaluate emotion recognition and emotion regulation skills of children with exogenous obesity between the ages of 11 and 18 years and compare them with healthy controls. The Schedule for Affective Disorders and Schizophrenia for School Aged Children was used for psychiatric evaluations. Emotion recognition skills were evaluated using Faces Test and Reading the Mind in the Eyes Test. The Difficulties in Emotions Regulation Scale was used for evaluating skills of emotion regulation. Children with obesity had lower scores on Faces Test and Reading the Mind in the Eyes Test, and experienced greater difficulty in emotional regulation skills. Improved understanding of emotional recognition and emotion regulation in young people with obesity may improve their social adaptation and help in the treatment of their disorder. To the best of our knowledge, this is the first study to evaluate both emotional recognition and emotion regulation functions in obese children and obese adolescents between 11 and 18 years of age.

Towards automatic forensic face recognition

NARCIS (Netherlands)

Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2011-01-01

In this paper we present a methodology and experimental results for evidence evaluation in the context of forensic face recognition. In forensic applications, the matching score (hereafter referred to as similarity score) from a biometric system must be represented as a Likelihood Ratio (LR). In our

Action Recognition Using Motion Primitives and Probabilistic Edit Distance

DEFF Research Database (Denmark)

Fihl, Preben; Holte, Michael Boelstoft; Moeslund, Thomas B.

2006-01-01

In this paper we describe a recognition approach based on the notion of primitives. As opposed to recognizing actions based on temporal trajectories or temporal volumes, primitive-based recognition is based on representing a temporal sequence containing an action by only a few characteristic time...... into a string containing a sequence of symbols, each representing a primitives. After pruning the string a probabilistic Edit Distance classifier is applied to identify which action best describes the pruned string. The approach is evaluated on five one-arm gestures and the recognition rate is 91...

Mechanical Fault Diagnosis Using Color Image Recognition of Vibration Spectrogram Based on Quaternion Invariable Moment

Directory of Open Access Journals (Sweden)

Liang Hua

2015-01-01

Full Text Available Automatic extraction of time-frequency spectral image of mechanical faults can be achieved and faults can be identified consequently when rotating machinery spectral image processing technology is applied to fault diagnosis, which is an advantage. Acquired mechanical vibration signals can be converted into color time-frequency spectrum images by the processing of pseudo Wigner-Ville distribution. Then a feature extraction method based on quaternion invariant moment was proposed, combining image processing technology and multiweight neural network technology. The paper adopted quaternion invariant moment feature extraction method and gray level-gradient cooccurrence matrix feature extraction method and combined them with geometric learning algorithm and probabilistic neural network algorithm, respectively, and compared the recognition rates of rolling bearing faults. The experimental results show that the recognition rates of quaternion invariant moment are higher than gray level-gradient cooccurrence matrix in the same recognition method. The recognition rates of geometric learning algorithm are higher than probabilistic neural network algorithm in the same feature extraction method. So the method based on quaternion invariant moment geometric learning and multiweight neural network is superior. What is more, this algorithm has preferable generalization performance under the condition of fewer samples, and it has practical value and acceptation on the field of fault diagnosis for rotating machinery as well.

Evaluation of Brine Processing Technologies for Spacecraft Wastewater

Science.gov (United States)

Shaw, Hali L.; Flynn, Michael; Wisniewski, Richard; Lee, Jeffery; Jones, Harry; Delzeit, Lance; Shull, Sarah; Sargusingh, Miriam; Beeler, David; Howard, Jeanie;

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Novel acoustic features for speech emotion recognition

Institute of Scientific and Technical Information of China (English)

ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

2009-01-01

This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

Evaluation of selected sewage sludge gasification technological parameters

Science.gov (United States)

Gałko, Grzegorz; Król, Danuta

2018-02-01

Evaluation of selected sewage sludge gasification technological parameters was shown in this paper. Degree of carbon conducted in combustible substance and syngas efficiency (technological readiness coefficient) in accordance with equations were calculated. Enthalpy of individual compounds formation and energy balance were calculated in accordance with rule of Hess.

Advertisement recognition using mode voting acoustic fingerprint

Science.gov (United States)

Fahmi, Reza; Abedi Firouzjaee, Hosein; Janalizadeh Choobbasti, Ali; Mortazavi Najafabadi, S. H. E.; Safavi, Saeid

2017-12-01

Emergence of media outlets and public relations tools such as TV, radio and the Internet since the 20th century provided the companies with a good platform for advertising their goods and services. Advertisement recognition is an important task that can help companies measure the efficiency of their advertising campaigns in the market and make it possible to compare their performance with competitors in order to get better business insights. Advertisement recognition is usually performed manually with help of human labor or is done through automated methods that are mainly based on heuristics features, these methods usually lack abilities such as scalability, being able to be generalized and be used in different situations. In this paper, we present an automated method for advertisement recognition based on audio processing method that could make this process fairly simple and eliminate the human factor out of the equation. This method has ultimately been used in Miras information technology in order to monitor 56 TV channels to detect all ad video clips broadcast over some networks.

Compact Acoustic Models for Embedded Speech Recognition

Directory of Open Access Journals (Sweden)

Lévy Christophe

2009-01-01

Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

Robust Indoor Human Activity Recognition Using Wireless Signals.

Science.gov (United States)

Wang, Yi; Jiang, Xinli; Cao, Rongyu; Wang, Xiyang

2015-07-15

Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

Robust Indoor Human Activity Recognition Using Wireless Signals

Directory of Open Access Journals (Sweden)

Yi Wang

2015-07-01

Full Text Available Wireless signals–based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP and access points (AP. First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions’ CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

International Nuclear Information System (INIS)

Deputch, G.; Hoff, J.; Lipton, R.; Liu, T.; Olsen, J.; Ramberg, E.; Wu, Jin-Yuan; Yarema, R.; Shochet, M.; Tang, F.; Demarteau, M.

2011-01-01

Many next-generation physics experiments will be characterized by the collection of large quantities of data, taken in rapid succession, from which scientists will have to unravel the underlying physical processes. In most cases, large backgrounds will overwhelm the physics signal. Since the quantity of data that can be stored for later analysis is limited, real-time event selection is imperative to retain the interesting events while rejecting the background. Scaling of current technologies is unlikely to satisfy the scientific needs of future projects, so investments in transformational new technologies need to be made. For example, future particle physics experiments looking for rare processes will have to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare processes. In this proposal, we intend to develop hardware-based technology that significantly advances the state-of-the-art for fast pattern recognition within and outside HEP using the 3D vertical integration technology that has emerged recently in industry. The ultimate physics reach of the LHC experiments will crucially depend on the tracking trigger's ability to help discriminate between interesting rare events and the background. Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing pattern recognition

AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

Directory of Open Access Journals (Sweden)

K. Meena

2013-11-01

Full Text Available Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE, Gamma Intensity Correction (GIC, Normalization chain and Modified Homomorphic Filtering (MHF are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP, Local Derivative Pattern (LDP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.

Mixed Waste Integrated Program interim evaluation report on thermal treatment technologies

International Nuclear Information System (INIS)

Gillins, R.L.; DeWitt, L.M.; Wollerman, A.L.

1993-02-01

The Mixed Waste Integrated Program (MWIP) is one of several US Department of Energy (DOE) integrated programs established to organize and coordinate throughout the DOE complex the development of technologies for treatment of specific waste categories. The goal of the MWIP is to develop and deploy appropriate technologies for -the treatment of DOE mixed low-level and alpha-contaminated wastes in order to bring all affected DOE installations and projects into compliance with environmental laws. Evaluation of treatment technologies by the MWIP will focus on meeting waste form performance requirements for disposal. Thermal treatment technologies were an early emphasis for the MWIP because thermal treatment is indicated (or mandated) for many of the hazardous constituents in DOE mixed waste and because these technologies have been widely investigated for these applications. An advisory group, the Thermal Treatment Working Group (TTWG), was formed during the program's infancy to assist the MWIP in evaluating and prioritizing thermal treatment technologies suitable for development. The results of the overall evaluation scoring indicate that the four highest-rated technologies were rotary kilns, slagging kilns, electric-arc furnaces, and plasma-arc furnaces. The four highest-rated technologies were all judged to be applicable on five of the six waste streams and are the only technologies in the evaluation with this distinction. Conclusions as to the superiority of one technology over others are not valid based on this preliminary study, although some general conclusions can be drawn

Printed Persian Subword Recognition Using Wavelet Packet Descriptors

Directory of Open Access Journals (Sweden)

Samira Nasrollahi

2013-01-01

Full Text Available In this paper, we present a new approach to offline OCR (optical character recognition for printed Persian subwords using wavelet packet transform. The proposed algorithm is used to extract font invariant and size invariant features from 87804 subwords of 4 fonts and 3 sizes. The feature vectors are compressed using PCA. The obtained feature vectors yield a pictorial dictionary for which an entry is the mean of each group that consists of the same subword with 4 fonts in 3 sizes. The sets of these features are congregated by combining them with the dot features for the recognition of printed Persian subwords. To evaluate the feature extraction results, this algorithm was tested on a set of 2000 subwords in printed Persian text documents. An encouraging recognition rate of 97.9% is got at subword level recognition.

Dissemination of Technology to Evaluate Healthy Food Incentive Programs.

Science.gov (United States)

Freedman, Darcy A; Hunt, Alan R; Merritt, Katie; Shon, En-Jung; Pike, Stephanie N

2017-03-01

Federal policy supports increased implementation of monetary incentive interventions for chronic disease prevention among low-income populations. This study describes how a Prevention Research Center, working with a dissemination partner, developed and distributed technology to support nationwide implementation and evaluation of healthy food incentive programming focused on Supplemental Nutrition Assistance Program recipients. FM Tracks, an iOS-based application and website, was developed to standardize evaluation methods for healthy food incentive program implementation at direct-to-consumer markets. This evaluation examined diffusion and adoption of the technology over 9 months (July 2015-March 2016). Data were analyzed in 2016. FM Tracks was disseminated to 273 markets affiliated with 37 regional networks in 18 states and Washington, DC. All markets adopted the sales transaction data collection feature, with nearly all recording at least one Supplemental Nutrition Assistance Program (99.3%) and healthy food incentive (97.1%) transaction. A total of 43,493 sales transactions were recorded. By the ninth month of technology dissemination, markets were entering individual sales transactions using the application (34.5%) and website (29.9%) and aggregated transactions via website (35.6%) at similar rates. Use of optional evaluation features like recording a customer ID with individual transactions increased successively with a low of 22.2% during the first month to a high of 69.2% in the ninth month. Systematic and widely used evaluation technology creates possibilities for pragmatic research embedded within ongoing, real-world implementation of food access interventions. Technology dissemination requires supportive technical assistance and continuous refinement that can be advanced through academic-practitioner partnerships. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Oak Ridge National Laboratory Technology Logic Diagram. Volume 3, Technology evaluation data sheets: Part B, Dismantlement, Remedial action

Energy Technology Data Exchange (ETDEWEB)

1993-09-01

The Oak Ridge National Laboratory Technology Logic Diagram (TLD) was developed to provide a decision support tool that relates environmental restoration (ER) and waste management (WM) problems at Oak Ridge National Laboratory (ORNL) to potential technologies that can remediate these problems. The TLD identifies the research, development, demonstration testing, and evaluation needed to develop these technologies to a state that allows technology transfer and application to decontamination and decommissioning (D&D), remedial action (RA), and WM activities. The TLD consists of three fundamentally separate volumes: Vol. 1, Technology Evaluation; Vol. 2, Technology Logic Diagram and Vol. 3, Technology EvaLuation Data Sheets. Part A of Vols. 1 and 2 focuses on RA. Part B of Vols. 1 and 2 focuses on the D&D of contaminated facilities. Part C of Vols. 1 and 2 focuses on WM. Each part of Vol. 1 contains an overview of the TM, an explanation of the problems facing the volume-specific program, a review of identified technologies, and rankings of technologies applicable to the site. Volume 2 (Pts. A. B. and C) contains the logic linkages among EM goals, environmental problems, and the various technologies that have the potential to solve these problems. Volume 3 (Pts. A. B, and C) contains the TLD data sheets. This volume provides the technology evaluation data sheets (TEDS) for ER/WM activities (D&D, RA and WM) that are referenced by a TEDS code number in Vol. 2 of the TLD. Each of these sheets represents a single logic trace across the TLD. These sheets contain more detail than is given for the technologies in Vol. 2.

A New Framework for Evaluating the Functional Capabilities of Intra-Enterprise Application Integration Technologies

Directory of Open Access Journals (Sweden)

Hossein Moradi

2010-10-01

Full Text Available Enterprise Application Integration (EAI technologies facilitate the sharing of information and business processes of interrelated information systems in order to achieve the target integrated systems. Different EAI solutions and technologies provide various capabilities which lead to the complexity of their evaluation process. To reduce this complexity, appropriate tools for evaluating the functional capabilities of EAI technologies are required. This paper proposes a new framework for evaluating the functional capabilities of EAI technologies, which simplify the process of evaluating the functional capabilities of intra-enterprise integration technologies and solutions.The proposed framework for evaluating the EAI technologies was enhanced using the structural and conceptual aspects of previous frameworks. It offers a new schema for which various EAI technologies are categorized in different classes and are evaluated based on their supporting level for functional integration capabilities’ criteria.The new framework offers two lists containing integration technologies and their associated classifications, and functional capabilities of integration technologies. The proposed framework is a novel one which can be used by information system experts for evaluation and comparison purposes of various integration technologies.

The review and results of different methods for facial recognition

Science.gov (United States)

Le, Yifan

2017-09-01

In recent years, facial recognition draws much attention due to its wide potential applications. As a unique technology in Biometric Identification, facial recognition represents a significant improvement since it could be operated without cooperation of people under detection. Hence, facial recognition will be taken into defense system, medical detection, human behavior understanding, etc. Several theories and methods have been established to make progress in facial recognition: (1) A novel two-stage facial landmark localization method is proposed which has more accurate facial localization effect under specific database; (2) A statistical face frontalization method is proposed which outperforms state-of-the-art methods for face landmark localization; (3) It proposes a general facial landmark detection algorithm to handle images with severe occlusion and images with large head poses; (4) There are three methods proposed on Face Alignment including shape augmented regression method, pose-indexed based multi-view method and a learning based method via regressing local binary features. The aim of this paper is to analyze previous work of different aspects in facial recognition, focusing on concrete method and performance under various databases. In addition, some improvement measures and suggestions in potential applications will be put forward.

Speech Recognition

Directory of Open Access Journals (Sweden)

Adrian Morariu

2009-01-01

Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

Recognition of edible oil by using BP neural network and laser induced fluorescence spectrum

Science.gov (United States)

Mu, Tao-tao; Chen, Si-ying; Zhang, Yin-chao; Guo, Pan; Chen, He; Zhang, Hong-yan; Liu, Xiao-hua; Wang, Yuan; Bu, Zhi-chao

2013-09-01

In order to accomplish recognition of the different edible oil we set up a laser induced fluorescence spectrum system in the laboratory based on Laser induced fluorescence spectrum technology, and then collect the fluorescence spectrum of different edible oil by using that system. Based on this, we set up a fluorescence spectrum database of different cooking oil. It is clear that there are three main peak position of different edible oil from fluorescence spectrum chart. Although the peak positions of all cooking oil were almost the same, the relative intensity of different edible oils was totally different. So it could easily accomplish that oil recognition could take advantage of the difference of relative intensity. Feature invariants were extracted from the spectrum data, which were chosen from the fluorescence spectrum database randomly, before distinguishing different cooking oil. Then back propagation (BP) neural network was established and trained by the chosen data from the spectrum database. On that basis real experiment data was identified by BP neural network. It was found that the overall recognition rate could reach as high as 83.2%. Experiments showed that the laser induced fluorescence spectrum of different cooking oil was very different from each other, which could be used to accomplish the oil recognition. Laser induced fluorescence spectrum technology, combined BP neural network，was fast, high sensitivity, non-contact, and high recognition rate. It could become a new technique to accomplish the edible oil recognition and quality detection.

Automatic anatomy recognition via multiobject oriented active shape models.

Science.gov (United States)

Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A

2010-12-01

This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a

PALESTINE AUTOMOTIVE LICENSE IDENTITY RECOGNITION FOR INTELLIGENT PARKING SYSTEM

OpenAIRE

ANEES ABU SNEINEH; WAEL A. SALAH

2017-01-01

Providing employees with protection and security is one of the key concerns of any organization. This goal can be implemented mainly by managing and protecting employees’ cars in the parking area. Therefore, a parking area must be managed and organized with smart technologies and tools that can be applied and integrated in an intelligent parking system. This paper presents the tools based on image recognition technology that can be used to effectively control various parts of a parking sys...

Clinical Simulation: A Protocol for Evaluation of Mobile Technology.

Science.gov (United States)

Mather, Carey; Jensen, Sanne; Cummings, Elizabeth

2017-01-01

For mobile technology to be accepted at point of care in healthcare environments there is a need to demonstrate benefits whilst ameliorating the risks and challenges. To provide a standardised approach to evaluation of mobile technology a simulation protocol was developed to provide guidance for its use in healthcare environments. Simulated conditions provide the opportunity to assess intended and unintended consequences and identify potential workarounds when using technology. The protocol can also be used to demonstrate the importance of the development of digital professionalism by end-users prior to students entering the clinical practice setting. The mobile technology protocol was adapted from a health information systems protocol developed and used at the ITX Lab, Denmark for use in other simulation laboratories. Use case scenarios were developed to enable evaluation of mobile technology for mobile learning of nurses, nurse supervisors, students and patients. The scenarios can be used in a range of simulated environments including hospital bedside, outpatient clinic or community settings. A case study exemplar of a nurse and patient is included to demonstrate how the mobile technology protocol can be applied.

Improving Protein Fold Recognition by Deep Learning Networks

Science.gov (United States)

Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-01

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl’s benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Improving Protein Fold Recognition by Deep Learning Networks.

Science.gov (United States)

Jo, Taeho; Hou, Jie; Eickholt, Jesse; Cheng, Jianlin

2015-12-04

For accurate recognition of protein folds, a deep learning network method (DN-Fold) was developed to predict if a given query-template protein pair belongs to the same structural fold. The input used stemmed from the protein sequence and structural features extracted from the protein pair. We evaluated the performance of DN-Fold along with 18 different methods on Lindahl's benchmark dataset and on a large benchmark set extracted from SCOP 1.75 consisting of about one million protein pairs, at three different levels of fold recognition (i.e., protein family, superfamily, and fold) depending on the evolutionary distance between protein sequences. The correct recognition rate of ensembled DN-Fold for Top 1 predictions is 84.5%, 61.5%, and 33.6% and for Top 5 is 91.2%, 76.5%, and 60.7% at family, superfamily, and fold levels, respectively. We also evaluated the performance of single DN-Fold (DN-FoldS), which showed the comparable results at the level of family and superfamily, compared to ensemble DN-Fold. Finally, we extended the binary classification problem of fold recognition to real-value regression task, which also show a promising performance. DN-Fold is freely available through a web server at http://iris.rnet.missouri.edu/dnfold.

Recognition and Toleration

DEFF Research Database (Denmark)

Lægaard, Sune

2010-01-01

Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...... or interpretations of recognition and toleration are considered, confusing and problematic uses of the terms are noted, and the compatibility of toleration and recognition is discussed. The article argues that there is a range of legitimate and importantly different conceptions of both toleration and recognition...

Object recognition memory in zebrafish.

Science.gov (United States)

May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James

2016-01-01

The novel object recognition, or novel-object preference (NOP) test is employed to assess recognition memory in a variety of organisms. The subject is exposed to two identical objects, then after a delay, it is placed back in the original environment containing one of the original objects and a novel object. If the subject spends more time exploring one object, this can be interpreted as memory retention. To date, this test has not been fully explored in zebrafish (Danio rerio). Zebrafish possess recognition memory for simple 2- and 3-dimensional geometrical shapes, yet it is unknown if this translates to complex 3-dimensional objects. In this study we evaluated recognition memory in zebrafish using complex objects of different sizes. Contrary to rodents, zebrafish preferentially explored familiar over novel objects. Familiarity preference disappeared after delays of 5 mins. Leopard danios, another strain of D. rerio, also preferred the familiar object after a 1 min delay. Object preference could be re-established in zebra danios by administration of nicotine tartrate salt (50mg/L) prior to stimuli presentation, suggesting a memory-enhancing effect of nicotine. Additionally, exploration biases were present only when the objects were of intermediate size (2 × 5 cm). Our results demonstrate zebra and leopard danios have recognition memory, and that low nicotine doses can improve this memory type in zebra danios. However, exploration biases, from which memory is inferred, depend on object size. These findings suggest zebrafish ecology might influence object preference, as zebrafish neophobia could reflect natural anti-predatory behaviour. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of noise and other factors on speech recognition in anaesthesia

DEFF Research Database (Denmark)

Alapetite, Alexandre

2008-01-01

of training. Methods: Eight volunteers read aloud a total of about 3 600 typical short anaesthesia comments to be transcribed by a continuous speech recognition system. Background noises were collected in an operating room and reproduced. A regression analysis and descriptive statistics were done to evaluate...... operations. Objective: The aim of the experiment is to evaluate the relative impact of several factors affecting speech recognition when used in operating rooms, such as the type or loudness of background noises, type of microphone, type of recognition mode (free speech versus command mode), and type...... the relative effect of various factors. Results: Some factors have a major impact, such as the words to be recognised, the type of recognition, and participants. The type of microphone is especially significant when combined with the type of noise. While loud noises in the operating room can have a predominant...

Learning and Treatment of Anaphylaxis by Laypeople: A Simulation Study Using Pupilar Technology

Directory of Open Access Journals (Sweden)

Felipe Fernandez-Mendez

2017-01-01

Full Text Available An anaphylactic shock is a time-critical emergency situation. The decision-making during emergencies is an important responsibility but difficult to study. Eye-tracking technology allows us to identify visual patterns involved in the decision-making. The aim of this pilot study was to evaluate two training models for the recognition and treatment of anaphylaxis by laypeople, based on expert assessment and eye-tracking technology. A cross-sectional quasi-experimental simulation study was made to evaluate the identification and treatment of anaphylaxis. 50 subjects were randomly assigned to four groups: three groups watching different training videos with content supervised by sanitary personnel and one control group who received face-to-face training during paediatric practice. To evaluate the learning, a simulation scenario represented by an anaphylaxis’ victim was designed. A device capturing eye movement as well as expert valuation was used to evaluate the performance. The subjects that underwent paediatric face-to-face training achieved better and faster recognition of the anaphylaxis. They also used the adrenaline injector with better precision and less mistakes, and they needed a smaller number of visual fixations to recognise the anaphylaxis and to make the decision to inject epinephrine. Analysing the different video formats, mixed results were obtained. Therefore, they should be tested to evaluate their usability before implementation.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Min Beom Lee

2017-12-01

Full Text Available In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user’s eyes looking somewhere else, not into the front of the camera, specular reflection (SR and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs. Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II training dataset (selected from the university of Beira iris (UBIRIS.v2 database, mobile iris challenge evaluation (MICHE database, and institute of automation of Chinese academy of sciences (CASIA-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks.

Science.gov (United States)

Lee, Min Beom; Hong, Hyung Gil; Park, Kang Ryoung

2017-12-17

In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user's eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

EPA [Environmental Protection Agency] SITE [Superfund Innovative Technology Evaluation] program seeks technology proposals

International Nuclear Information System (INIS)

Anon.

1989-01-01

EPA will issue an RFP to initiate the SITE-005 solicitation for demonstration of technologies under the Superfund Innovative Technology Evaluation (SITE) Program. This portion of the SITE program offers a mechanism for conducting a joint technology demonstration between EPA and the private sector. The goal of the demonstration program is to provide an opportunity for developers to demonstrate the performance of their technologies on actual hazardous wastes at Superfund sites, and to provide accurate and reliable data on that performance. Technologies selected must be of commercial scale and provide solutions to problems encountered at Superfund Sites. Primary emphasis in the RFP is on technologies that address: treatment of mixed, low level radioactive wastes in soils and groundwater; treatment of soils and sludges contaminated with organics and/or inorganics, materials handling as a preliminary step to treatment or further processing, treatment trains designed to handle specific wastes, are in situ technologies, especially those processes providing alternatives to conventional groundwater pump and treat techniques

Human-assisted sound event recognition for home service robots.

Science.gov (United States)

Do, Ha Manh; Sheng, Weihua; Liu, Meiqin

This paper proposes and implements an open framework of active auditory learning for a home service robot to serve the elderly living alone at home. The framework was developed to realize the various auditory perception capabilities while enabling a remote human operator to involve in the sound event recognition process for elderly care. The home service robot is able to estimate the sound source position and collaborate with the human operator in sound event recognition while protecting the privacy of the elderly. Our experimental results validated the proposed framework and evaluated auditory perception capabilities and human-robot collaboration in sound event recognition.

GIS technology in regional recognition of the distribution pattern of multifloral honey: The chemical traits in Serbia

Directory of Open Access Journals (Sweden)

Radović D.I.

2014-01-01

Full Text Available GIS is a computer-based system to input, store, manipulate, analyze and output spatially referenced data. There is a huge range application of GIS that generally sets out to fulfill: mapping, measurement, monitoring, modeling and management. In this study, GIS technology was used for the regional recognition of origin and distribution patterns of multifloral honey chemical traits in Serbia. This included organizing and analyzing the spatial and attributive data of 164 honey samples collected from different regions of Serbia during the harvesting season of 2009. Multifloral honey was characterized in regards to mineral composition, sugar content and basic physicochemical properties. The kriging method of Geostatistical Analyst was used for interpolation to predict values of a sampled variable over the whole territory of Serbia. [Projekat Ministarstva nauke Republike Srbije, br. III 46002, OI 172017 and 451-03-2372-IP Type 1/107

A study on facial expressions recognition

Science.gov (United States)

Xu, Jingjing

2017-09-01

In terms of communication, postures and facial expressions of such feelings like happiness, anger and sadness play important roles in conveying information. With the development of the technology, recently a number of algorithms dealing with face alignment, face landmark detection, classification, facial landmark localization and pose estimation have been put forward. However, there are a lot of challenges and problems need to be fixed. In this paper, a few technologies have been concluded and analyzed, and they all relate to handling facial expressions recognition and poses like pose-indexed based multi-view method for face alignment, robust facial landmark detection under significant head pose and occlusion, partitioning the input domain for classification, robust statistics face formalization.

Early economic evaluation of emerging health technologies: protocol of a systematic review

Science.gov (United States)

2014-01-01

Background The concept of early health technology assessment, discussed well over a decade, has now been collaboratively implemented by industry, government, and academia to select and expedite the development of emerging technologies that may address the needs of patients and health systems. Early economic evaluation is essential to assess the value of emerging technologies, but empirical data to inform the current practice of early evaluation is limited. We propose a systematic review of early economic evaluation studies in order to better understand the current practice. Methods/design This protocol describes a systematic review of economic evaluation studies of regulated health technologies in which the evaluation is conducted prior to regulatory approval and when the technology effectiveness is not well established. Included studies must report an economic evaluation, defined as the comparative analysis of alternatives with respect to their associated costs and health consequences, and must evaluate some regulated health technology such as pharmaceuticals, biologics, high-risk medical devices, or biomarkers. We will conduct the literature search on multiple databases, including MEDLINE, EMBASE, the Centre for Reviews and Dissemination Databases, and EconLit. Additional citations will be identified via scanning reference lists and author searching. We suspect that many early economic evaluation studies are unpublished, especially those conducted for internal use only. Additionally, we use a chain-referral sampling approach to identify authors of unpublished studies who work in technology discovery and development, starting out with our contact lists and authors who published relevant studies. Citation screening and full-text review will be conducted by pairs of reviewers. Abstracted data will include those related to the decision context and decision problem of the early evaluation, evaluation methods (e.g., data sources, methods, and assumptions used to

Preparing Pre-Service Teachers to Integrate Technology into K-12 Instruction: Evaluation of a Technology-Infused Approach

Science.gov (United States)

Admiraal, Wilfried; van Vugt, Felix; Kranenburg, Frans; Koster, Bob; Smit, Ben; Weijers, Sanne; Lockhorst, Ditte

2017-01-01

The quality of how technology is addressed in teacher education programmes is conditional for how student teachers apply technology in secondary schools after their graduation. Two technology-infused courses of one teacher education programme were evaluated. In line with studies on the development of pre-service teachers' technological,…

DEMONSTRATION OF AQUAFIX AND SAPS PASSIVE MINE WATER TREATMENT TECHNOLOGIES AT SUMMITVILLE MINE SITE, INNOVATIVE TECHNOLOGY EVALUATION REPORT

Science.gov (United States)

As part of the Superfund Innovative Technology Evaluation (SITE) Program, the U.S. Environmental Protection Agency evaluated two passive water treatment (PWT) technologies for metals removal from acid mine drainage (AMD) at the Summitville Mine Superfund Site in southern Colorado...

Teach Your Computer to Read: Scanners and Optical Character Recognition.

Science.gov (United States)

Marsden, Jim

1993-01-01

Desktop scanners can be used with a software technology called optical character recognition (OCR) to convert the text on virtually any paper document into an electronic form. OCR offers educators new flexibility in incorporating text into tests, lesson plans, and other materials. (MLF)

Automatic Facial Expression Recognition and Operator Functional State

Science.gov (United States)

Blanson, Nina

2012-01-01

The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions

Automatic Facial Expression Recognition and Operator Functional State

Science.gov (United States)

Blanson, Nina

2011-01-01

The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

Face Recognition Using Local Quantized Patterns and Gabor Filters

Science.gov (United States)

Khryashchev, V.; Priorov, A.; Stepanova, O.; Nikitin, A.

2015-05-01

The problem of face recognition in a natural or artificial environment has received a great deal of researchers' attention over the last few years. A lot of methods for accurate face recognition have been proposed. Nevertheless, these methods often fail to accurately recognize the person in difficult scenarios, e.g. low resolution, low contrast, pose variations, etc. We therefore propose an approach for accurate and robust face recognition by using local quantized patterns and Gabor filters. The estimation of the eye centers is used as a preprocessing stage. The evaluation of our algorithm on different samples from a standardized FERET database shows that our method is invariant to the general variations of lighting, expression, occlusion and aging. The proposed approach allows about 20% correct recognition accuracy increase compared with the known face recognition algorithms from the OpenCV library. The additional use of Gabor filters can significantly improve the robustness to changes in lighting conditions.

Adaptive Self-Occlusion Behavior Recognition Based on pLSA

Directory of Open Access Journals (Sweden)

Hong-bin Tu

2013-01-01

Full Text Available Human action recognition is an important area of human action recognition research. Focusing on the problem of self-occlusion in the field of human action recognition, a new adaptive occlusion state behavior recognition approach was presented based on Markov random field and probabilistic Latent Semantic Analysis (pLSA. Firstly, the Markov random field was used to represent the occlusion relationship between human body parts in terms an occlusion state variable by phase space obtained. Then, we proposed a hierarchical area variety model. Finally, we use the topic model of pLSA to recognize the human behavior. Experiments were performed on the KTH, Weizmann, and Humaneva dataset to test and evaluate the proposed method. The compared experiment results showed that what the proposed method can achieve was more effective than the compared methods.

Recognition and Synthesis of Human Movements by Parametric HMMs

DEFF Research Database (Denmark)

Herzog, Dennis; Krüger, Volker

2009-01-01

The representation of human movements for recognition and synthesis is important in many application fields such as: surveillance, human-computer interaction, motion capture, and humanoid robots. Hidden Markov models (HMMs) are a common statistical framework in this context, since...... on the recognition and synthesis of human arm movements. Furthermore, we will show in various experiments the use of PHMMs for the control of a humanoid robot by synthesizing movements for relocating objects at arbitrary positions. In vision-based interaction experiments, PHMM are used for the recognition...... of pointing movements, where the recognized parameterization conveys to a robot the important information which object to relocate and where to put it. Finally, we evaluate the accuracy of recognition and synthesis for pointing and grasping arm movements and discuss that the precision of the synthesis...

On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment.

Science.gov (United States)

Cicirelli, Franco; Fortino, Giancarlo; Giordano, Andrea; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea

2016-09-01

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.

Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial.

Science.gov (United States)

Vogel, Markus; Kaisers, Wolfgang; Wassmuth, Ralf; Mayatepek, Ertan

2015-11-03

Clinical documentation has undergone a change due to the usage of electronic health records. The core element is to capture clinical findings and document therapy electronically. Health care personnel spend a significant portion of their time on the computer. Alternatives to self-typing, such as speech recognition, are currently believed to increase documentation efficiency and quality, as well as satisfaction of health professionals while accomplishing clinical documentation, but few studies in this area have been published to date. This study describes the effects of using a Web-based medical speech recognition system for clinical documentation in a university hospital on (1) documentation speed, (2) document length, and (3) physician satisfaction. Reports of 28 physicians were randomized to be created with (intervention) or without (control) the assistance of a Web-based system of medical automatic speech recognition (ASR) in the German language. The documentation was entered into a browser's text area and the time to complete the documentation including all necessary corrections, correction effort, number of characters, and mood of participant were stored in a database. The underlying time comprised text entering, text correction, and finalization of the documentation event. Participants self-assessed their moods on a scale of 1-3 (1=good, 2=moderate, 3=bad). Statistical analysis was done using permutation tests. The number of clinical reports eligible for further analysis stood at 1455. Out of 1455 reports, 718 (49.35%) were assisted by ASR and 737 (50.65%) were not assisted by ASR. Average documentation speed without ASR was 173 (SD 101) characters per minute, while it was 217 (SD 120) characters per minute using ASR. The overall increase in documentation speed through Web-based ASR assistance was 26% (P=.04). Participants documented an average of 356 (SD 388) characters per report when not assisted by ASR and 649 (SD 561) characters per report when assisted

Evaluation of technological measures to cope with climate change

Energy Technology Data Exchange (ETDEWEB)

Shimizu, Hiroshi; Moriguchi, Yulchi [National Inst. for Environmental Studies, Onogawa Tsukuba (Japan)

1993-12-31

Because the global warming (climate change) is recognized as a highly probable phenomenon in the next century, the countermeasures to cope with this issue is really Important. International discussion Is progressing towards the conclusion of the treaty to stabilize global warming. Therefore, now is the time to take concrete action to reduce the emission to the greenhouse gases (GHG). To find the way to reduce the emission of the GHG, the procedure as next should be taken. (1) Systematic estimation of GHG emission (GHG analysis), (2) Identification of conventional and Innovative technologies, (3) Assessment of individual sectoral technologies, (4) Comprehensive evaluation of countermeasures as a whole. Both in the U.S.A. and Japan, this kind of research have been made independently. Among these processes, the standard methodologies should be established on the GHG analysis, the assessment of individual technologies and the comprehensive evaluation. From such a background, it is important to discuss the way to evaluate technological measures to cope with climate change between the specialist from the U.S.A. and Japan. And still required to search the possibility to establish a joint project between both countries.

A new concept of vertically integrated pattern recognition associative memory

International Nuclear Information System (INIS)

Liu, Ted; Hoff, Jim; Deptuch, Grzegorz; Yarema, Ray

2011-01-01

Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing fast pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Scaling of current technologies is unlikely to satisfy the scientific needs of the future, and investments in transformational new technologies need to be made. In this paper, we will discuss a new concept of using the emerging 3D vertical integration technology to significantly advance the state-of-the-art for fast pattern recognition within and outside HEP. A generic R and D proposal based on this new concept, with a few institutions involved, has recently been submitted to DOE with the goal to design and perform the ASIC engineering necessary to realize a prototype device. The progress of this R and D project will be reported in the future. Here we will only focus on the concept of this new approach.

Re-thinking employee recognition: understanding employee experiences of recognition

OpenAIRE

Smith, Charlotte

2013-01-01

Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...

Research on Recognition and Evaluation of Traffic Guide Sign

OpenAIRE

Li Yuan; Ming-jie Cai; Tang-yi Guo; Yu Jiang

2015-01-01

Traffic guide signs are effective only when they are clearly recognized by drivers. Three experiments were conducted in this study. In the first, the influence factors of guide sign recognition were studied. This study investigated 11 main factors with a convenience sample of drivers from Nanjing city in China. Weights of different influence factors were obtained through analytic hierarchy process (AHP). The results showed that the setting position, occlusion degree, and character size of gui...

Simulation studies for the evaluation of health information technologies

DEFF Research Database (Denmark)

Ammenwerth, Elske; Hackl, Werner; Binzer, Kristine

2012-01-01

It is essential for new health information technologies (IT) to undergo rigorous evaluations to ensure they are effective and safe for use in real-world situations. However, evaluation of new health IT is challenging, as field studies are often not feasible when the technology being evaluated...... is not sufficiently mature. Laboratory-based evaluations have also been shown to have insufficient external validity. Simulation studies seem to be a way to bridge this gap. The aim of this study was to evaluate, using a simulation methodology, the impact of a new prototype of an electronic medication management...... system on the appropriateness of prescriptions and drugrelated activities, including laboratory test ordering or medication changes. This article presents the results of a controlled simulation study with 50 simulation runs, including ten doctors and five simulation patients, and discusses experiences...

Sonographic Diagnosis of Tubal Cancer with IOTA Simple Rules Plus Pattern Recognition

Science.gov (United States)

Tongsong, Theera; Wanapirak, Chanane; Tantipalakorn, Charuwan; Tinnangwattana, Dangcheewan

2017-11-26

Objective: To evaluate diagnostic performance of IOTA simple rules plus pattern recognition in predicting tubal cancer. Methods: Secondary analysis was performed on prospective database of our IOTA project. The patients recruited in the project were those who were scheduled for pelvic surgery due to adnexal masses. The patients underwent ultrasound examinations within 24 hours before surgery. On ultrasound examination, the masses were evaluated using the well-established IOTA simple rules plus pattern recognition (sausage-shaped appearance, incomplete septum, visible ipsilateral ovaries) to predict tubal cancer. The gold standard diagnosis was based on histological findings or operative findings. Results: A total of 482 patients, including 15 cases of tubal cancer, were evaluated by ultrasound preoperatively. The IOTA simple rules plus pattern recognition gave a sensitivity of 86.7% (13 in 15) and specificity of 97.4%. Sausage-shaped appearance was identified in nearly all cases (14 in 15). Incomplete septa and normal ovaries could be identified in 33.3% and 40%, respectively. Conclusion: IOTA simple rules plus pattern recognition is relatively effective in predicting tubal cancer. Thus, we propose the simple scheme in diagnosis of tubal cancer as follows. First of all, the adnexal masses are evaluated with IOTA simple rules. If the B-rules could be applied, tubal cancer is reliably excluded. If the M-rules could be applied or the result is inconclusive, careful delineation of the mass with pattern recognition should be performed. Creative Commons Attribution License

Emotion recognition pattern in adolescent boys with attention-deficit/hyperactivity disorder.

Science.gov (United States)

Aspan, Nikoletta; Bozsik, Csilla; Gadoros, Julia; Nagy, Peter; Inantsy-Pap, Judit; Vida, Peter; Halasz, Jozsef

2014-01-01

Social and emotional deficits were recently considered as inherent features of individuals with attention-deficit hyperactivity disorder (ADHD), but only sporadic literature data exist on emotion recognition in adolescents with ADHD. The aim of the present study was to establish emotion recognition profile in adolescent boys with ADHD in comparison with control adolescents. Forty-four adolescent boys (13-16 years) participated in the study after informed consent; 22 boys had a clinical diagnosis of ADHD, while data were also assessed from 22 adolescent control boys matched for age and Raven IQ. Parent- and self-reported behavioral characteristics were assessed by the means of the Strengths and Difficulties Questionnaire. The recognition of six basic emotions was evaluated by the "Facial Expressions of Emotion-Stimuli and Tests." Compared to controls, adolescents with ADHD were more sensitive in the recognition of disgust and, worse in the recognition of fear and showed a tendency for impaired recognition of sadness. Hyperactivity measures showed an inverse correlation with fear recognition. Our data suggest that adolescent boys with ADHD have alterations in the recognition of specific emotions.

X-231B technology demonstration for in situ treatment of contaminated soil: Technology evaluation and screening

International Nuclear Information System (INIS)

Siegrist, R.L.; Morris, M.I.; Donaldson, T.L.; Palumbo, A.V.; Herbes, S.E.; Jenkins, R.A.; Morrissey, C.M.; Harris, M.T.

1993-08-01

The Portsmouth Gaseous Diffusion Plant (Ports) is located approximately 70 miles south of Columbus in southern Ohio. Among the several waste management units on the facility, the X-231B unit consists of two adjacent oil biodegradation plots. The plots encompass ∼ 0.8 acres and were reportedly used from 1976 to 1983 for the treatment and disposal of waste oils and degreasing solvents, some containing uranium-235 and technetium-99. The X-231B unit is a regulated solid waste management unit (SWMU) under the Resource Conservation and Recovery Act (RCRA). The X-231B unit is also a designated SWMU located within Quadrant I of the site as defined in an ongoing RCRA Facilities Investigation and Corrective Measures Study (RFI/CMS). Before implementing one or more Technology Demonstration Project must be completed. The principal goal of this project was to elect and successfully demonstrate one ore more technologies for effective treatment of the contaminated soils associated with the X-231B unit at PORTS. The project was divided into two major phases. Phase 1 involved a technology evaluation and screening process. The second phase (i.e., Phase 2) was to involve field demonstration, testing and evaluation of the technology(s) selected during Phase 1. This report presents the methods, results, and conclusions of the technology evaluation and screening portion of the project

FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

Directory of Open Access Journals (Sweden)

T. Pasupathi

2014-05-01

Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

Iris recognition as a biometric method after cataract surgery

Directory of Open Access Journals (Sweden)

Roizenblatt Jaime

2004-01-01

Full Text Available Abstract Background Biometric methods are security technologies, which use human characteristics for personal identification. Iris recognition systems use iris textures as unique identifiers. This paper presents an analysis of the verification of iris identities after intra-ocular procedures, when individuals were enrolled before the surgery. Methods Fifty-five eyes from fifty-five patients had their irises enrolled before a cataract surgery was performed. They had their irises verified three times before and three times after the procedure, and the Hamming (mathematical distance of each identification trial was determined, in a controlled ideal biometric environment. The mathematical difference between the iris code before and after the surgery was also compared to a subjective evaluation of the iris anatomy alteration by an experienced surgeon. Results A correlation between visible subjective iris texture alteration and mathematical difference was verified. We found only six cases in which the eye was no more recognizable, but these eyes were later reenrolled. The main anatomical changes that were found in the new impostor eyes are described. Conclusions Cataract surgeries change iris textures in such a way that iris recognition systems, which perform mathematical comparisons of textural biometric features, are able to detect these changes and sometimes even discard a pre-enrolled iris considering it an impostor. In our study, re-enrollment proved to be a feasible procedure.

Learning From Tests: Facilitation of Delayed Recall by Initial Recognition Alternatives.

Science.gov (United States)

Whitten, William B., II; Leonard, Janet Mauriello

1980-01-01

Two experiments were designed to determine the effects of multiple-choice recognition test alternatives on subsequent memory for the correct answers. Results of both experiments are interpreted as demonstrations of the principle that long-term retention is facilitated such that memory evaluation occurs during initial recognition tests. (Author/RD)

[Information technology in learning sign language].

Science.gov (United States)

Hernández, Cesar; Pulido, Jose L; Arias, Jorge E

2015-01-01

To develop a technological tool that improves the initial learning of sign language in hearing impaired children. The development of this research was conducted in three phases: the lifting of requirements, design and development of the proposed device, and validation and evaluation device. Through the use of information technology and with the advice of special education professionals, we were able to develop an electronic device that facilitates the learning of sign language in deaf children. This is formed mainly by a graphic touch screen, a voice synthesizer, and a voice recognition system. Validation was performed with the deaf children in the Filadelfia School of the city of Bogotá. A learning methodology was established that improves learning times through a small, portable, lightweight, and educational technological prototype. Tests showed the effectiveness of this prototype, achieving a 32 % reduction in the initial learning time for sign language in deaf children.

Application research for 4D technology in flood forecasting and evaluation

Science.gov (United States)

Li, Ziwei; Liu, Yutong; Cao, Hongjie

1998-08-01

In order to monitor the region which disaster flood happened frequently in China, satisfy the great need of province governments for high accuracy monitoring and evaluated data for disaster and improve the efficiency for repelling disaster, under the Ninth Five-year National Key Technologies Programme, the method was researched for flood forecasting and evaluation using satellite and aerial remoted sensed image and land monitor data. The effective and practicable flood forecasting and evaluation system was established and DongTing Lake was selected as the test site. Modern Digital photogrammetry, remote sensing and GIS technology was used in this system, the disastrous flood could be forecasted and loss can be evaluated base on '4D' (DEM -- Digital Elevation Model, DOQ -- Digital OrthophotoQuads, DRG -- Digital Raster Graph, DTI -- Digital Thematic Information) disaster background database. The technology of gathering and establishing method for '4D' disaster environment background database, application technology for flood forecasting and evaluation based on '4D' background data and experimental results for DongTing Lake test site were introduced in detail in this paper.

Oak Ridge National Laboratory Technology Logic Diagram. Volume 3, Technology evaluation data sheets: Part C, Robotics/automation, Waste management

Energy Technology Data Exchange (ETDEWEB)

1993-09-01

The Oak Ridge National Laboratory Technology Logic Diagram (TLD) was developed to provide a decision support tool that relates environmental restoration (ER) and waste management (WM) problems at Oak Ridge National Laboratory (ORNL) to potential technologies that can remediate these problems. The TLD identifies the research, development, demonstration testing, and evaluation needed to develop these technologies to a state that allows technology transfer and application to decontamination and decommissioning (D&D), remedial action (RA), and WM activities. The TLD consists of three fundamentally separate volumes: Vol. 1, Technology Evaluation; Vol. 2, Technology Logic Diagram and Vol. 3, Technology EvaLuation Data Sheets. Part A of Vols. 1 and 2 focuses on RA. Part B of Vols. 1 and 2 focuses on the D&D of contaminated facilities. Part C of Vols. 1 and 2 focuses on WM. Each part of Vol. 1 contains an overview of the TM, an explanation of the problems facing the volume-specific program, a review of identified technologies, and rankings of technologies applicable to the site. Volume 2 (Pts. A. B. and C) contains the logic linkages among EM goals, environmental problems, and the various technologies that have the potential to solve these problems. Volume 3 (Pts. A. B, and C) contains the TLD data sheets. This volume provides the technology evaluation data sheets (TEDS) for ER/WM activities (D&D, RA and WM) that are referenced by a TEDS code number in Vol. 2 of the TLD. Each of these sheets represents a single logic trace across the TLD. These sheets contain more detail than is given for the technologies in Vol. 2.

Graphical symbol recognition

OpenAIRE

K.C. , Santosh; Wendling , Laurent

2015-01-01

International audience; The chapter focuses on one of the key issues in document image processing i.e., graphical symbol recognition. Graphical symbol recognition is a sub-field of a larger research domain: pattern recognition. The chapter covers several approaches (i.e., statistical, structural and syntactic) and specially designed symbol recognition techniques inspired by real-world industrial problems. It, in general, contains research problems, state-of-the-art methods that convey basic s...

Multimodal approaches for emotion recognition: a survey

Science.gov (United States)

Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

2005-01-01

Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

Real-Time Hand Posture Recognition Using a Range Camera

Science.gov (United States)

Lahamy, Herve

The basic goal of human computer interaction is to improve the interaction between users and computers by making computers more usable and receptive to the user's needs. Within this context, the use of hand postures in replacement of traditional devices such as keyboards, mice and joysticks is being explored by many researchers. The goal is to interpret human postures via mathematical algorithms. Hand posture recognition has gained popularity in recent years, and could become the future tool for humans to interact with computers or virtual environments. An exhaustive description of the frequently used methods available in literature for hand posture recognition is provided. It focuses on the different types of sensors and data used, the segmentation and tracking methods, the features used to represent the hand postures as well as the classifiers considered in the recognition process. Those methods are usually presented as highly robust with a recognition rate close to 100%. However, a couple of critical points necessary for a successful real-time hand posture recognition system require major improvement. Those points include the features used to represent the hand segment, the number of postures simultaneously recognizable, the invariance of the features with respect to rotation, translation and scale and also the behavior of the classifiers against non-perfect hand segments for example segments including part of the arm or missing part of the palm. A 3D time-of-flight camera named SR4000 has been chosen to develop a new methodology because of its capability to provide in real-time and at high frame rate 3D information on the scene imaged. This sensor has been described and evaluated for its capability for capturing in real-time a moving hand. A new recognition method that uses the 3D information provided by the range camera to recognize hand postures has been proposed. The different steps of this methodology including the segmentation, the tracking, the hand

A Malaysian Vehicle License Plate Localization and Recognition System

Directory of Open Access Journals (Sweden)

Ganapathy Velappa

2008-02-01

Full Text Available Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services, secure usage of parking houses and also to prevent car theft issues. The proposed license plate localization algorithm is based on a combination of morphological processes with a modified Hough Transform approach and the recognition of the license plates is achieved by the implementation of the feed-forward backpropagation artificial neural network. Experimental results show an average of 95% successful license plate localization and recognition in a total of 589 images captured from a complex outdoor environment.

Collecting and evaluating speech recognition corpora for nine Southern Bantu languages

CSIR Research Space (South Africa)

Badenhorst, JAC

2009-03-01

Full Text Available The authors describes the Lwazi corpus for automatic speech recognition (ASR), a new telephone speech corpus which includes data from nine Southern Bantu languages. Because of practical constraints, the amount of speech per language is relatively...

Brain Structural Correlates of Emotion Recognition in Psychopaths.

Directory of Open Access Journals (Sweden)

Vanessa Pera-Guardiola

Full Text Available Individuals with psychopathy present deficits in the recognition of facial emotional expressions. However, the nature and extent of these alterations are not fully understood. Furthermore, available data on the functional neural correlates of emotional face recognition deficits in adult psychopaths have provided mixed results. In this context, emotional face morphing tasks may be suitable for clarifying mild and emotion-specific impairments in psychopaths. Likewise, studies exploring corresponding anatomical correlates may be useful for disentangling available neurofunctional evidence based on the alleged neurodevelopmental roots of psychopathic traits. We used Voxel-Based Morphometry and a morphed emotional face expression recognition task to evaluate the relationship between regional gray matter (GM volumes and facial emotion recognition deficits in male psychopaths. In comparison to male healthy controls, psychopaths showed deficits in the recognition of sad, happy and fear emotional expressions. In subsequent brain imaging analyses psychopaths with better recognition of facial emotional expressions showed higher volume in the prefrontal cortex (orbitofrontal, inferior frontal and dorsomedial prefrontal cortices, somatosensory cortex, anterior insula, cingulate cortex and the posterior lobe of the cerebellum. Amygdala and temporal lobe volumes contributed to better emotional face recognition in controls only. These findings provide evidence suggesting that variability in brain morphometry plays a role in accounting for psychopaths' impaired ability to recognize emotional face expressions, and may have implications for comprehensively characterizing the empathy and social cognition dysfunctions typically observed in this population of subjects.

Use of digital speech recognition in diagnostics radiology

International Nuclear Information System (INIS)

Arndt, H.; Stockheim, D.; Mutze, S.; Petersein, J.; Gregor, P.; Hamm, B.

1999-01-01

Purpose: Applicability and benefits of digital speech recognition in diagnostic radiology were tested using the speech recognition system SP 6000. Methods: The speech recognition system SP 6000 was integrated into the network of the institute and connected to the existing Radiological Information System (RIS). Three subjects used this system for writing 2305 findings from dictation. After the recognition process the date, length of dictation, time required for checking/correction, kind of examination and error rate were recorded for every dictation. With the same subjects, a correlation was performed with 625 conventionally written finding. Results: After an 1-hour initial training the average error rates were 8.4 to 13.3%. The first adaptation of the speech recognition system (after nine days) decreased the average error rates to 2.4 to 10.7% due to the ability of the program to learn. The 2 nd and 3 rd adaptations resulted only in small changes of the error rate. An individual comparison of the error rate developments in the same kind of investigation showed the relative independence of the error rate on the individual user. Conclusion: The results show that the speech recognition system SP 6000 can be evaluated as an advantageous alternative for quickly recording radiological findings. A comparison between manually writing and dictating the findings verifies the individual differences of the writing speeds and shows the advantage of the application of voice recognition when faced with normal keyboard performance. (orig.) [de

An Evaluation of Wind Turbine Technology at Peterson Air Force Base

Science.gov (United States)

2005-03-01

by the wind speed. Darrieus turbines are ordinarily inexpensive and are used for electricity generation and irrigation. One advantage to a...AN EVALUATION OF WIND TURBINE TECHNOLOGY...02 AN EVALUATION OF WIND TURBINE TECHNOLOGY AT PETERSON AIR FORCE BASE THESIS Presented to the Faculty Department of

Evaluation technology of human behavior cognition; Ningen kodo ninchi hyoka gijutsu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

For human engineering and improvement of the living environment, the evaluation technology of human behavior cognition was studied. For the future reformation and creation of economic structure, the following are required: establishment of safe and affluent communities, further improvement of the safety and harmonious balance of people, lives and society, and R & D close to people and social needs. Introduction of Product Liability law and a fail-safe concept are examples of such efforts. However, since many accidents are found in the human society, the relation between human errors and human characteristics should be studied in detail. The cognitive science of human behavior is an objective evaluation technology from the viewpoint of human being, object, environment and society. Based on these social and technological background, the feasibility of the evaluation technology is studied, and the future trend and skeleton of this project are clarified. The domestic and foreign trends of technologies concerned are thus surveyed, and the important points, features, skeleton and ripple effect of the technology are summarized. 500 refs., 70 figs., 5 tabs.

A multi-approach feature extractions for iris recognition

Science.gov (United States)

Sanpachai, H.; Settapong, M.

2014-04-01

Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.

Scale Invariant Gabor Descriptor-Based Noncooperative Iris Recognition

Directory of Open Access Journals (Sweden)

Du Yingzi

2010-01-01

Full Text Available Abstract A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

Scale Invariant Gabor Descriptor-based Noncooperative Iris Recognition

Directory of Open Access Journals (Sweden)

Zhi Zhou

2010-01-01

Full Text Available A new noncooperative iris recognition method is proposed. In this method, the iris features are extracted using a Gabor descriptor. The feature extraction and comparison are scale, deformation, rotation, and contrast-invariant. It works with off-angle and low-resolution iris images. The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT for feature extraction to better extract the iris features. Both the phase and magnitude of the Gabor wavelet outputs were used in a novel way for local feature point description. Two feature region maps were designed to locally and globally register the feature points and each subregion in the map is locally adjusted to the dilation/contraction/deformation. We also developed a video-based non-cooperative iris recognition system by integrating video-based non-cooperative segmentation, segmentation evaluation, and score fusion units. The proposed method shows good performance for frontal and off-angle iris matching. Video-based recognition methods can improve non-cooperative iris recognition accuracy.

Technical and economic evaluation of selected technologies of the Landfill Characterization System

Energy Technology Data Exchange (ETDEWEB)

Floran, R.J.

1993-12-31

In 1992 and 1993, numerous innovative and emerging technologies for characterizing metal and mixed waste contaminants and their migration beneath landfills in and environments were field tested at Sandia`s Chemical Waste Landfill. Many of these technologies are being evaluated as part of the Landfill Characterization System (LCS). The LCS emphasizes minimally intrusive technologies and downhole sensors that strive to be cheaper, better, safer and faster than conventional methods. Major aims of the LCS are to demonstrate, test and evaluate these technologies, and determine whether substantial cost saving over traditional baseline methods can be realized. To achieve these goals, the LCS uses an integrated systems approach that stresses the application of complementary and compatible technologies. Successful field demonstrations combined with favorable economics, will greatly assist the commercialization of these technologies to the private sector and to Environmental Restoration groups throughout the DOE Complex. In this paper, a technical and economic evaluation of selected technologies that comprise the LCS is presented. Because sampling and analysis is the most costly part of a characterization effort, the economic evaluation presented here focuses specifically on these activities. LCS technologies discussed include the ``Smart Sampling Methodology`` and two field screening analytical methods, stripping voltammetry and x-ray fluorescence.

An Evaluation of Imitation Recognition Abilities in Typically Developing Children and Young Children with Autism Spectrum Disorder.

Science.gov (United States)

Berger, Natalie I; Ingersoll, Brooke

2015-08-01

Previous work has indicated that both typically developing children and children with Autism Spectrum Disorder (ASD) display a range of imitation recognition behaviors in response to a contingent adult imitator. However, it is unknown how the two groups perform comparatively on this construct. In this study, imitation recognition behaviors for children with ASD and typically developing children were observed during periods of contingent imitation imbedded in a naturalistic imitation task. Results from this study indicate that children with ASD are impaired in their ability to recognize being imitated relative to typically developing peers as demonstrated both by behaviors representing basic social attention and more mature imitation recognition. Display of imitation recognition behaviors was independent of length of contingent imitation period in typically developing children, but rate of engagement in imitation recognition behaviors was positively correlated with length of contingent imitation period in children with ASD. Exploratory findings also suggest a link between the ability to demonstrate recognition of being imitated and ASD symptom severity, language, and object imitation for young children with ASD. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Channel-dependent GMM and multi-class logistic: Regression models for language recognition

NARCIS (Netherlands)

Leeuwen, D.A. van; Brümmer, Niko

2006-01-01

This paper describes two new approaches to spoken language recognition. These were both successfully applied in the NIST 2005 Language Recognition Evaluation. The first approach extends the Gaussian Mixture Model technique with channel dependency, which results in actual detection costs (CDET) of

The Impact of Image Quality on the Performance of Face Recognition

NARCIS (Netherlands)

Dutta, A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

The performance of a face recognition system depends on the quality of both test and reference images participating in the face comparison process. In a forensic evaluation case involving face recognition, we do not have any control over the quality of the trace (image captured by a CCTV at a crime

Output Interference in Recognition Memory

Science.gov (United States)

Criss, Amy H.; Malmberg, Kenneth J.; Shiffrin, Richard M.

2011-01-01

Dennis and Humphreys (2001) proposed that interference in recognition memory arises solely from the prior contexts of the test word: Interference does not arise from memory traces of other words (from events prior to the study list or on the study list, and regardless of similarity to the test item). We evaluate this model using output…

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

Science.gov (United States)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

DOE evaluates nine alternative thermal technologies for treatment of mixed waste

International Nuclear Information System (INIS)

Anon.

1995-01-01

In June 1993, the U.S. Department of Energy's (DOE's) Office of Technology Development commissioned a study to evaluate 19 thermal technologies for treating DOE's mixed waste. The study was divided into two phases: Phase I evaluated ten conventional incineration techniques (primarily rotary kiln), and Phase II looked at nine innovative, alternative thermal treatment technologies. The treatment processes were evaluated as part of an integrated waste treatment system, which would include all of the facilities, equipment, and methods required to treat and dispose DOE mixed waste. The relative merits and life-cycle costs were then developed for each of the 19 waste treatment systems evaluated. The study also identified the additional research and development, demonstration, and testing/evaluation steps that would be necessary for the waste treatment systems to successfully treat DOE mixed waste. 3 tabs., 2 refs

A recurrent dynamic model for correspondence-based face recognition.

Science.gov (United States)

Wolfrum, Philipp; Wolff, Christian; Lücke, Jörg; von der Malsburg, Christoph

2008-12-29

Our aim here is to create a fully neural, functionally competitive, and correspondence-based model for invariant face recognition. By recurrently integrating information about feature similarities, spatial feature relations, and facial structure stored in memory, the system evaluates face identity ("what"-information) and face position ("where"-information) using explicit representations for both. The network consists of three functional layers of processing, (1) an input layer for image representation, (2) a middle layer for recurrent information integration, and (3) a gallery layer for memory storage. Each layer consists of cortical columns as functional building blocks that are modeled in accordance with recent experimental findings. In numerical simulations we apply the system to standard benchmark databases for face recognition. We find that recognition rates of our biologically inspired approach lie in the same range as recognition rates of recent and purely functionally motivated systems.

An Orchestrating Evaluation of Complex Educational Technologies: a Case Study of a CSCL System

Directory of Open Access Journals (Sweden)

Luis P. Prieto

2014-06-01

Full Text Available As digital technologies permeate every aspect of our lives, the complexity of the educational settings, and of the technological support we use within them, unceasingly rises. This increased complexity, along with the need for educational practitioners to apply such technologies within multi-constraint authentic settings, has given rise to the notion of technology-enhanced learning practice as “orchestration of learning”. However, at the same time, the complexity involved in evaluating the benefits of such educational technologies has also increased, prompting questions about the way evaluators can cope with the different places, technologies, informants and issues involved in their evaluation activity. By proposing the notion of “orchestrating evaluation”, this paper tries to reconcile the often disparate “front office accounts” of research publications and the “shop floor practice” of evaluation of educational technology, through the case study of evaluating a system to help teachers in coordinating computer-supported collaborative learning (CSCL scenarios. We reuse an internationally-evaluated conceptual framework of “orchestration aspects” (design, management, adaptation, pragmatism, etc. to structure the case‟s narrative, showing how the original evaluation questions and methods were modulated in the face of the multiple (authentic evaluation setting constraints.

Frontal view reconstruction for iris recognition

Science.gov (United States)

Santos-Villalobos, Hector J; Bolme, David S; Boehnen, Chris Bensing

2015-02-17

Iris recognition can be accomplished for a wide variety of eye images by correcting input images with an off-angle gaze. A variety of techniques, from limbus modeling, corneal refraction modeling, optical flows, and genetic algorithms can be used. A variety of techniques, including aspherical eye modeling, corneal refraction modeling, ray tracing, and the like can be employed. Precomputed transforms can enhance performance for use in commercial applications. With application of the technologies, images with significantly unfavorable gaze angles can be successfully recognized.

MYRRHA successfully launched. After Belgium, a European recognition

International Nuclear Information System (INIS)

Abderrahim, H.A.

2011-01-01

The green light of the Belgian governments to MYRRHA in 2010 was one of the major milestones for SCK-CEN. In the years to come, a research team will look for answers to unresolved scientific and technological issues, and will finalise the design of this cutting-edge research reactor. In 2010, MYRRHA received wide recognition at the international level as well. MYRRHA was selected as one of the most promising nuclear technologies in the European Sustainable Nuclear Industrial Initiative (ESNII) and received a prominent place in the list of priority research facilities of the European Strategy Forum on Research Infrastructures (ESFRI).

Improving entrepreneurial opportunity recognition through web content analytics

Science.gov (United States)

Bakar, Muhamad Shahbani Abu; Azmi, Azwiyati

2017-10-01

The ability to recognize and develop an opportunity into a venture defines an entrepreneur. Research in opportunity recognition has been robust and focuses more on explaining the processes involved in opportunity recognition. Factors such as prior knowledge, cognitive and creative capabilities are shown to affect opportunity recognition in entrepreneurs. Prior knowledge in areas such as customer problems, ways to serve the market, and technology has been shows in various studies to be a factor that facilitates entrepreneurs to identify and recognize opportunities. Findings from research also shows that experienced entrepreneurs search and scan for information to discover opportunities. Searching and scanning for information has also been shown to help novice entrepreneurs who lack prior knowledge to narrow this gap and enable them to better identify and recognize opportunities. There is less focus in research on finding empirically proven techniques and methods to develop and enhance opportunity recognition in student entrepreneurs. This is important as the country pushes for more graduate entrepreneurs that can drive the economy. This paper aims to discuss Opportunity Recognition Support System (ORSS), an information support system to help especially student entrepreneurs in identifying and recognizing business opportunities. The ORSS aims to provide the necessary knowledge to student entrepreneurs to be able to better identify and recognize opportunities. Applying design research, theories in opportunity recognition are applied to identify the requirements for the support system and the requirements in turn dictate the design of the support system. The paper proposes the use of web content mining and analytics as two core components and techniques for the support system. Web content mining can mine the vast knowledge repositories available on the internet and analytics can provide entrepreneurs with further insights into the information needed to recognize

On the limits of target recognition in the presence of atmospheric effects

Science.gov (United States)

Chen, Xiaohan; Schmid, Natalia A.

2008-04-01

The importance of Networked Automatic Target Recognition systems for surveillance applications is continuously increasing. Because of the requirement of a low cost and limited payload these networks are traditionally equipped with lightweight, low-cost sensors such as Electro Optical or Infrared sensors. The quality of imagery acquired by these sensors critically depends on the environmental conditions, type and characteristics of sensors, and absence of occluding or concealing objects. In the past a large number of efficient detection, tracking, and recognition algorithms have been designed to operate on imagery of good quality. However, detection and recognition limits under non-ideal environmental and/or sensor based distortions have not been carefully evaluated. This work describes a real image dataset formed by imaging 10 die cast models of military vehicles at different elevation and orientation angles. The dataset contains imagery acquired both indoors and outdoors. The indoors dataset is composed of clear and distorted images. The distortions include defocus blur, sided illumination, low contrast, shadows and occlusions. All images in this dataset, however, have a uniform blue background. The indoors dataset is applied to evaluate the degradations of recognition performance due to camera and illumination effects. The recognition method is based on Bessel K forms. The dataset collected outdoors includes real background and is much more complex to process. This dataset is used to evaluate performance of a fully automatic target recognition system that involves a Haar-based detector to select potential regions of interest within images; performs adjustment and fusion of detected regions; segments potential targets using a region based approach; identifies targets using Bessel K form-based encoding; and performs clutter rejection. The numerical results demonstrate that the complexity of the background and the presence of occlusions lead to substantial detection

METHODS FOR EVALUATION OF COMPANIES’ INFORMATION SYSTEMS AND TECHNOLOGIES EFFICIENCY AND CONTROL IN TEACHING COURSE "INFORMATION TECHNOLOGY GOVERNANCE"

Directory of Open Access Journals (Sweden)

Samchynska Yaroslava

2014-10-01

Full Text Available The use of the information systems and technologies in economic activity is called to represent companies’ corporate principles, aims, traditions, to help in realization of the planned strategies, thanks to that the management efficiency and the cost of enterprise increases. Teaching for educational discipline «IT Governance» is directed on a study and research of these intercommunications by students of the 5th course on specialties «Computer Science», «Software Engineering» for educational level Specialist (Past Bachelor Degree, Master degree. The auditing services belong to the actual methods for evaluation of the information systems and technologies efficiency and control, which are studied according to the course «IT Governance». The article deals with the methodological basis of providing auditing services for evaluation of efficiency and control of information systems (technologies for the purpose of satisfaction of growing informational needs of companies and functional activation in their information resources. The main task of auditing services for control of information systems (information communication technologies efficiency is to evaluate independently and objectively if the information technologies provide the necessary services. The basic criteria, data ware, subject and object of audit necessary for drawing up an audit report and assurance declaring are established. The program and a detailed list of auditing procedures for evaluation of efficiency of information systems and technologies have been presented

Impact of Digital Tooth Preparation Evaluation Technology on Preclinical Dental Students' Technical and Self-Evaluation Skills.

Science.gov (United States)

Gratton, David G; Kwon, So Ran; Blanchette, Derek; Aquilino, Steven A

2016-01-01

The aim of this study was to evaluate the effect of digital tooth preparation imaging and evaluation technology on dental students' technical abilities, self-evaluation skills, and the assessment of their simulated clinical work. A total of 80 second-year students at one U.S. dental school were assigned to one of three groups: control (n=40), E4D Compare (n=20), and Sirona prepCheck (n=20). Students in the control group were taught by traditional teaching methodologies, and the technology-assisted groups received both traditional training and supplementary feedback from the corresponding digital system. Three outcomes were measured: faculty technical score, self-evaluation score, and E4D Compare scores at 0.30 mm tolerance. Correlations were determined between the groups' scores from visual assessment and self-evaluation and between the visual assessment and digital scores. The results showed that the visual assessment and self-evaluation scores did not differ among groups (p>0.05). Overall, correlations between visual and digital assessment scores were modest though statistically significant (5% level of significance). These results suggest that the use of digital tooth preparation evaluation technology did not impact the students' prosthodontic technical and self-evaluation skills. Visual scores given by faculty and digital assessment scores correlated moderately in only two instances.

Contextual System of Symbol Structural Recognition based on an Object-Process Methodology

OpenAIRE

Delalandre, Mathieu

2005-01-01

We present in this paper a symbol recognition system for the graphic documents. This one is based on a contextual approach for symbol structural recognition exploiting an Object-Process Methodology. It uses a processing library composed of structural recognition processings and contextual evaluation processings. These processings allow our system to deal with the multi-representation of symbols. The different processings are controlled, in an automatic way, by an inference engine during the r...

Study on the evaluation of decontamination and decommissioning technologies and their demands in Korea

Energy Technology Data Exchange (ETDEWEB)

Oh, Won Zin; Lee, K. W.; Jung, C. H.; Choi, W. K.; Won, H. J.; Kim, G. N.; Jung, K. J.; Chung, U. S.; Lee, D. G.; Kim, C. J.; Kim, S. H.; Chung, J. M.; Kwon, S. O. [Korea Atomic Energy Research Institute, Taejeon (Korea)

2001-03-01

D and D market demand, the current status of the technology, technology items applicable to the domestic market and the future prospect of technologies not self-developed in Korea were evaluated. In the evaluation of D and D market demand and the current status of the technology, 1) the market demand was investigated on the D and D objects such as the research reactors, the nuclear power plants and the nuclear fuel cycle development facilities from 2001 to 2010, and 2) the technology demand for decommissioning of the nuclear power plants from 2001 to 2030 were investigated. In the evaluation of the technology items applicable to the domestic market, 1) the analysis of the technologies derived from the technology requirements on D and D objects and their related similar technologies was performed, and 2) the technology items applicable to the domestic market were derived from the evaluation of the suitability on the domestic technology requirements. The promising technologies applicable to the domestic market were derived from the integrated evaluation of the technological factors(innovation, internationally competitive power and the difficulty of the technology development), economical factors (domestic demand and substitution effect of foreign currency) and domestically applicable factors (applicability on the industry and a ripple effect). The background of the technology development such as business applicability and the technology demonstration effect through the integrated management of the decommissioning of TRIGA reactor and the uranium conversion facility was also analyzed. 10 refs., 9 figs., 28 tabs. (Author)

Influence of Child Factors on Health-Care Professionals' Recognition of Common Childhood Mental-Health Problems.

Science.gov (United States)

Burke, Delia A; Koot, Hans M; de Wilde, Amber; Begeer, Sander

Early recognition of childhood mental-health problems can help minimise long-term negative outcomes. Recognition of mental-health problems, needed for referral and diagnostic evaluation, is largely dependent on health-care professionals' (HCPs) judgement of symptoms presented by the child. This study aimed to establish whether HCPs recognition of mental-health problems varies as a function of three child-related factors (type of problem, number of symptoms, and demographic characteristics). In an online survey, HCPs ( n  = 431) evaluated a series of vignettes describing children with symptoms of mental-health problems. Vignettes varied by problem type (Attention-Deficit/Hyperactivity Disorder (ADHD), Generalised Anxiety Disorder (GAD), Autism Spectrum Disorder (ASD), Conduct Disorder (CD) and Major Depressive Disorder), number of symptoms presented (few and many), and child demographic characteristics (ethnicity, gender, age and socio-economic status (SES)). Results show that recognition of mental-health problems varies by problem type, with ADHD best recognised and GAD worst. Furthermore, recognition varies by the number of symptoms presented. Unexpectedly, a child's gender, ethnicity and family SES did not influence likelihood of problem recognition. These results are the first to reveal differences in HCPs' recognition of various common childhood mental-health problems. HCPs in practice should be advised about poor recognition of GAD, and superior recognition of ADHD, if recognition of all childhood mental-health problems is to be equal.

Dynamic Recognition of Driver’s Propensity Based on GPS Mobile Sensing Data and Privacy Protection

Directory of Open Access Journals (Sweden)

Xiaoyuan Wang

2016-01-01

Full Text Available Driver’s propensity is a dynamic measurement of driver’s emotional preference characteristics in driving process. It is a core parameter to compute driver’s intention and consciousness in safety driving assist system, especially in vehicle collision warning system. It is also an important influence factor to achieve the Driver-Vehicle-Environment Collaborative Wisdom and Control macroscopically. In this paper, dynamic recognition model of driver’s propensity based on support vector machine is established taking the vehicle safety controlled technology and respecting and protecting the driver’s privacy as precondition. The experiment roads travel time obtained through GPS is taken as the characteristic parameter. The sensing information of Driver-Vehicle-Environment was obtained through psychological questionnaire tests, real vehicle experiments, and virtual driving experiments, and the information is used for parameter calibration and validation of the model. Results show that the established recognition model of driver’s propensity is reasonable and feasible, which can achieve the dynamic recognition of driver’s propensity to some extent. The recognition model provides reference and theoretical basis for personalized vehicle active safety systems taking people as center especially for the vehicle safety technology based on the networking.

Image recognition on raw and processed potato detection: a review

Science.gov (United States)

Qi, Yan-nan; Lü, Cheng-xu; Zhang, Jun-ning; Li, Ya-shuo; Zeng, Zhen; Mao, Wen-hua; Jiang, Han-lu; Yang, Bing-nan

2018-02-01

Objective: Chinese potato staple food strategy clearly pointed out the need to improve potato processing, while the bottleneck of this strategy is technology and equipment of selection of appropriate raw and processed potato. The purpose of this paper is to summarize the advanced raw and processed potato detection methods. Method: According to consult research literatures in the field of image recognition based potato quality detection, including the shape, weight, mechanical damage, germination, greening, black heart, scab potato etc., the development and direction of this field were summarized in this paper. Result: In order to obtain whole potato surface information, the hardware was built by the synchronous of image sensor and conveyor belt to achieve multi-angle images of a single potato. Researches on image recognition of potato shape are popular and mature, including qualitative discrimination on abnormal and sound potato, and even round and oval potato, with the recognition accuracy of more than 83%. Weight is an important indicator for potato grading, and the image classification accuracy presents more than 93%. The image recognition of potato mechanical damage focuses on qualitative identification, with the main affecting factors of damage shape and damage time. The image recognition of potato germination usually uses potato surface image and edge germination point. Both of the qualitative and quantitative detection of green potato have been researched, currently scab and blackheart image recognition need to be operated using the stable detection environment or specific device. The image recognition of processed potato mainly focuses on potato chips, slices and fries, etc. Conclusion: image recognition as a food rapid detection tool have been widely researched on the area of raw and processed potato quality analyses, its technique and equipment have the potential for commercialization in short term, to meet to the strategy demand of development potato as

Statistical Pattern Recognition

CERN Document Server

Webb, Andrew R

2011-01-01

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

Real-Time Multiview Recognition of Human Gestures by Distributed Image Processing

Directory of Open Access Journals (Sweden)

Sato Kosuke

2010-01-01

Full Text Available Since a gesture involves a dynamic and complex motion, multiview observation and recognition are desirable. For the better representation of gestures, one needs to know, in the first place, from which views a gesture should be observed. Furthermore, it becomes increasingly important how the recognition results are integrated when larger numbers of camera views are considered. To investigate these problems, we propose a framework under which multiview recognition is carried out, and an integration scheme by which the recognition results are integrated online and in realtime. For performance evaluation, we use the ViHASi (Virtual Human Action Silhouette public image database as a benchmark and our Japanese sign language (JSL image database that contains 18 kinds of hand signs. By examining the recognition rates of each gesture for each view, we found gestures that exhibit view dependency and the gestures that do not. Also, we found that the view dependency itself could vary depending on the target gesture sets. By integrating the recognition results of different views, our swarm-based integration provides more robust and better recognition performance than individual fixed-view recognition agents.

A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

Directory of Open Access Journals (Sweden)

Ahmad Jalal

2014-07-01

Full Text Available Recent advancements in depth video sensors technologies have made human activity recognition (HAR realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments.

Science.gov (United States)

Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

2014-07-02

Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

Physics of Automatic Target Recognition

CERN Document Server

Sadjadi, Firooz

2007-01-01

Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

Development of integrity evaluation technology for pressurized components in nuclear power plant and IT based integrity evaluation system

International Nuclear Information System (INIS)

Kim, Young Jin; Choi, Jae Boong; Shim, Do Jun

2004-02-01

The objective of this research is to develop on efficient integrity evaluation technology and to investigate the applicability of the newly-developed technology such as internet-based cyber platform etc. to Nuclear Power Plant(NPP) components. The development of an efficient structural integrity evaluation system is necessary for safe operation of NPP as the increase of operating periods. Moreover, material test data as well as emerging structural integrity assessment technology are also needed for the evaluation of aged components. The following five topics are covered in this project: development of the wall-thinning evaluation program for nuclear piping; development of structural integrity evaluation criteria for steam generator tubes with cracks of various shape; development of fatigue life evaluation system for major components of NPP; ingegration of internet-based cyber platform and integrity evaluation program for primary components of NPP; effects of aging on strength of dissimilar welds

Development of integrity evaluation technology for pressurized components in nuclear power plant and IT based integrity evaluation system

Energy Technology Data Exchange (ETDEWEB)

Kim, Young Jin; Choi, Jae Boong; Shim, Do Jun [Sungkyunkwan Univ., Seoul (Korea, Republic of)] (and others)

2004-02-15

The objective of this research is to develop on efficient integrity evaluation technology and to investigate the applicability of the newly-developed technology such as internet-based cyber platform etc. to Nuclear Power Plant(NPP) components. The development of an efficient structural integrity evaluation system is necessary for safe operation of NPP as the increase of operating periods. Moreover, material test data as well as emerging structural integrity assessment technology are also needed for the evaluation of aged components. The following five topics are covered in this project: development of the wall-thinning evaluation program for nuclear piping; development of structural integrity evaluation criteria for steam generator tubes with cracks of various shape; development of fatigue life evaluation system for major components of NPP; ingegration of internet-based cyber platform and integrity evaluation program for primary components of NPP; effects of aging on strength of dissimilar welds.

Human and automatic speaker recognition over telecommunication channels

CERN Document Server

Fernández Gallardo, Laura

2016-01-01

This work addresses the evaluation of the human and the automatic speaker recognition performances under different channel distortions caused by bandwidth limitation, codecs, and electro-acoustic user interfaces, among other impairments. Its main contribution is the demonstration of the benefits of communication channels of extended bandwidth, together with an insight into how speaker-specific characteristics of speech are preserved through different transmissions. It provides sufficient motivation for considering speaker recognition as a criterion for the migration from narrowband to enhanced bandwidths, such as wideband and super-wideband.

Evaluation of alternative nonflame technologies for destruction of hazardous organic waste