Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System.

Science.gov (United States)

Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

2015-01-01

The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

Ultrahigh-pressure transitions in solid hydrogen

International Nuclear Information System (INIS)

Mao, H.; Hemley, R.J.

1994-01-01

During the past five years, major progress has been made in the experimental study of solid hydrogen at ultrahigh pressures as a result of developments in diamond-cell technology. Pressures at which metallization has been predicted to occur have been reached (250--300 Gigapascals). Detailed studies of the dynamic, structural, and electronic properties of dense hydrogen reveal a system unexpectedly rich in physical phenomena, exhibiting a variety of transitions at ultrahigh pressures. This colloquium explores the study of dense hydrogen as an archetypal problem in condensed-matter physics

Quartz microbalance device for transfer into ultrahigh vacuum systems

International Nuclear Information System (INIS)

Stavale, F.; Achete, C. A.; Niehus, H.

2008-01-01

An uncomplicated quartz microbalance device has been developed which is transferable into ultrahigh vacuum (UHV) systems. The device is extremely useful for flux calibration of different kinds of material evaporators. Mounted on a commercial specimen holder, the device allows fast quartz microbalance transfer into the UHV and subsequent positioning exactly to the sample location where subsequent thin film deposition experiments shall be carried out. After backtransfer into an UHV sample stage, the manipulator may be loaded in situ with the specimen suited for the experiment. The microbalance device capability is demonstrated for monolayer and submonolayer vanadium depositions with an achieved calibration sensitivity of less the 0.001 ML coverage.

Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

Directory of Open Access Journals (Sweden)

Pavol Partila

2015-01-01

Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

Pressure measurements in the AGS Booster ultra-high vacuum system

International Nuclear Information System (INIS)

Gabusi, J.; Geller, J.; Hseuh, H.C.; Mapes, M.; Stattel, P.

1992-01-01

An average pressure of mid 10 -11 Torr has been achieved and maintained in the AGS Booster ring vacuum system during its first year of operation. This ultra-high vacuum system is monitored through remote controlled Bayard-Alpert Gauges (BAGs). The characteristics of the pressure measurements with BAGs over the long cable lengths (up to 200 m) and under various accelerator operating conditions will be described. Two types of noise in the pressure readouts have been identified; the electromagnetic interference (EMI) associated with the acceleration cycles of the Booster and the environment noise associated with the temperature of the collector cables. The magnitude of the noise pickup depends on the routing of the collector cables and reaches the equivalent pressure of low 10 -9 Torr

Combat Systems Department Employee Recognition System

National Research Council Canada - National Science Library

1996-01-01

This handbook contains two types of information: guidelines and instructions. The guidelines provide a foundation of purpose, assumptions, principles, expectations and attributes the Employee Recognition System is designed to reflect...

Fingerprint recognition system by use of graph matching

Science.gov (United States)

Shen, Wei; Shen, Jun; Zheng, Huicheng

2001-09-01

Fingerprint recognition is an important subject in biometrics to identify or verify persons by physiological characteristics, and has found wide applications in different domains. In the present paper, we present a finger recognition system that combines singular points and structures. The principal steps of processing in our system are: preprocessing and ridge segmentation, singular point extraction and selection, graph representation, and finger recognition by graphs matching. Our fingerprint recognition system is implemented and tested for many fingerprint images and the experimental result are satisfactory. Different techniques are used in our system, such as fast calculation of orientation field, local fuzzy dynamical thresholding, algebraic analysis of connections and fingerprints representation and matching by graphs. Wed find that for fingerprint database that is not very large, the recognition rate is very high even without using a prior coarse category classification. This system works well for both one-to-few and one-to-many problems.

Ultrahigh temperature vapor core reactor-MHD system for space nuclear electric power

Science.gov (United States)

Maya, Isaac; Anghaie, Samim; Diaz, Nils J.; Dugan, Edward T.

1991-01-01

The conceptual design of a nuclear space power system based on the ultrahigh temperature vapor core reactor with MHD energy conversion is presented. This UF4 fueled gas core cavity reactor operates at 4000 K maximum core temperature and 40 atm. Materials experiments, conducted with UF4 up to 2200 K, demonstrate acceptable compatibility with tungsten-molybdenum-, and carbon-based materials. The supporting nuclear, heat transfer, fluid flow and MHD analysis, and fissioning plasma physics experiments are also discussed.

Ultra-high vacuum system of the Brookhaven National Synchrotron Light Source

International Nuclear Information System (INIS)

Foerster, C.L.

1995-01-01

The rings of the National Synchrotron Light Source (NSLS) have been supplying light to numerous users for approximately a decade and recently a fully conditioned machine vacuum at design currents was obtained. A brief description of the x-ray storage ring, the VUV storage ring and their current supply is given along with some of their features. The ultra-high vacuum system employed for the storage rings and their advantages for the necessary stored beam environments are discussed including, a brief history of time. 15 refs., 2 tabs., 8 figs

Research on Face Recognition Based on Embedded System

Directory of Open Access Journals (Sweden)

Hong Zhao

2013-01-01

Full Text Available Because a number of image feature data to store, complex calculation to execute during the face recognition, therefore the face recognition process was realized only by PCs with high performance. In this paper, the OpenCV facial Haar-like features were used to identify face region; the Principal Component Analysis (PCA was employed in quick extraction of face features and the Euclidean Distance was also adopted in face recognition; as thus, data amount and computational complexity would be reduced effectively in face recognition, and the face recognition could be carried out on embedded platform. Finally, based on Tiny6410 embedded platform, a set of embedded face recognition systems was constructed. The test results showed that the system has stable operation and high recognition rate can be used in portable and mobile identification and authentication.

Measurement system for ultrahigh temperature thermophysical properties

International Nuclear Information System (INIS)

Fukuyama, Hiroyuki

2015-01-01

Properties and Simulations Probed with Electromagnetic Containerless Technique (PROSPECT) is a measurement system for ultrahigh temperature thermophysical properties to be able to measure thermophysical properties with high precision by combining AC magnetic field (electromagnetic levitation device) and DC magnetic field (superconducting magnet) to realize the static floating state of metallic melt, in other words, the state of suppressing the surface vibration of droplets, translational motion, and internal convection. The electromagnetic levitation method is a method to obtain a floating force due to the Lorentz force generated by the interaction between high-frequency current flowing in the coil and the induced current generated in a sample, and to heat/melt the sample with the Joule heat generated by its induced current. This paper roughly explains the element technologies of PROSPECT with a focus on the laser modulation calorimetry (laser periodic heating method), normal spectral emissivity measurement method, density measurement, and surface tension measurement method. Furthermore, as the application of PROSPECT to new research deployment, it introduces the observation of phase separation structure in the supercooled solidification structure of Cu-Co alloy. (A.O.)

8th International Conference on Computer Recognition Systems

CERN Document Server

Jackowski, Konrad; Kurzynski, Marek; Wozniak, Michał; Zolnierek, Andrzej

2013-01-01

The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 86 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Biometrics Data Stream Classification and Big Data Analytics  Features, learning, and classifiers Image processing and computer vision Medical applications Miscellaneous applications Pattern recognition and image processing in robotics  Speech and word recognition This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

DEVELOPMENT OF HOLE RECOGNITION SYSTEM FROM STEP FILE

Directory of Open Access Journals (Sweden)

C. F. Tan

2017-11-01

Full Text Available This paper describes the development of Hole Recognition System (HRS for Computer-Aided Process Planning (CAPP using a neutral data format produced by CAD system. The geometrical data of holes is retrieved from STandard for the Exchange of Product model data (STEP. Rule-based algorithm is used during recognising process. Current implementation of feature recognition is limited to simple hole feat ures. Test results are presented to demonstrate the capabilities of the feature recognition algorithm.

An ultra-high speed whole slide image viewing system.

Science.gov (United States)

Yagi, Yukako; Yoshioka, Shigeatsu; Kyusojin, Hiroshi; Onozato, Maristela; Mizutani, Yoichi; Osato, Kiyoshi; Yada, Hiroaki; Mark, Eugene J; Frosch, Matthew P; Louis, David N

2012-01-01

One of the goals for a Whole Slide Imaging (WSI) system is implementation in the clinical practice of pathology. One of the unresolved problems in accomplishing this goal is the speed of the entire process, i.e., from viewing the slides through making the final diagnosis. Most users are not satisfied with the correct viewing speeds of available systems. We have evaluated a new WSI viewing station and tool that focuses on speed. A prototype WSI viewer based on PlayStation®3 with wireless controllers was evaluated at the Department of Pathology at MGH for the following reasons: 1. For the simulation of signing-out cases; 2. Enabling discussion at a consensus conference; and 3. Use at slide seminars during a Continuing Medical Education course. Pathologists were being able to use the system comfortably after 0-15 min training. There were no complaints regarding speed. Most pathologists were satisfied with the functionality, usability and speed of the system. The most difficult situation was simulating diagnostic sign-out. The preliminary results of adapting the Sony PlayStation®3 (PS3®) as an ultra-high speed WSI viewing system were promising. The achieved speed is consistent with what would be needed to use WSI in daily practice.

Biometric Features in Person Recognition Systems

Directory of Open Access Journals (Sweden)

Edgaras Ivanovas

2011-03-01

Full Text Available Lately a lot of research effort is devoted for recognition of a human being using his biometric characteristics. Biometric recognition systems are used in various applications, e. g., identification for state border crossing or firearm, which allows only enrolled persons to use it. In this paper biometric characteristics and their properties are reviewed. Development of high accuracy system requires distinctive and permanent characteristics, whereas development of user friendly system requires collectable and acceptable characteristics. It is showed that properties of biometric characteristics do not influence research effort significantly. Properties of biometric characteristic features and their influence are discussed.Article in Lithuanian

Ultrahigh resolution radiation imaging system using an optical fiber structure scintillator plate.

Science.gov (United States)

Yamamoto, Seiichi; Kamada, Kei; Yoshikawa, Akira

2018-02-16

High resolution imaging of radiation is required for such radioisotope distribution measurements as alpha particle detection in nuclear facilities or high energy physics experiments. For this purpose, we developed an ultrahigh resolution radiation imaging system using an optical fiber structure scintillator plate. We used a ~1-μm diameter fiber structured GdAlO 3 :Ce (GAP) /α-Al 2 O 3 scintillator plate to reduce the light spread. The fiber structured scintillator plate was optically coupled to a tapered optical fiber plate to magnify the image and combined with a lens-based high sensitivity CCD camera. We observed the images of alpha particles with a spatial resolution of ~25 μm. For the beta particles, the images had various shapes, and the trajectories of the electrons were clearly observed in the images. For the gamma photons, the images also had various shapes, and the trajectories of the secondary electrons were observed in some of the images. These results show that combining an optical fiber structure scintillator plate with a tapered optical fiber plate and a high sensitivity CCD camera achieved ultrahigh resolution and is a promising method to observe the images of the interactions of radiation in a scintillator.

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

Testing of a portable ultrahigh pressure water decontamination system (UHPWDS)

International Nuclear Information System (INIS)

Lovell, A.; Dahlby, J.

1996-02-01

This report describes the tests done with a portable ultrahigh pressure water decontamination system (UHPWDS) on highly radioactively contaminated surfaces. A small unit was purchased, modified, and used for in-situ decontamination to change the waste level of the contaminated box from transuranic (TRU) waste to low- level waste (LLW). Low-level waste is less costly by as much as a factor of five or more if compared with TRU waste when handling, storage, and disposal are considered. The portable unit we tested is commercially available and requires minimal utilities for operation. We describe the UHPWDS unit itself, a procedure for its use, the results of the testing we did, and conclusions including positive and negative aspects of the UHPWDS

Automatic Number Plate Recognition System for IPhone Devices

Directory of Open Access Journals (Sweden)

Călin Enăchescu

2013-06-01

Full Text Available This paper presents a system for automatic number plate recognition, implemented for devices running the iOS operating system. The methods used for number plate recognition are based on existing methods, but optimized for devices with low hardware resources. To solve the task of automatic number plate recognition we have divided it into the following subtasks: image acquisition, localization of the number plate position on the image and character detection. The first subtask is performed by the camera of an iPhone, the second one is done using image pre-processing methods and template matching. For the character recognition we are using a feed-forward artificial neural network. Each of these methods is presented along with its results.

Ultra-high temperature direct propulsion

International Nuclear Information System (INIS)

Araj, K.J.; Slovik, G.; Powell, J.R.; Ludewig, H.

1987-01-01

Potential advantages of ultra-high exhaust temperature (3000 K - 4000 K) direct propulsion nuclear rockets are explored. Modifications to the Particle Bed Reactor (PBR) to achieve these temperatures are described. Benefits of ultra-high temperature propulsion are discussed for two missions - orbit transfer (ΔV = 5546 m/s) and interplanetary exploration (ΔV = 20000 m/s). For such missions ultra-high temperatures appear to be worth the additional complexity. Thrust levels are reduced substantially for a given power level, due to the higher enthalpy caused by partial disassociation of the hydrogen propellant. Though technically challenging, it appears potentially feasible to achieve such ultra high temperatures using the PBR

Automated pattern recognition system for noise analysis

International Nuclear Information System (INIS)

Sides, W.H. Jr.; Piety, K.R.

1980-01-01

A pattern recognition system was developed at ORNL for on-line monitoring of noise signals from sensors in a nuclear power plant. The system continuousy measures the power spectral density (PSD) values of the signals and the statistical characteristics of the PSDs in unattended operation. Through statistical comparison of current with past PSDs (pattern recognition), the system detects changes in the noise signals. Because the noise signals contain information about the current operational condition of the plant, a change in these signals could indicate a change, either normal or abnormal, in the operational condition

FY 1998 result report on the leading R and D of MGC ultra-high efficiency turbine system technology; 1998 nendo MGC chokokoritsu turbine system gijutsu sendo kenkyu kaihatsu seika hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

1999-03-01

One of the main subjects for further conserving energy by enhancing efficiency of gas turbine system for power generation, etc. is the heightening of operation temperature. The development is urgently needed of heat-resistant ultra-high temperature members which make high-reliable operation under ultra-high temperature possible. Therefore, an introductory study was made aiming at using MGC materials which does not reduce strength even at high temperature and also has plastic deformability as large-size structure members of gas turbine system for power generation use. In FY 1998, the following were studied: (1) basic study to get material design guidelines for making efficiency of MGC materials higher; (2) construction of the basic data for elucidating the manifestation mechanism of high temperature characteristics of MGC materials; (3) setting of gas turbine specifications which are to be the basis of study work in and after FY 1999; (4) setting of parameters to be evaluated, evaluation criteria, etc., and definition of the evaluation criteria for possibility of establishing an MGC ultra-high efficiency gas turbine system. (NEDO)

Formal Implementation of a Performance Evaluation Model for the Face Recognition System

Directory of Open Access Journals (Sweden)

Yong-Nyuo Shin

2008-01-01

Full Text Available Due to usability features, practical applications, and its lack of intrusiveness, face recognition technology, based on information, derived from individuals' facial features, has been attracting considerable attention recently. Reported recognition rates of commercialized face recognition systems cannot be admitted as official recognition rates, as they are based on assumptions that are beneficial to the specific system and face database. Therefore, performance evaluation methods and tools are necessary to objectively measure the accuracy and performance of any face recognition system. In this paper, we propose and formalize a performance evaluation model for the biometric recognition system, implementing an evaluation tool for face recognition systems based on the proposed model. Furthermore, we performed evaluations objectively by providing guidelines for the design and implementation of a performance evaluation system, formalizing the performance test process.

Active Multimodal Sensor System for Target Recognition and Tracking.

Science.gov (United States)

Qu, Yufu; Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-06-28

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system.

Container-code recognition system based on computer vision and deep neural networks

Science.gov (United States)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Neural Mechanisms and Information Processing in Recognition Systems

Directory of Open Access Journals (Sweden)

Mamiko Ozaki

2014-10-01

Full Text Available Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold.

Automated road marking recognition system

Science.gov (United States)

Ziyatdinov, R. R.; Shigabiev, R. R.; Talipov, D. N.

2017-09-01

Development of the automated road marking recognition systems in existing and future vehicles control systems is an urgent task. One way to implement such systems is the use of neural networks. To test the possibility of using neural network software has been developed with the use of a single-layer perceptron. The resulting system based on neural network has successfully coped with the task both when driving in the daytime and at night.

Enhancement of Iris Recognition System Based on Phase Only Correlation

Directory of Open Access Journals (Sweden)

Nuriza Pramita

2011-08-01

Full Text Available Iris recognition system is one of biometric based recognition/identification systems. Numerous techniques have been implemented to achieve a good recognition rate, including the ones based on Phase Only Correlation (POC. Significant and higher correlation peaks suggest that the system recognizes iris images of the same subject (person, while lower and unsignificant peaks correspond to recognition of those of difference subjects. Current POC methods have not investigated minimum iris point that can be used to achieve higher correlation peaks. This paper proposed a method that used only one-fourth of full normalized iris size to achieve higher (or at least the same recognition rate. Simulation on CASIA version 1.0 iris image database showed that averaged recognition rate of the proposed method achieved 67%, higher than that of using one-half (56% and full (53% iris point. Furthermore, all (100% POC peak values of the proposed method was higher than that of the method with full iris points.

Bridging ultrahigh-Q devices and photonic circuits

Science.gov (United States)

Yang, Ki Youl; Oh, Dong Yoon; Lee, Seung Hoon; Yang, Qi-Fan; Yi, Xu; Shen, Boqiang; Wang, Heming; Vahala, Kerry

2018-05-01

Optical microresonators are essential to a broad range of technologies and scientific disciplines. However, many of their applications rely on discrete devices to attain challenging combinations of ultra-low-loss performance (ultrahigh Q) and resonator design requirements. This prevents access to scalable fabrication methods for photonic integration and lithographic feature control. Indeed, finding a microfabrication bridge that connects ultrahigh-Q device functions with photonic circuits is a priority of the microcavity field. Here, an integrated resonator having a record Q factor over 200 million is presented. Its ultra-low-loss and flexible cavity design brings performance to integrated systems that has been the exclusive domain of discrete silica and crystalline microcavity devices. Two distinctly different devices are demonstrated: soliton sources with electronic repetition rates and high-coherence/low-threshold Brillouin lasers. This multi-device capability and performance from a single integrated cavity platform represents a critical advance for future photonic circuits and systems.

Automatic TLI recognition system. Part 1: System description

Energy Technology Data Exchange (ETDEWEB)

Partin, J.K.; Lassahn, G.D.; Davidson, J.R.

1994-05-01

This report describes an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system uses image data fusion and gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. This volume gives a general description of the ATR system.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

Science.gov (United States)

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2018-04-01

Full Text Available Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD method for an iris recognition system (iPAD using a near infrared light (NIR camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED. Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM. Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

Science.gov (United States)

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Development of an ultrahigh-resolution Si-PM-based dual-head GAGG coincidence imaging system

Science.gov (United States)

Yamamoto, Seiichi; Watabe, Hiroshi; Kanai, Yasukazu; Kato, Katsuhiko; Hatazawa, Jun

2013-03-01

A silicon photomultiplier (Si-PM) is a promising photodetector for high resolution PET systems due to its small channel size and high gain. Using Si-PMs, it will be possible to develop a high resolution imaging systems. For this purpose, we developed a small field-of-view (FOV) ultrahigh-resolution Si-PM-based dual-head coincidence imaging system for small animals and plant research. A new scintillator, Ce doped Gd3Al12Ga3O12 (GAGG), was selected because of its high light output and its emission wavelength matched with the Si-PM arrays and contained no radioactivity. Each coincidence imaging block detector consists of 0.5×0.5×5 mm3 GAGG pixels combined with a 0.1-mm thick reflector to form a 20×17 matrix that was optically coupled to a Si-PM array (Hamamatsu MPPC S11064-050P) with a 1.5-mm thick light guide. The GAGG block size was 12.0×10.2 mm2. Two GAGG block detectors were positioned face to face and set on a flexible arm based detector stand. All 0.5 mm GAGG pixels in the block detectors were clearly resolved in the 2-dimensional position histogram. The energy resolution was 14.4% FWHM for the Cs-137 gamma ray. The spatial resolution was 0.7 mm FWHM measured using a 0.25 mm diameter Na-22 point source. Small animal and plant images were successfully obtained. We conclude that our developed ultrahigh-resolution Si-PM-based dual-head coincidence imaging system is promising for small animal and plant imaging research.

Optical-electronic shape recognition system based on synergetic associative memory

Science.gov (United States)

Gao, Jun; Bao, Jie; Chen, Dingguo; Yang, Youqing; Yang, Xuedong

2001-04-01

This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system; the second is synergetic pattern recognition system. Hough transform is proposed for feature extraction of unrecognized object, with the effects of reducing dimensions and filtering for object distortion and noise, synergetic neural network is proposed for realizing associative memory in order to eliminate spurious states. Then we adopt an approach of optical- electronic realization to our system that can satisfy the demands of real time, high speed and parallelism. In order to realize fast algorithm, we replace the dynamic evolution circuit with adjudge circuit according to the relationship between attention parameters and order parameters, then implement the recognition of some simple images and its validity is proved.

Developing a Credit Recognition System for Chinese Higher Education Institutions

Science.gov (United States)

Li, Fuhui

2015-01-01

In recent years, a credit recognition system has been developing in Chinese higher education institutions. Much research has been done on this development, but it has been concentrated on system building, barriers/issues and international practices. The relationship between credit recognition system reforms and democratisation of higher education…

Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

Science.gov (United States)

Fang, Fuming; Shinozaki, Takahiro

2018-01-01

Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

Improved pattern recognition systems by hybrid methods

International Nuclear Information System (INIS)

Duerr, B.; Haettich, W.; Tropf, H.; Winkler, G.; Fraunhofer-Gesellschaft zur Foerderung der Angewandten Forschung e.V., Karlsruhe

1978-12-01

This report describes a combination of statistical and syntactical pattern recongition methods. The hierarchically structured recognition system consists of a conventional statistical classifier, a structural classifier analysing the topological composition of the patterns, a stage reducing the number of hypotheses made by the first two stages, and a mixed stage based on a search for maximum similarity between syntactically generated prototypes and patterns. The stages work on different principles to avoid mistakes made in one stage in the other stages. This concept is applied to the recognition of numerals written without constraints. If no samples are rejected, a recognition rate of 99,5% is obtained. (orig.) [de

Automated Degradation Diagnosis in Character Recognition System Subject to Camera Vibration

Directory of Open Access Journals (Sweden)

Chunmei Liu

2014-01-01

Full Text Available Degradation diagnosis plays an important role for degraded character processing, which can tell the recognition difficulty of a given degraded character. In this paper, we present a framework for automated degraded character recognition system by statistical syntactic approach using 3D primitive symbol, which is integrated by degradation diagnosis to provide accurate and reliable recognition results. Our contribution is to design the framework to build the character recognition submodels corresponding to degradation subject to camera vibration or out of focus. In each character recognition submodel, statistical syntactic approach using 3D primitive symbol is proposed to improve degraded character recognition performance. In the experiments, we show attractive experimental results, highlighting the system efficiency and recognition performance by statistical syntactic approach using 3D primitive symbol on the degraded character dataset.

The design and structure of the ultra-high vacuum system of HIRFL-CSR

International Nuclear Information System (INIS)

Yang Xiaotian; Zhang Junhui; Zhang Xinjun; Meng Jun; Zhan Wenlong

2001-01-01

To minimize the beam loss due to charge exchange of very heavy ions with the residual gas molecules, ultra-high vacuum of 6x10 -9 Pa is required for the HIRFL-CSR facility, which is the lowest pressure in a large vacuum system in China up to now. The total length of the system is about 450 meters and the total inner surface is about 263 square meters. More than 500 standard vacuum components are needed and more than 400 different chambers have to be manufactured. A lot of researches have been down to try to find out the experiences to obtain the required pressure. In this article the following contents are described: the layout of the system; the structure of main vacuum chambers; the treatment method to reduce the outgassing rate of the chamber wall surfaces; vacuum equipment; pressure distribution and the progress of the system

9th International Conference on Computer Recognition Systems

CERN Document Server

Jackowski, Konrad; Kurzyński, Marek; Woźniak, Michał; Żołnierek, Andrzej

2016-01-01

The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.  .

Ultra-flattened nearly-zero dispersion and ultrahigh nonlinear slot silicon photonic crystal fibers with ultrahigh birefringence

Science.gov (United States)

Liao, Jianfei; Xie, Yingmao; Wang, Xinghua; Li, Dongbo; Huang, Tianye

2017-07-01

A slot silicon photonic crystal fiber (PCF) is proposed to simultaneously achieve ultrahigh birefringence, large nonlinearity and ultra-flattened nearly-zero dispersion over a wide wavelength range. By taking advantage on the slot effect, ultrahigh birefringence up to 0.0736 and ultrahigh nonlinear coefficient up to 211.48 W-1 m-1 for quasi-TE mode can be obtained at the wavelength of 1.55 μm. Moreover, ultra-flattened dispersion of 0.49 ps/(nm km) for quasi-TE mode can be achieved over a 180 nm wavelength range with low dispersion slope of 1.85 × 10-3 ps/(nm2 km) at 1.55 μm. Leveraging on these advantages, the proposed slot PCF has great potential for efficient all-optical signal processing applications.

Intelligent Facial Recognition Systems: Technology advancements for security applications

Energy Technology Data Exchange (ETDEWEB)

Beer, C.L.

1993-07-01

Insider problems such as theft and sabotage can occur within the security and surveillance realm of operations when unauthorized people obtain access to sensitive areas. A possible solution to these problems is a means to identify individuals (not just credentials or badges) in a given sensitive area and provide full time personnel accountability. One approach desirable at Department of Energy facilities for access control and/or personnel identification is an Intelligent Facial Recognition System (IFRS) that is non-invasive to personnel. Automatic facial recognition does not require the active participation of the enrolled subjects, unlike most other biological measurement (biometric) systems (e.g., fingerprint, hand geometry, or eye retinal scan systems). It is this feature that makes an IFRS attractive for applications other than access control such as emergency evacuation verification, screening, and personnel tracking. This paper discusses current technology that shows promising results for DOE and other security applications. A survey of research and development in facial recognition identified several companies and universities that were interested and/or involved in the area. A few advanced prototype systems were also identified. Sandia National Laboratories is currently evaluating facial recognition systems that are in the advanced prototype stage. The initial application for the evaluation is access control in a controlled environment with a constant background and with cooperative subjects. Further evaluations will be conducted in a less controlled environment, which may include a cluttered background and subjects that are not looking towards the camera. The outcome of the evaluations will help identify areas of facial recognition systems that need further development and will help to determine the effectiveness of the current systems for security applications.

Constraints in distortion-invariant target recognition system simulation

Science.gov (United States)

Iftekharuddin, Khan M.; Razzaque, Md A.

2000-11-01

Automatic target recognition (ATR) is a mature but active research area. In an earlier paper, we proposed a novel ATR approach for recognition of targets varying in fine details, rotation, and translation using a Learning Vector Quantization (LVQ) Neural Network (NN). The proposed approach performed segmentation of multiple objects and the identification of the objects using LVQNN. In this current paper, we extend the previous approach for recognition of targets varying in rotation, translation, scale, and combination of all three distortions. We obtain the analytical results of the system level design to show that the approach performs well with some constraints. The first constraint determines the size of the input images and input filters. The second constraint shows the limits on amount of rotation, translation, and scale of input objects. We present the simulation verification of the constraints using DARPA's Moving and Stationary Target Recognition (MSTAR) images with different depression and pose angles. The simulation results using MSTAR images verify the analytical constraints of the system level design.

Implementation of age and gender recognition system for intelligent digital signage

Science.gov (United States)

Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

2015-12-01

Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

An artificial odor recognition system is developed for discriminating odors

Directory of Open Access Journals (Sweden)

Wisnu Jatmiko

2002-12-01

Full Text Available This artificial system consisted of 16 quartz resonator crystals as the sensor array, a frequency modulator and a frequency counter for each sensor that are connected directly to a microcomputer. We have already shown that the artificial odor recognition system with 4 sensors is high enough to discriminate simple odor correctly, however, when it was used to discriminate compound odors, the recognition capability of this system is dropped significantly to be about 40%. Results of experiments show that the developed artificial system with 16 sensors could discriminate compound aroma based on 6 gradient of alcohol concentrations with high recognition rate of 89.9% for non batch processing system, and 82.4% for batch processing of the classes of odors.

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.

Increased Efficiency of Face Recognition System using Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Rajani Muraleedharan

2006-02-01

Full Text Available This research was inspired by the need of a flexible and cost effective biometric security system. The flexibility of the wireless sensor network makes it a natural choice for data transmission. Swarm intelligence (SI is used to optimize routing in distributed time varying network. In this paper, SI maintains the required bit error rate (BER for varied channel conditions while consuming minimal energy. A specific biometric, the face recognition system, is discussed as an example. Simulation shows that the wireless sensor network is efficient in energy consumption while keeping the transmission accuracy, and the wireless face recognition system is competitive to the traditional wired face recognition system in classification accuracy.

Imaging at ultrahigh magnetic fields: History, challenges, and solutions.

Science.gov (United States)

Uğurbil, Kamil

2018-03-01

Following early efforts in applying nuclear magnetic resonance (NMR) spectroscopy to study biological processes in intact systems, and particularly since the introduction of 4 T human scanners circa 1990, rapid progress was made in imaging and spectroscopy studies of humans at 4 T and animal models at 9.4 T, leading to the introduction of 7 T and higher magnetic fields for human investigation at about the turn of the century. Work conducted on these platforms has provided numerous technological solutions to challenges posed at these ultrahigh fields, and demonstrated the existence of significant advantages in signal-to-noise ratio and biological information content. Primary difference from lower fields is the deviation from the near field regime at the radiofrequencies (RF) corresponding to hydrogen resonance conditions. At such ultrahigh fields, the RF is characterized by attenuated traveling waves in the human body, which leads to image non-uniformities for a given sample-coil configuration because of destructive and constructive interferences. These non-uniformities were initially considered detrimental to progress of imaging at high field strengths. However, they are advantageous for parallel imaging in signal reception and transmission, two critical technologies that account, to a large extend, for the success of ultrahigh fields. With these technologies and improvements in instrumentation and imaging methods, today ultrahigh fields have provided unprecedented gains in imaging of brain function and anatomy, and started to make inroads into investigation of the human torso and extremities. As extensive as they are, these gains still constitute a prelude to what is to come given the increasingly larger effort committed to ultrahigh field research and development of ever better instrumentation and techniques. Copyright © 2017 Elsevier Inc. All rights reserved.

New method for the simultaneous condensation of complete ternary alloy systems under ultrahigh vacuum conditions

International Nuclear Information System (INIS)

Mehrtens, A.; Moske, M.; Samwer, K.

1988-01-01

An ultrahigh vacuum apparatus is described for the simultaneous condensation of complete ternary alloy systems. Three singly controlled electron beam evaporation sources provide a constant evaporation rate of the different elements. A specially designed rotating mask guarantees a concentration gradient on the substrate according to a ternary phase diagram. The conversion of the actual concentration profile into a standard ternary phase diagram is done by simple computer calculations. They involve corrections for the beam characteristics of the evaporation sources and for the rotating mask. As an example, measurements for the Zr--Cu--Co system are given. The concentration range for the amorphous phase is compared with thermodynamic predictions using Miedema's parameter

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.

TFTR ultrahigh-vacuum pumping system incorporating mercury diffusion pumps

International Nuclear Information System (INIS)

Sink, D.A.; Sniderman, M.

1976-06-01

The TFTR vacuum vessel will have a system of four 61 cm diameter mercury diffusion pumps to provide a base pressure in the 10 -8 to 10 -9 Torr range as well as a low impurity level within the vessel. The system, called the Torus Vacuum Pumping System (TVPS), will be employed with the aid of an occasional 250 0 C bakeout in situ as well as periodic applications of aggressive discharge cleaning. The TVPS is an ultrahigh-vacuum (UHV) system using no elastomers as well as being a closed system with respect to tritium or any tritiated gases. The backing system employing approximately 75 all-metal isolation valves is designed with the features of redundancy and flexibility employed in a variety of ways to meet the fundamental requirements and functions enumerated for the TVPS. Since the design, is one which is a modification of the conceptual design of the TVPS, those features which have changed are discussed. Calculations are presented for the major performance parameters anticipated for the TVPS and include conductances, effective pumping speeds, base pressures, operating parameters, getter pump parameters, and calculations of time constants associated with leak checking. Modifications in the vacuum pumping system for the guard regions on the twelve bellows sections are presented so that it is compatible with the main TVPS. The bellows pumping system consists of a mechanical pump unit, a zirconium aluminum getter pump unit and a residual gas analyzer. The control and management of the TVPS is described with particular attention given to providing both manual and automatic control at a local station and at the TFTR Central Control. Such operations as testing, maintenance, leak checking, startup, bakeout, and various other operations are considered in some detail. Various aspects related to normal pulsing, discharge cleaning, non-tritium operations and tritium operations are also taken into consideration. A cost estimate is presented

The NA50 segmented target and vertex recognition system

International Nuclear Information System (INIS)

Bellaiche, F.; Cheynis, B.; Contardo, D.; Drapier, O.; Grossiord, J.Y.; Guichard, A.; Haroutunian, R.; Jacquin, M.; Ohlsson-Malek, F.; Pizzi, J.R.

1997-01-01

The NA50 segmented target and vertex recognition system is described. The segmented target consists of 7 sub-targets of 1-2 mm thickness. The vertex recognition system used to determine the sub-target where an interaction has occured is based upon quartz elements which produce Cerenkov light when traversed by charged particles from the interaction. The geometrical arrangement of the quartz elements has been optimized for vertex recognition in 208 Pb-Pb collisions at 158 GeV/nucleon. A simple algorithm provides a vertex recognition efficiency of better than 85% for dimuon trigger events collected with a 1 mm sub-target set-up. A method for recognizing interactions of projectile fragments (nuclei and/or groups of nucleons) is presented. The segmented target allows a large target thickness which together with a high beam intensity (∼10 7 ions/s) enables high statistics measurements. (orig.)

Adamantane in Drug Delivery Systems and Surface Recognition.

Science.gov (United States)

Štimac, Adela; Šekutor, Marina; Mlinarić-Majerski, Kata; Frkanec, Leo; Frkanec, Ruža

2017-02-16

The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

Adamantane in Drug Delivery Systems and Surface Recognition

Directory of Open Access Journals (Sweden)

Adela Štimac

2017-02-01

Full Text Available The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

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)

Optical character recognition systems for different languages with soft computing

CERN Document Server

Chaudhuri, Arindam; Badelia, Pratixa; K Ghosh, Soumya

2017-01-01

The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

Profile measurement of a bent neutron mirror using an ultrahigh precision non-contact measurement system with an auto focus laser probe

International Nuclear Information System (INIS)

Morita, S; Guo, J; Yamagata, Y; Yamada, N L; Torikai, N; Takeda, S; Furusaka, M

2016-01-01

A bent neutron mirror has been considered as one of the best solutions for focusing neutron beams from the viewpoint of cost-benefit performance. Although the form deviation of the bent profile is expected because of the large spot size, it is difficult to measure due to its geometric limitation. Here, we propose a non-contact measurement system using an auto focus (AF) laser probe on an ultrahigh precision machine tool to precisely evaluate the form deviation of the bent mirror. The AF laser probe is composed of a diode laser, a position sensitive sensor, a charge-coupled device (CCD) camera and a microscope objective lens which is actuated by an electromagnetic motor with 1 nm resolution for position sensing and control. The sensor enables a non-contact profile measurement of a high precision surface without any surface damage in contrast with contact-type ultrahigh precision coordinate measurement machines with ruby styli. In the on-machine measurement system, a personal computer simultaneously acquires a displacement signal from the AF laser probe and 3-axis positional coordinates of the ultrahigh machine tool branched between the linear laser scales and the numerical controller. The acquisition rate of the 4-axis positional data in 1 nm resolution is more than 10 Hz and the simultaneity between the axes is negligible. The profile of a neutron bent mirror was measured from a transparent side using the developed system, and the result proves that the form deviation of the mirror enlarged the the spot size of focused neuron beam. (paper)

UNCONSTRAINED HANDWRITING RECOGNITION : LANGUAGE MODELS, PERPLEXITY, AND SYSTEM PERFORMANCE

NARCIS (Netherlands)

Marti, U-V.; Bunke, H.

2004-01-01

In this paper we present a number of language models and their behavior in the recognition of unconstrained handwritten English sentences. We use the perplexity to compare the different models and their prediction power, and relate it to the performance of a recognition system under different

Concrete Materials with Ultra-High Damage Resistance and Self- Sensing Capacity for Extended Nuclear Fuel Storage Systems

Energy Technology Data Exchange (ETDEWEB)

Li, Mo [Univ. of California, Irvine, CA (United States); Nakshatrala, Kalyana [Univ. of Houston, TX (United States); William, Kasper [Univ. of Houston, TX (United States); Xi, Yungping [Univ. of Colorado, Boulder, CO (United States)

2017-02-08

The objective of this project is to develop a new class of multifunctional concrete materials (MSCs) for extended spent nuclear fuel (SNF) storage systems, which combine ultra-high damage resistance through strain-hardening behavior with distributed multi-dimensional damage self-sensing capacity. The beauty of multifunctional concrete materials is two-fold: First, it serves as a major material component for the SNF pool, dry cask shielding and foundation pad with greatly improved resistance to cracking, reinforcement corrosion, and other common deterioration mechanisms under service conditions, and prevention from fracture failure under extreme events (e.g. impact, earthquake). This will be achieved by designing multiple levels of protection mechanisms into the material (i.e., ultrahigh ductility that provides thousands of times greater fracture energy than concrete and normal fiber reinforced concrete; intrinsic cracking control, electrochemical properties modification, reduced chemical and radionuclide transport properties, and crack-healing properties). Second, it offers capacity for distributed and direct sensing of cracking, strain, and corrosion wherever the material is located. This will be achieved by establishing the changes in electrical properties due to mechanical and electrochemical stimulus. The project will combine nano-, micro- and composite technologies, computational mechanics, durability characterization, and structural health monitoring methods, to realize new MSCs for very long-term (greater than 120 years) SNF storage systems.

Exhibits Recognition System for Combining Online Services and Offline Services

Science.gov (United States)

Ma, He; Liu, Jianbo; Zhang, Yuan; Wu, Xiaoyu

2017-10-01

In order to achieve a more convenient and accurate digital museum navigation, we have developed a real-time and online-to-offline museum exhibits recognition system using image recognition method based on deep learning. In this paper, the client and server of the system are separated and connected through the HTTP. Firstly, by using the client app in the Android mobile phone, the user can take pictures and upload them to the server. Secondly, the features of the picture are extracted using the deep learning network in the server. With the help of the features, the pictures user uploaded are classified with a well-trained SVM. Finally, the classification results are sent to the client and the detailed exhibition’s introduction corresponding to the classification results are shown in the client app. Experimental results demonstrate that the recognition accuracy is close to 100% and the computing time from the image uploading to the exhibit information show is less than 1S. By means of exhibition image recognition algorithm, our implemented exhibits recognition system can combine online detailed exhibition information to the user in the offline exhibition hall so as to achieve better digital navigation.

Automated recognition system for ELM classification in JET

International Nuclear Information System (INIS)

Duro, N.; Dormido, R.; Vega, J.; Dormido-Canto, S.; Farias, G.; Sanchez, J.; Vargas, H.; Murari, A.

2009-01-01

Edge localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. Considerable efforts are being devoted to understanding the physics behind this non-linear phenomenon. A first characterization of ELMs is usually their identification as type I or type III. An automated pattern recognition system has been developed in JET for off-line ELM recognition and classification. The empirical method presented in this paper analyzes each individual ELM instead of starting from a temporal segment containing many ELM bursts. The ELM recognition and isolation is carried out using three signals: Dα, line integrated electron density and stored diamagnetic energy. A reduced set of characteristics (such as diamagnetic energy drop, ELM period or Dα shape) has been extracted to build supervised and unsupervised learning systems for classification purposes. The former are based on support vector machines (SVM). The latter have been developed with hierarchical and K-means clustering methods. The success rate of the classification systems is about 98% for a database of almost 300 ELMs.

Speech recognition systems on the Cell Broadband Engine

Energy Technology Data Exchange (ETDEWEB)

Liu, Y; Jones, H; Vaidya, S; Perrone, M; Tydlitat, B; Nanda, A

2007-04-20

In this paper we describe our design, implementation, and first results of a prototype connected-phoneme-based speech recognition system on the Cell Broadband Engine{trademark} (Cell/B.E.). Automatic speech recognition decodes speech samples into plain text (other representations are possible) and must process samples at real-time rates. Fortunately, the computational tasks involved in this pipeline are highly data-parallel and can receive significant hardware acceleration from vector-streaming architectures such as the Cell/B.E. Identifying and exploiting these parallelism opportunities is challenging, but also critical to improving system performance. We observed, from our initial performance timings, that a single Cell/B.E. processor can recognize speech from thousands of simultaneous voice channels in real time--a channel density that is orders-of-magnitude greater than the capacity of existing software speech recognizers based on CPUs (central processing units). This result emphasizes the potential for Cell/B.E.-based speech recognition and will likely lead to the future development of production speech systems using Cell/B.E. clusters.

Application of Video Recognition Technology in Landslide Monitoring System

Directory of Open Access Journals (Sweden)

Qingjia Meng

2018-01-01

Full Text Available The video recognition technology is applied to the landslide emergency remote monitoring system. The trajectories of the landslide are identified by this system in this paper. The system of geological disaster monitoring is applied synthetically to realize the analysis of landslide monitoring data and the combination of video recognition technology. Landslide video monitoring system will video image information, time point, network signal strength, power supply through the 4G network transmission to the server. The data is comprehensively analysed though the remote man-machine interface to conduct to achieve the threshold or manual control to determine the front-end video surveillance system. The system is used to identify the target landslide video for intelligent identification. The algorithm is embedded in the intelligent analysis module, and the video frame is identified, detected, analysed, filtered, and morphological treatment. The algorithm based on artificial intelligence and pattern recognition is used to mark the target landslide in the video screen and confirm whether the landslide is normal. The landslide video monitoring system realizes the remote monitoring and control of the mobile side, and provides a quick and easy monitoring technology.

Spoof Detection for Finger-Vein Recognition System Using NIR Camera

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2017-10-01

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

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

Science.gov (United States)

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

2017-10-01

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

Characterization and usage of the EASY-spray technology as part of an online 2D SCX-RP ultra-high pressure system

NARCIS (Netherlands)

Marino, Fabio; Cristobal, Alba; Binai, Nadine A; Bache, Nicolai; Heck, Albert J R; Mohammed, Shabaz

2014-01-01

Ultra-high pressure liquid chromatography (UHPLC) systems combined with state-of-the-art mass spectrometers have pushed the limit of deep proteome sequencing to new heights making it possible to identify thousands of proteins in a single LC-MS experiment within a few hours. The recently released

System of breast cancer recognition

International Nuclear Information System (INIS)

Rozhkova, N.I.

1984-01-01

The paper is concerned with the resUlts of the multimodality system of breast cancer recognition using methods, of clinical X-ray and cytological examinations. Altogether 1671 women were examined; breast cancer was detected in 165. Stage 1 was detected in 63 patients, Stage 2 in 34, Stage 3 in 34, and Stage 4 in 8. In 7% of the cases, tumors were inpalpable and could be detected by X-ray only. In 9.9% of the cases, the multicentric nature of tumor growth was established. In 71% tumors had a mixed histological structure. The system of breast cancer recognition provided for accurate diagnosis in 98% of the cases making it possible to avoid surgical intervention in 38%. Good diagnostic results are possible under conditions of a special mammology unit where a roentgenologist working in a close contact with surgeonns working in a close contact with surgeos and morphologists, performs the first stages of diagnosis beginning from clinical examination up to special methods that require X-ray control (paracentesis, ductography, pneumocystography, preoperative marking of the breast and marking of the remote sectors of the breast)

Modification of Ultra-High Vacuum Surfaces Using Free Radicals

CERN Document Server

Vorlaufer, G

2002-01-01

In ultra-high vacuum systems outgassing from vacuum chamber walls and desorption of surface adsorbates are usually the factors which determine pressure and residual gas composition. In particular in beam vacuum systems of accelerators like the LHC, where surfaces are exposed to intense synchrotron radiation and bombardment by energetic ions and electrons, surface properties like the molecular desorption yield or secondary electron yield can strongly influence the performance of the accelerator. Well-established treatment methods like vacuum bake-out or glow-discharge cleaning have been successfully applied in the past to condition ultra-high vacuum surfaces, but these methods are sometimes difficult to carry out, for example if the vacuum chambers are not accessible. In this work, an alternative treatment method is investigated. This method is based on the strong chemical reactivity of free radicals, electrically neutral fragments of molecules. Free radicals (in the case of this work, nitrogen and oxygen radi...

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

Science.gov (United States)

Huntsberger, Terry

2011-01-01

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

Connected digit speech recognition system for Malayalam language

Indian Academy of Sciences (India)

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual ...

Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

Science.gov (United States)

Winda, A.; E Byan, W. R.; Sofyan; Armansyah; Zariantin, D. L.; Josep, B. G.

2017-03-01

Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is ‘On’ or ‘Off’. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.

Adamantane in Drug Delivery Systems and Surface Recognition

OpenAIRE

Adela Štimac; Marina Šekutor; Kata Mlinarić-Majerski; Leo Frkanec; Ruža Frkanec

2017-01-01

The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based struc...

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

Science.gov (United States)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Face recognition system and method using face pattern words and face pattern bytes

Science.gov (United States)

Zheng, Yufeng

2014-12-23

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

2nd International Symposium on Signal Processing and Intelligent Recognition Systems

CERN Document Server

Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

2016-01-01

This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

SU-F-J-45: Sparing Normal Tissue with Ultra-High Dose Rate in Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Feng, Y [DCH Reg. Medical Center, Tuscaloosa, AL (United States)

2016-06-15

Purpose: To spare normal tissue by reducing the location uncertainty of a moving target, we proposed an ultra-high dose rate system and evaluated. Methods: High energy electrons generated with a linear accelerator were injected into a storage ring to be accumulated. The number of the electrons in the ring was determined based on the prescribed radiation dose. The dose was delivered within a millisecond, when an online imaging system found that the target was in the position that was consistent with that in a treatment plan. In such a short time period, the displacement of the target was negligible. The margin added to the clinical target volume (CTV) could be reduced that was evaluated by comparing of volumes between CTV and ITV in 14 cases of lung stereotactic body radiation therapy (SBRT) treatments. A design of the ultra-high dose rate system was evaluated based clinical needs and the recent developments of low energy (a few MeV) electron storage ring. Results: This design of ultra-high dose rate system was feasible based on the techniques currently available. The reduction of a target volume was significant by reducing the margin that accounted the motion of the target. ∼50% volume reduction of the internal target volume (ITV) could be achieved in lung SBRT treatments. Conclusion: With this innovation of ultra-high dose rate system, the margin of target is able to be significantly reduced. It will reduce treatment time of gating and allow precisely specified gating window to improve the accuracy of dose delivering.

Ultrahigh-brightness KrF laser system for fast ignition studies

International Nuclear Information System (INIS)

Shaw, M.J.; Ross, I.N.; Hooker, C.J.; Dodson, J.M.; Hirst, G.J.; Lister, J.M.D.; Divall, E.J.; Kidd, A.K.; Hancock, S.; Damerell, A.R.; Wyborn, B.E.

1999-01-01

The main requirements for a fast igniter laser beam are reviewed and shown to favour short wavelength and ultrahigh brightness. These requirements are met by the new KrF laser system at Rutherford Appleton Laboratory called TITANIA. TITANIA uses two schemes to enhance the laser beam brightness. The first is chirped pulse amplification which is used to enhance brightness by compressing the pulse into the femtosecond region. In this mode TITANIA produces in the region of 250 mJ on target in 700 fs. The second mode of operation uses a Raman technique for beam combining and beam clean-up which is designed to give a single beam of 80 Joules on target in a pulselength of 60 ps. In this scheme the KrF wavelength is Raman shifted to 268 nm. The Raman amplifiers will use gaseous rather than solid windows and experiments which demonstrate their feasibility will be described. A concept for a reactor scale fast igniter beam using the Raman technique will be discussed. (orig.)

Ultra-high vacuum system of the Brookhaven National Synchrotron Light Source

Energy Technology Data Exchange (ETDEWEB)

Foerster, C.L.

1995-12-31

The rings of the National Synchrotron Light Source (NSLS) have been supplying light to numerous users for approximately a decade and we recently enjoyed a fully conditioned machine vacuum at design currents. A brief description of the X-Ray storage ring, the VUV storage ring and their current supply is given along with some of their features. The ultra-high vacuum system employed for the storage rings and their advantages for the necessary stored beam environments are discussed including, a brief history of time. After several hundred amp hours of stored beam current operation, very little improvement in machine performance was seen due to conditioning. Sections of the rings were vented, to dry nitrogen and replacement components were pre-baked and pre-argon glow conditioned prior to installation. Very little machine conditioning was needed to return to operation after recovering vacuum due to well established conditioning procedures. All straight sections in the X-Ray ring and the VUV ring have been filled with various insertion devices and most are fully operational. Each storage ring has a computer controlled total pressure and partial pressure monitoring system for the ring and its beam ports, to insure good vacuum.

Processing and evaluation of the AGS Booster ultra-high vaccum system

International Nuclear Information System (INIS)

Hseuh, H.C.; Mapes, M.; Schnitzenbaumer, P.; Shen, B.; Sikora, R.; Stattel, P.

1991-01-01

The AGS Booster is a synchrotron for the acceleration of both protons and heavy ions. To minimize the beam loss due to charge exchange of the partially stripped, low Β very heavy ions with the residual gas molecules, pressure of low 10 -11 Torr is required for the 200 m booster ring. To achieve this ultra high vacuum, chemical cleaning, vacuum furnace degassing and insitu bake were employed for all chambers and beam components. Using these procedures, vacuums of low 10 -11 Torr have been routinely achieved during the testing of individual half cells and beam components, and during the commissioning of the vacuum sectors. In this paper, the design and layout of chambers, flanges and bakeout hardware is briefly described. The vacuum processing of different components and the results of bakeout and evaluation are summarized. The experience gained during the construction and commissioning of this ultra-high vacuum system is also given. 3 refs., 3 figs., 1 tab

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...

Ultra-high vacuum compatible optical chopper system for synchrotron x-ray scanning tunneling microscopy

Energy Technology Data Exchange (ETDEWEB)

Chang, Hao, E-mail: hc000211@ohio.edu [Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439 (United States); Nanoscale and Quantum Phenomena Institute, Physics & Astronomy Department, Ohio University, Athens, Ohio 45701 (United States); Cummings, Marvin; Shirato, Nozomi; Stripe, Benjamin; Preissner, Curt; Freeland, John W. [Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439 (United States); Rosenmann, Daniel [Center for Nanoscale Materials, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439 (United States); Kersell, Heath; Hla, Saw-Wai [Nanoscale and Quantum Phenomena Institute, Physics & Astronomy Department, Ohio University, Athens, Ohio 45701 (United States); Center for Nanoscale Materials, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439 (United States); Rose, Volker, E-mail: vrose@anl.gov [Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439 (United States); Center for Nanoscale Materials, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, Illinois 60439 (United States)

2016-01-28

High-speed beam choppers are a crucial part of time-resolved x-ray studies as well as a necessary component to enable elemental contrast in synchrotron x-ray scanning tunneling microscopy (SX-STM). However, many chopper systems are not capable of operation in vacuum, which restricts their application to x-ray studies with high photon energies, where air absorption does not present a significant problem. To overcome this limitation, we present a fully ultra-high vacuum (UHV) compatible chopper system capable of operating at variable chopping frequencies up to 4 kHz. The lightweight aluminum chopper disk is coated with Ti and Au films to provide the required beam attenuation for soft and hard x-rays with photon energies up to about 12 keV. The chopper is used for lock-in detection of x-ray enhanced signals in SX-STM.

An ultrahigh vacuum, low-energy ion-assisted deposition system for III-V semiconductor film growth

Science.gov (United States)

Rohde, S.; Barnett, S. A.; Choi, C.-H.

1989-06-01

A novel ion-assisted deposition system is described in which the substrate and growing film can be bombarded with high current densities (greater than 1 mA/sq cm) of very low energy (10-200 eV) ions. The system design philosophy is similar to that used in III-V semiconductor molecular-beam epitaxy systems: the chamber is an all-metal ultrahigh vacuum system with liquid-nitrogen-cooled shrouds, Knudsen-cell evaporation sources, a sample insertion load-lock, and a 30-kV reflection high-energy electron diffraction system. III-V semiconductor film growth is achieved using evaporated group-V fluxes and group-III elemental fluxes sputtered from high-purity targets using ions extracted from a triode glow discharge. Using an In target and an As effusion cell, InAs deposition rates R of 2 microns/h have been obtained. Epitaxial growth of InAs was observed on both GaSb(100) and Si(100) substrates.

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.

A Cooking Recipe Recommendation System with Visual Recognition of Food Ingredients

Directory of Open Access Journals (Sweden)

Keiji Yanai

2014-04-01

Full Text Available In this paper, we propose a cooking recipe recommendation system which runs on a consumer smartphone as an interactive mobile application. The proposed system employs real-time visual object recognition of food ingredients, and recommends cooking recipes related to the recognized food ingredients. Because of visual recognition, by only pointing a built-in camera on a smartphone to food ingredients, a user can get to know a related cooking recipes instantly. The objective of the proposed system is to assist people who cook to decide a cooking recipe at grocery stores or at a kitchen. In the current implementation, the system can recognize 30 kinds of food ingredient in 0.15 seconds, and it has achieved the 83.93% recognition rate within the top six candidates. By the user study, we confirmed the effectiveness of the proposed system.

A Support System for the Electric Appliance Control Using Pose Recognition

Science.gov (United States)

Kawano, Takuya; Yamamoto, Kazuhiko; Kato, Kunihito; Hongo, Hitoshi

In this paper, we propose an electric appliance control support system for aged and bedridden people using pose recognition. We proposed a pose recognition system that distinguishes between seven poses of the user on the bed. First, the face and arm regions of the user are detected by using the skin color. Our system focuses a recognition region surrounding the face region. Next, the higher order local autocorrelation features within the region are extracted. The linear discriminant analysis creates the coefficient matrix that can optimally distinguish among training data from the seven poses. Our algorithm can recognize the seven poses even if the subject wears different clothes and slightly shifts or slants on the bed. From the experimental results, our system achieved an accuracy rate of over 99 %. Then, we show that it possibles to construct one of a user-friendly system.

Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition

CERN Document Server

Melin, Patricia

2012-01-01

This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural ne...

Industrial robots with sensors and object recognition systems

International Nuclear Information System (INIS)

Koehler, G.W.

1978-01-01

The previous development and the present status of industrial robots equipped with sensors and object recognition systems are described. This type of equipment allows flexible automation of many work stations in which industrial robots of the first generation, which are unable to react to changes in their respective environments automatically, apart from their being linked to other machines, could not be used because of the prevailing boundary conditions. A classification system facilitates an overview of the large number of technical solutions now available. The manifold possibilities of application of this equipment are demonstrated by a number of examples. As a result of the present state of development of the components required, and in view also of economic reasons, there is a trend towards special designs for a small number of specific purposes and towards stripped-down object recognition. systems with limited applications. A fitting description is offered of the term 'robot', which is now being used in various contexts, and an indication is made of the capabilities and components a machine to be called robot should have as a minimum. Finally, reference is made to some potential lines of development serving to reduce expediture and accelerate recognition processes. (orig.) [de

Advanced Photon Source accelerator ultrahigh vacuum guide

International Nuclear Information System (INIS)

Liu, C.; Noonan, J.

1994-03-01

In this document the authors summarize the following: (1) an overview of basic concepts of ultrahigh vacuum needed for the APS project, (2) a description of vacuum design and calculations for major parts of APS, including linac, linac waveguide, low energy undulator test line, positron accumulator ring (PAR), booster synchrotron ring, storage ring, and insertion devices, and (3) cleaning procedures of ultrahigh vacuum (UHV) components presently used at APS

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...

Automatic system for localization and recognition of vehicle plate numbers

OpenAIRE

Vázquez, N.; Nakano, M.; Pérez-Meana, H.

2003-01-01

This paper proposes a vehicle numbers plate identification system, which extracts the characters features of a plate from a captured image by a digital camera. Then identify the symbols of the number plate using a multilayer neural network. The proposed recognition system consists of two processes: The training process and the recognition process. During the training process, a database is created using 310 vehicular plate images. Then using this database a multilayer neural network is traine...

Arm Motion Recognition and Exercise Coaching System for Remote Interaction

Directory of Open Access Journals (Sweden)

Hong Zeng

2016-01-01

Full Text Available Arm motion recognition and its related applications have become a promising human computer interaction modal due to the rapid integration of numerical sensors in modern mobile-phones. We implement a mobile-phone-based arm motion recognition and exercise coaching system that can help people carrying mobile-phones to do body exercising anywhere at any time, especially for the persons that have very limited spare time and are constantly traveling across cities. We first design improved k-means algorithm to cluster the collecting 3-axis acceleration and gyroscope data of person actions into basic motions. A learning method based on Hidden Markov Model is then designed to classify and recognize continuous arm motions of both learners and coaches, which also measures the action similarities between the persons. We implement the system on MIUI 2S mobile-phone and evaluate the system performance and its accuracy of recognition.

Implementation of CT and IHT Processors for Invariant Object Recognition System

Directory of Open Access Journals (Sweden)

J. Turan jr.

2004-12-01

Full Text Available This paper presents PDL or ASIC implementation of key modules ofinvariant object recognition system based on the combination of theIncremental Hough transform (IHT, correlation and rapid transform(RT. The invariant object recognition system was represented partiallyin C++ language for general-purpose processor on personal computer andpartially described in VHDL code for implementation in PLD or ASIC.

An intra-neural microstimulation system for ultra-high field magnetic resonance imaging and magnetoencephalography.

Science.gov (United States)

Glover, Paul M; Watkins, Roger H; O'Neill, George C; Ackerley, Rochelle; Sanchez-Panchuelo, Rosa; McGlone, Francis; Brookes, Matthew J; Wessberg, Johan; Francis, Susan T

2017-10-01

Intra-neural microstimulation (INMS) is a technique that allows the precise delivery of low-current electrical pulses into human peripheral nerves. Single unit INMS can be used to stimulate individual afferent nerve fibres during microneurography. Combining this with neuroimaging allows the unique monitoring of central nervous system activation in response to unitary, controlled tactile input, with functional magnetic resonance imaging (fMRI) providing exquisite spatial localisation of brain activity and magnetoencephalography (MEG) high temporal resolution. INMS systems suitable for use within electrophysiology laboratories have been available for many years. We describe an INMS system specifically designed to provide compatibility with both ultra-high field (7T) fMRI and MEG. Numerous technical and safety issues are addressed. The system is fully analogue, allowing for arbitrary frequency and amplitude INMS stimulation. Unitary recordings obtained within both the MRI and MEG screened-room environments are comparable with those obtained in 'clean' electrophysiology recording environments. Single unit INMS (current met. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Method for secure electronic voting system: face recognition based approach

Science.gov (United States)

Alim, M. Affan; Baig, Misbah M.; Mehboob, Shahzain; Naseem, Imran

2017-06-01

In this paper, we propose a framework for low cost secure electronic voting system based on face recognition. Essentially Local Binary Pattern (LBP) is used for face feature characterization in texture format followed by chi-square distribution is used for image classification. Two parallel systems are developed based on smart phone and web applications for face learning and verification modules. The proposed system has two tire security levels by using person ID followed by face verification. Essentially class specific threshold is associated for controlling the security level of face verification. Our system is evaluated three standard databases and one real home based database and achieve the satisfactory recognition accuracies. Consequently our propose system provides secure, hassle free voting system and less intrusive compare with other biometrics.

Using a data fusion-based activity recognition framework to determine surveillance system requirements

CSIR Research Space (South Africa)

Le Roux, WH

2007-07-01

Full Text Available A technique is proposed to extract system requirements for a maritime area surveillance system, based on an activity recognition framework originally intended for the characterisation, prediction and recognition of intentional actions for threat...

Euro Banknote Recognition System for Blind People.

Science.gov (United States)

Dunai Dunai, Larisa; Chillarón Pérez, Mónica; Peris-Fajarnés, Guillermo; Lengua Lengua, Ismael

2017-01-20

This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

Study on reactor building structure using ultrahigh strength materials, 1

International Nuclear Information System (INIS)

Ishimura, Kikuo; Odajima, Masahiro; Irino, Kazuo; Hashiba, Toshio.

1991-01-01

This study was promoted to be aimed at realization of the optimal nuclear reactor building structure of the future. As the first step, the study regarding ultrahigh strength reinforced concrete (abbr. RC) shear wall was selected. As the result of various tests, the application of ultrahigh strength RC shear walls was verified. The tests conducted were relevant to; ultrahigh strength concrete material tests; pure shear tests of RC flat panels; and bending shear tests and its simulation analysis of RC shear walls. (author)

Precision mechanical design of an ultrahigh-resolution inelastic x-ray scattering spectrometer system with CDFDW optics at the APS

International Nuclear Information System (INIS)

Shu, D; Stoupin, S; Khachatryan, R; Goetze, K A; Roberts, T; Shvyd'ko, Y; Mundboth, K; Collins, S

2013-01-01

There are many scientific applications, especially involving topics related to the equilibrium atomic-scale dynamics of condensed matter, that require both a narrower and a steeper resolution function and access to a broader dynamic range than are currently available. To meet these important scientific needs, a prototype of a novel ultrahigh-resolution inelastic x-ray scattering spectrometer system has been designed and constructed at undulator-based beamline 30-ID at the Advanced Photon Source, Argonne National Laboratory. This prototype is designed to meet challenging mechanical and optical specifications for performing so-called CDFDW angular-dispersive x-ray crystal optics, which include a central ultra-thin CFW crystal and a pair of dispersing elements. The abbreviation CDFDW stands for: C – collimating crystal, D – dispersing-element crystal (two D-crystals are used in each CDFDW), F – anomalous transmission filter, and W – wavelength-selector crystal [1]. The mechanical design of the ultrahigh-resolution inelastic x-ray scattering spectrometer, as well as the preliminary test results of its precision positioning performance are presented in this paper.

A Cross-Layer Biometric Recognition System for Mobile IoT Devices

Directory of Open Access Journals (Sweden)

Shayan Taheri

2018-02-01

Full Text Available A biometric recognition system is one of the leading candidates for the current and the next generation of smart visual systems. The visual system is the engine of the surveillance cameras that have great importance for intelligence and security purposes. These surveillance devices can be a target of adversaries for accomplishing various malicious scenarios such as disabling the camera in critical times or the lack of recognition of a criminal. In this work, we propose a cross-layer biometric recognition system that has small computational complexity and is suitable for mobile Internet of Things (IoT devices. Furthermore, due to the involvement of both hardware and software in realizing this system in a decussate and chaining structure, it is easier to locate and provide alternative paths for the system flow in the case of an attack. For security analysis of this system, one of the elements of this system named the advanced encryption standard (AES is infected by four different Hardware Trojansthat target different parts of this module. The purpose of these Trojans is to sabotage the biometric data that are under process by the biometric recognition system. All of the software and the hardware modules of this system are implemented using MATLAB and Verilog HDL, respectively. According to the performance evaluation results, the system shows an acceptable performance in recognizing healthy biometric data. It is able to detect the infected data, as well. With respect to its hardware results, the system may not contribute significantly to the hardware design parameters of a surveillance camera considering all the hardware elements within the device.

Designing a Low-Resolution Face Recognition System for Long-Range Surveillance

NARCIS (Netherlands)

Peng, Y.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2016-01-01

Most face recognition systems deal well with high-resolution facial images, but perform much worse on low-resolution facial images. In low-resolution face recognition, there is a specific but realistic surveillance scenario: a surveillance camera monitoring a large area. In this scenario, usually

Adaptive sensor-based ultra-high accuracy solar concentrator tracker

Science.gov (United States)

Brinkley, Jordyn; Hassanzadeh, Ali

2017-09-01

Conventional solar trackers use information of the sun's position, either by direct sensing or by GPS. Our method uses the shading of the receiver. This, coupled with nonimaging optics design allows us to achieve ultra-high concentration. Incorporating a sensor based shadow tracking method with a two stage concentration solar hybrid parabolic trough allows the system to maintain high concentration with acute accuracy.

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.

DEVELOPMENT OF AUTOMATED SPEECH RECOGNITION SYSTEM FOR EGYPTIAN ARABIC PHONE CONVERSATIONS

Directory of Open Access Journals (Sweden)

A. N. Romanenko

2016-07-01

Full Text Available The paper deals with description of several speech recognition systems for the Egyptian Colloquial Arabic. The research is based on the CALLHOME Egyptian corpus. The description of both systems, classic: based on Hidden Markov and Gaussian Mixture Models, and state-of-the-art: deep neural network acoustic models is given. We have demonstrated the contribution from the usage of speaker-dependent bottleneck features; for their extraction three extractors based on neural networks were trained. For their training three datasets in several languageswere used:Russian, English and differentArabic dialects.We have studied the possibility of application of a small Modern Standard Arabic (MSA corpus to derive phonetic transcriptions. The experiments have shown that application of the extractor obtained on the basis of the Russian dataset enables to increase significantly the quality of the Arabic speech recognition. We have also stated that the usage of phonetic transcriptions based on modern standard Arabic decreases recognition quality. Nevertheless, system operation results remain applicable in practice. In addition, we have carried out the study of obtained models application for the keywords searching problem solution. The systems obtained demonstrate good results as compared to those published before. Some ways to improve speech recognition are offered.

Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution.

Science.gov (United States)

Hsieh, Sheng-Hsun; Li, Yung-Hui; Tien, Chung-Hao; Chang, Chin-Chen

2016-12-01

Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

Human-inspired sound environment recognition system for assistive vehicles

Science.gov (United States)

González Vidal, Eduardo; Fredes Zarricueta, Ernesto; Auat Cheein, Fernando

2015-02-01

Objective. The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars. These vehicles need environment information to ensure safe navigation. Approach. In the field of environment recognition, range sensors (such as LiDAR and ultrasonic systems) and artificial vision devices are widely used; however, these sensors depend on environment constraints (such as lighting variability or color of objects), and sound can provide important information for the characterization of an environment. In this work, we propose a sound-based approach to enhance the environment recognition process, mainly for cases that compromise human integrity, according to the International Classification of Functioning (ICF). Our proposal is based on a neural network implementation that is able to classify up to 15 different environments, each selected according to the ICF considerations on environment factors in the community-based physical activities of people with disabilities. Main results. The accuracy rates in environment classification ranges from 84% to 93%. This classification is later used to constrain assistive vehicle navigation in order to protect the user during daily activities. This work also includes real-time outdoor experimentation (performed on an assistive vehicle) by seven volunteers with different disabilities (but without cognitive impairment and experienced in the use of wheelchairs), statistical validation, comparison with previously published work, and a discussion section where the pros and cons of our system are evaluated. Significance

Improving emotion recognition systems by embedding cardiorespiratory coupling

International Nuclear Information System (INIS)

Valenza, Gaetano; Lanatá, Antonio; Scilingo, Enzo Pasquale

2013-01-01

This work aims at showing improved performances of an emotion recognition system embedding information gathered from cardiorespiratory (CR) coupling. Here, we propose a novel methodology able to robustly identify up to 25 regions of a two-dimensional space model, namely the well-known circumplex model of affect (CMA). The novelty of embedding CR coupling information in an autonomic nervous system-based feature space better reveals the sympathetic activations upon emotional stimuli. A CR synchrogram analysis was used to quantify such a coupling in terms of number of heartbeats per respiratory period. Physiological data were gathered from 35 healthy subjects emotionally elicited by means of affective pictures of the international affective picture system database. In this study, we finely detected five levels of arousal and five levels of valence as well as the neutral state, whose combinations were used for identifying 25 different affective states in the CMA plane. We show that the inclusion of the bivariate CR measures in a previously developed system based only on monovariate measures of heart rate variability, respiration dynamics and electrodermal response dramatically increases the recognition accuracy of a quadratic discriminant classifier, obtaining more than 90% of correct classification per class. Finally, we propose a comprehensive description of the CR coupling during sympathetic elicitation adapting an existing theoretical nonlinear model with external driving. The theoretical idea behind this model is that the CR system is comprised of weakly coupled self-sustained oscillators that, when exposed to an external perturbation (i.e. sympathetic activity), becomes synchronized and less sensible to input variations. Given the demonstrated role of the CR coupling, this model can constitute a general tool which is easily embedded in other model-based emotion recognition systems. (paper)

Vision-based obstacle recognition system for automated lawn mower robot development

Science.gov (United States)

Mohd Zin, Zalhan; Ibrahim, Ratnawati

2011-06-01

Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

Device-Free Indoor Activity Recognition System

Directory of Open Access Journals (Sweden)

Mohammed Abdulaziz Aide Al-qaness

2016-11-01

Full Text Available In this paper, we explore the properties of the Channel State Information (CSI of WiFi signals and present a device-free indoor activity recognition system. Our proposed system uses only one ubiquitous router access point and a laptop as a detection point, while the user is free and neither needs to wear sensors nor carry devices. The proposed system recognizes six daily activities, such as walk, crawl, fall, stand, sit, and lie. We have built the prototype with an effective feature extraction method and a fast classification algorithm. The proposed system has been evaluated in a real and complex environment in both line-of-sight (LOS and none-line-of-sight (NLOS scenarios, and the results validate the performance of the proposed system.

Privacy protection schemes for fingerprint recognition systems

Science.gov (United States)

Marasco, Emanuela; Cukic, Bojan

2015-05-01

The deployment of fingerprint recognition systems has always raised concerns related to personal privacy. A fingerprint is permanently associated with an individual and, generally, it cannot be reset if compromised in one application. Given that fingerprints are not a secret, potential misuses besides personal recognition represent privacy threats and may lead to public distrust. Privacy mechanisms control access to personal information and limit the likelihood of intrusions. In this paper, image- and feature-level schemes for privacy protection in fingerprint recognition systems are reviewed. Storing only key features of a biometric signature can reduce the likelihood of biometric data being used for unintended purposes. In biometric cryptosystems and biometric-based key release, the biometric component verifies the identity of the user, while the cryptographic key protects the communication channel. Transformation-based approaches only a transformed version of the original biometric signature is stored. Different applications can use different transforms. Matching is performed in the transformed domain which enable the preservation of low error rates. Since such templates do not reveal information about individuals, they are referred to as cancelable templates. A compromised template can be re-issued using a different transform. At image-level, de-identification schemes can remove identifiers disclosed for objectives unrelated to the original purpose, while permitting other authorized uses of personal information. Fingerprint images can be de-identified by, for example, mixing fingerprints or removing gender signature. In both cases, degradation of matching performance is minimized.

Study of application technology of ultra-high speed computer to the elucidation of complex phenomena

International Nuclear Information System (INIS)

Sekiguchi, Tomotsugu

1996-01-01

The basic design of numerical information library in the decentralized computer network was explained at the first step of constructing the application technology of ultra-high speed computer to the elucidation of complex phenomena. Establishment of the system makes possible to construct the efficient application environment of ultra-high speed computer system to be scalable with the different computing systems. We named the system Ninf (Network Information Library for High Performance Computing). The summary of application technology of library was described as follows: the application technology of library under the distributed environment, numeric constants, retrieval of value, library of special functions, computing library, Ninf library interface, Ninf remote library and registration. By the system, user is able to use the program concentrating the analyzing technology of numerical value with high precision, reliability and speed. (S.Y.)

A novel handwritten character recognition system using gradient ...

Indian Academy of Sciences (India)

The issues faced by the handwritten character recognition systems are the similarity. ∗ ... tical/structural features have also been successfully used in character ..... The coordinates (xc, yc) of centroid are calculated by equations (4) and (5). xc =.

Euro Banknote Recognition System for Blind People

Directory of Open Access Journals (Sweden)

Larisa Dunai Dunai

2017-01-01

Full Text Available This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

Implementing an excellence in teaching recognition system: needs analysis and recommendations.

Science.gov (United States)

Schindler, Nancy; Corcoran, Julia C; Miller, Megan; Wang, Chih-Hsiung; Roggin, Kevin; Posner, Mitchell; Fryer, Jonathan; DaRosa, Debra A

2013-01-01

Teaching awards have been suggested to serve a variety of purposes. The specific characteristics of teaching awards and the associated effectiveness at achieving planned purposes are poorly understood. A needs analysis was performed to inform recommendations for an Excellence in Teaching Recognition System to meet the needs of surgical education leadership. We performed a 2-part needs analysis beginning with a review of the literature. We then, developed, piloted, and administered a survey instrument to General Surgery program leaders. The survey examined the features and perceived effectiveness of existing teaching awards systems. A multi-institution committee of program directors, clerkship directors, and Vice-Chairs of education then met to identify goals and develop recommendations for implementation of an "Excellence in Teaching Recognition System." There is limited evidence demonstrating effectiveness of existing teaching awards in medical education. Evidence supports the ability of such awards to demonstrate value placed on teaching, to inspire faculty to teach, and to contribute to promotion. Survey findings indicate that existing awards strive to achieve these purposes and that educational leaders believe awards have the potential to do this and more. Leaders are moderately satisfied with existing awards for providing recognition and demonstrating value placed on teaching, but they are less satisfied with awards for motivating faculty to participate in teaching or for contributing to promotion. Most departments and institutions honor only a few recipients annually. There is a paucity of literature addressing teaching recognition systems in medical education and little evidence to support the success of such systems in achieving their intended purposes. The ability of awards to affect outcomes such as participation in teaching and promotion may be limited by the small number of recipients for most existing awards. We propose goals for a Teaching Recognition

Ultra-high pressure water jet: Baseline report

International Nuclear Information System (INIS)

1997-01-01

The ultra-high pressure waterjet technology was being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with FIU's evaluation of efficiency and cost, this report covers the evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The ultra-high pressure waterjet technology acts as a cutting tool for the removal of surface substrates. The Husky trademark pump feeds water to a lance that directs the high pressure water at the surface to be removed. The safety and health evaluation during the testing demonstration focused on two main areas of exposure. These were dust and noise. The dust exposure was found to be minimal, which would be expected due to the wet environment inherent in the technology, but noise exposure was at a significant level. Further testing for noise is recommended because of the outdoor environment where the testing demonstration took place. In addition, other areas of concern found were arm-hand vibration, ergonomics, heat stress, tripping hazards, electrical hazards, lockout/tagout, fall hazards, slipping hazards, hazards associated with the high pressure water, and hazards associated with air pressure systems

Research on gesture recognition of augmented reality maintenance guiding system based on improved SVM

Science.gov (United States)

Zhao, Shouwei; Zhang, Yong; Zhou, Bin; Ma, Dongxi

2014-09-01

Interaction is one of the key techniques of augmented reality (AR) maintenance guiding system. Because of the complexity of the maintenance guiding system's image background and the high dimensionality of gesture characteristics, the whole process of gesture recognition can be divided into three stages which are gesture segmentation, gesture characteristic feature modeling and trick recognition. In segmentation stage, for solving the misrecognition of skin-like region, a segmentation algorithm combing background mode and skin color to preclude some skin-like regions is adopted. In gesture characteristic feature modeling of image attributes stage, plenty of characteristic features are analyzed and acquired, such as structure characteristics, Hu invariant moments features and Fourier descriptor. In trick recognition stage, a classifier based on Support Vector Machine (SVM) is introduced into the augmented reality maintenance guiding process. SVM is a novel learning method based on statistical learning theory, processing academic foundation and excellent learning ability, having a lot of issues in machine learning area and special advantages in dealing with small samples, non-linear pattern recognition at high dimension. The gesture recognition of augmented reality maintenance guiding system is realized by SVM after the granulation of all the characteristic features. The experimental results of the simulation of number gesture recognition and its application in augmented reality maintenance guiding system show that the real-time performance and robustness of gesture recognition of AR maintenance guiding system can be greatly enhanced by improved SVM.

Propagation of ultrahigh-energy cosmic rays

Energy Technology Data Exchange (ETDEWEB)

Stanev, Todor [Bartol Research Institute and Department of Physics and Astronomy, University of Delaware, Newark, DE 19716 (United States)], E-mail: stanev@bartol.udel.edu

2009-06-15

We briefly describe the energy loss processes of ultrahigh-energy protons, heavier nuclei and {gamma}-rays in interactions with the universal photon fields of the Universe. We then discuss the modification of the accelerated cosmic-ray energy spectrum in propagation by the energy loss processes and the charged cosmic-ray scattering in the extragalactic magnetic fields. The energy lost by the ultrahigh-energy cosmic rays goes into {gamma}-rays and neutrinos that carry additional information about the sources of highest energy particles. The new experimental results of the HiRes and the Auger collaborations are discussed in view of the predictions from propagation calculations.

Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

Science.gov (United States)

Poock, G. K.; Martin, B. J.

1984-02-01

This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

Ultrahigh-energy cosmic-ray spectrum

International Nuclear Information System (INIS)

Hill, C.T.; Schramm, D.N.

1985-01-01

We analyze the evolution of the ultrahigh-energy cosmic-ray spectrum upon traversing the 2.7 0 K microwave background with respect to pion photoproduction, pair-production reactions, and cosmological effects. Our approach employs exact transport equations which manifestly conserve nucleon number and embody the laboratory details of these reactions. A spectrum enhancement appears around 6 x 10 19 eV due to the ''pile-up'' of energy-degraded nucleons, and a ''dip'' occurs around 10 19 eV due to combined effects. Both of these features appear in the observational spectrum. We analyze the resulting neutrino spectrum and the effects of cosmological source distributions. We present a complete model of the ultrahigh-energy spectrum and anisotropy in reasonable agreement with observation and which predicts an observable electron-neutrino spectrum

Evaluating strength at ultra-high temperatures-Methods and results

International Nuclear Information System (INIS)

Voelkl, Rainer; Fischer, Bernd; Beschliesser, Manuel; Glatzel, Uwe

2008-01-01

Proprietary equipment for mechanical testing at ultra-high temperatures by ohmic heating is outlined. Strain is measured with a video extensometer with an accuracy of up to Δε-bar∼±0.00025%. Stability and accuracy of the test system are evaluated on Pt- and refractory alloys. These specially designed and built test facilities are compared to commercially available high-vacuum test chambers with tungsten heater

A single-system model predicts recognition memory and repetition priming in amnesia.

Science.gov (United States)

Berry, Christopher J; Kessels, Roy P C; Wester, Arie J; Shanks, David R

2014-08-13

We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. Copyright © 2014 the authors 0270-6474/14/3410963-12$15.00/0.

AN EFFICIENT SELF-UPDATING FACE RECOGNITION SYSTEM FOR PLASTIC SURGERY FACE

Directory of Open Access Journals (Sweden)

A. Devi

2016-08-01

Full Text Available Facial recognition system is fundamental a computer application for the automatic identification of a person through a digitized image or a video source. The major cause for the overall poor performance is related to the transformations in appearance of the user based on the aspects akin to ageing, beard growth, sun-tan etc. In order to overcome the above drawback, Self-update process has been developed in which, the system learns the biometric attributes of the user every time the user interacts with the system and the information gets updated automatically. The procedures of Plastic surgery yield a skilled and endurable means of enhancing the facial appearance by means of correcting the anomalies in the feature and then treating the facial skin with the aim of getting a youthful look. When plastic surgery is performed on an individual, the features of the face undergo reconstruction either locally or globally. But, the changes which are introduced new by plastic surgery remain hard to get modeled by the available face recognition systems and they deteriorate the performances of the face recognition algorithm. Hence the Facial plastic surgery produces changes in the facial features to larger extent and thereby creates a significant challenge to the face recognition system. This work introduces a fresh Multimodal Biometric approach making use of novel approaches to boost the rate of recognition and security. The proposed method consists of various processes like Face segmentation using Active Appearance Model (AAM, Face Normalization using Kernel Density Estimate/ Point Distribution Model (KDE-PDM, Feature extraction using Local Gabor XOR Patterns (LGXP and Classification using Independent Component Analysis (ICA. Efficient techniques have been used in each phase of the FRAS in order to obtain improved results.

Cross domains Arabic named entity recognition system

Science.gov (United States)

Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

2016-07-01

Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora.

The effect of image resolution on the performance of a face recognition system

NARCIS (Netherlands)

Boom, B.J.; Beumer, G.M.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

2006-01-01

In this paper we investigate the effect of image resolution on the error rates of a face verification system. We do not restrict ourselves to the face recognition algorithm only, but we also consider the face registration. In our face recognition system, the face registration is done by finding

High resolution, high speed ultrahigh vacuum microscopy

International Nuclear Information System (INIS)

Poppa, Helmut

2004-01-01

The history and future of transmission electron microscopy (TEM) is discussed as it refers to the eventual development of instruments and techniques applicable to the real time in situ investigation of surface processes with high resolution. To reach this objective, it was necessary to transform conventional high resolution instruments so that an ultrahigh vacuum (UHV) environment at the sample site was created, that access to the sample by various in situ sample modification procedures was provided, and that in situ sample exchanges with other integrated surface analytical systems became possible. Furthermore, high resolution image acquisition systems had to be developed to take advantage of the high speed imaging capabilities of projection imaging microscopes. These changes to conventional electron microscopy and its uses were slowly realized in a few international laboratories over a period of almost 40 years by a relatively small number of researchers crucially interested in advancing the state of the art of electron microscopy and its applications to diverse areas of interest; often concentrating on the nucleation, growth, and properties of thin films on well defined material surfaces. A part of this review is dedicated to the recognition of the major contributions to surface and thin film science by these pioneers. Finally, some of the important current developments in aberration corrected electron optics and eventual adaptations to in situ UHV microscopy are discussed. As a result of all the path breaking developments that have led to today's highly sophisticated UHV-TEM systems, integrated fundamental studies are now possible that combine many traditional surface science approaches. Combined investigations to date have involved in situ and ex situ surface microscopies such as scanning tunneling microscopy/atomic force microscopy, scanning Auger microscopy, and photoemission electron microscopy, and area-integrating techniques such as x-ray photoelectron

Container code recognition in information auto collection system of container inspection

International Nuclear Information System (INIS)

Su Jianping; Chen Zhiqiang; Zhang Li; Gao Wenhuan; Kang Kejun

2003-01-01

Now custom needs electrical application and automatic detection. Container inspection should not only give the image of the goods, but also auto-attain container's code and weight. Its function and track control, information transfer make up the Information Auto Collection system of Container Inspection. Code Recognition is the point. The article is based on model match, the close property of character, and uses it to recognize. Base on checkout rule, design the adjustment arithmetic, form the whole recognition strategy. This strategy can achieve high recognition ratio and robust property

A Kinect based sign language recognition system using spatio-temporal features

Science.gov (United States)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Some problems of physics of ultrahigh energy cosmic rays

International Nuclear Information System (INIS)

Isaev, P.S.

1999-01-01

Nearest 15-20 years will be years of flourishing of experimental researches into the energy of cosmic rays at > or ∼ 10 15 eV and of new discoveries in the physics of elementary particles of ultrahigh energies. Unsolved problems of modern physics of ultrahigh energy cosmic rays, which are relevant to the problems of elementary particles physics, are reviewed

Application of the new pattern recognition system in the new e-nose to detecting Chinese spirits

International Nuclear Information System (INIS)

Gu Yu; Li Qiang

2014-01-01

We present a new pattern recognition system based on moving average and linear discriminant analysis (LDA), which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

Impact of a voice recognition system on report cycle time and radiologist reading time

Science.gov (United States)

Melson, David L.; Brophy, Robert; Blaine, G. James; Jost, R. Gilbert; Brink, Gary S.

1998-07-01

Because of its exciting potential to improve clinical service, as well as reduce costs, a voice recognition system for radiological dictation was recently installed at our institution. This system will be clinically successful if it dramatically reduces radiology report turnaround time without substantially affecting radiologist dictation and editing time. This report summarizes an observer study currently under way in which radiologist reporting times using the traditional transcription system and the voice recognition system are compared. Four radiologists are observed interpreting portable intensive care unit (ICU) chest examinations at a workstation in the chest reading area. Data are recorded with the radiologists using the transcription system and using the voice recognition system. The measurements distinguish between time spent performing clerical tasks and time spent actually dictating the report. Editing time and the number of corrections made are recorded. Additionally, statistics are gathered to assess the voice recognition system's impact on the report cycle time -- the time from report dictation to availability of an edited and finalized report -- and the length of reports.

AUTOMATIC SPEECH RECOGNITION SYSTEM CONCERNING THE MOROCCAN DIALECTE (Darija and Tamazight)

OpenAIRE

A. EL GHAZI; C. DAOUI; N. IDRISSI

2012-01-01

In this work we present an automatic speech recognition system for Moroccan dialect mainly: Darija (Arab dialect) and Tamazight. Many approaches have been used to model the Arabic and Tamazightphonetic units. In this paper, we propose to use the hidden Markov model (HMM) for modeling these phoneticunits. Experimental results show that the proposed approach further improves the recognition.

Baking enables McLeod gauge to measure in ultrahigh vacuum range

Science.gov (United States)

Kreisman, W. S.

1965-01-01

Accurate measurements in the ultrahigh vacuum range by a conventional McLeod gage requires degassing of the gage's glass walls. A closed system, in which mercury is forced into the gage by gravity alone, and in which the gage components are baked out for long periods, is used to achieve this degassing.

Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

Directory of Open Access Journals (Sweden)

Hong Zhang

2013-01-01

Full Text Available With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activity, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation towards the performance of human activity recognition.

Ultra-high resolution flat-panel volume CT: fundamental principles, design architecture, and system characterization

International Nuclear Information System (INIS)

Gupta, Rajiv; Brady, Tom; Grasruck, Michael; Suess, Christoph; Schmidt, Bernhard; Stierstorfer, Karl; Popescu, Stefan; Flohr, Thomas; Bartling, Soenke H.

2006-01-01

Digital flat-panel-based volume CT (VCT) represents a unique design capable of ultra-high spatial resolution, direct volumetric imaging, and dynamic CT scanning. This innovation, when fully developed, has the promise of opening a unique window on human anatomy and physiology. For example, the volumetric coverage offered by this technology enables us to observe the perfusion of an entire organ, such as the brain, liver, or kidney, tomographically (e.g., after a transplant or ischemic event). By virtue of its higher resolution, one can directly visualize the trabecular structure of bone. This paper describes the basic design architecture of VCT. Three key technical challenges, viz., scatter correction, dynamic range extension, and temporal resolution improvement, must be addressed for successful implementation of a VCT scanner. How these issues are solved in a VCT prototype and the modifications necessary to enable ultra-high resolution volumetric scanning are described. The fundamental principles of scatter correction and dose reduction are illustrated with the help of an actual prototype. The image quality metrics of this prototype are characterized and compared with a multi-detector CT (MDCT). (orig.)

Ultra-high resolution flat-panel volume CT: fundamental principles, design architecture, and system characterization

Energy Technology Data Exchange (ETDEWEB)

Gupta, Rajiv; Brady, Tom [Massachusetts General Hospital, Department of Radiology, Founders House, FND-2-216, Boston, MA (United States); Grasruck, Michael; Suess, Christoph; Schmidt, Bernhard; Stierstorfer, Karl; Popescu, Stefan; Flohr, Thomas [Siemens Medical Solutions, Forchheim (Germany); Bartling, Soenke H. [Hannover Medical School, Department of Neuroradiology, Hannover (Germany)

2006-06-15

Digital flat-panel-based volume CT (VCT) represents a unique design capable of ultra-high spatial resolution, direct volumetric imaging, and dynamic CT scanning. This innovation, when fully developed, has the promise of opening a unique window on human anatomy and physiology. For example, the volumetric coverage offered by this technology enables us to observe the perfusion of an entire organ, such as the brain, liver, or kidney, tomographically (e.g., after a transplant or ischemic event). By virtue of its higher resolution, one can directly visualize the trabecular structure of bone. This paper describes the basic design architecture of VCT. Three key technical challenges, viz., scatter correction, dynamic range extension, and temporal resolution improvement, must be addressed for successful implementation of a VCT scanner. How these issues are solved in a VCT prototype and the modifications necessary to enable ultra-high resolution volumetric scanning are described. The fundamental principles of scatter correction and dose reduction are illustrated with the help of an actual prototype. The image quality metrics of this prototype are characterized and compared with a multi-detector CT (MDCT). (orig.)

An Edge-Based Macao License Plate Recognition System

Directory of Open Access Journals (Sweden)

Chi-Man Pun

2011-04-01

Full Text Available This paper presents a system to recognize Macao license plates. Sobel edge detector is employed to extract the vertical edges, and an edge composition algorithm is proposed to combine the edges into candidate plate regions. They are further examined on the existence of the character qMq by a verification algorithm. A row separation algorithm is also proposed to cater both one-row and two-row types of plates. Projection analysis and template matching methods are exploited to segment and recognize the characters. Various pre and post processing steps are proposed other than traditional implementation so as to improve the recognition accuracy. This work achieves a high recognition rate of 95%.

A multi-view face recognition system based on cascade face detector and improved Dlib

Science.gov (United States)

Zhou, Hongjun; Chen, Pei; Shen, Wei

2018-03-01

In this research, we present a framework for multi-view face detect and recognition system based on cascade face detector and improved Dlib. This method is aimed to solve the problems of low efficiency and low accuracy in multi-view face recognition, to build a multi-view face recognition system, and to discover a suitable monitoring scheme. For face detection, the cascade face detector is used to extracted the Haar-like feature from the training samples, and Haar-like feature is used to train a cascade classifier by combining Adaboost algorithm. Next, for face recognition, we proposed an improved distance model based on Dlib to improve the accuracy of multiview face recognition. Furthermore, we applied this proposed method into recognizing face images taken from different viewing directions, including horizontal view, overlooks view, and looking-up view, and researched a suitable monitoring scheme. This method works well for multi-view face recognition, and it is also simulated and tested, showing satisfactory experimental results.

Applications of PCA and SVM-PSO Based Real-Time Face Recognition System

Directory of Open Access Journals (Sweden)

Ming-Yuan Shieh

2014-01-01

Full Text Available This paper incorporates principal component analysis (PCA with support vector machine-particle swarm optimization (SVM-PSO for developing real-time face recognition systems. The integrated scheme aims to adopt the SVM-PSO method to improve the validity of PCA based image recognition systems on dynamically visual perception. The face recognition for most human-robot interaction applications is accomplished by PCA based method because of its dimensionality reduction. However, PCA based systems are only suitable for processing the faces with the same face expressions and/or under the same view directions. Since the facial feature selection process can be considered as a problem of global combinatorial optimization in machine learning, the SVM-PSO is usually used as an optimal classifier of the system. In this paper, the PSO is used to implement a feature selection, and the SVMs serve as fitness functions of the PSO for classification problems. Experimental results demonstrate that the proposed method simplifies features effectively and obtains higher classification accuracy.

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.

A system of automatic speaker recognition on a minicomputer

International Nuclear Information System (INIS)

El Chafei, Cherif

1978-01-01

This study describes a system of automatic speaker recognition using the pitch of the voice. The pre-treatment consists in the extraction of the speakers' discriminating characteristics taken from the pitch. The programme of recognition gives, firstly, a preselection and then calculates the distance between the speaker's characteristics to be recognized and those of the speakers already recorded. An experience of recognition has been realized. It has been undertaken with 15 speakers and included 566 tests spread over an intermittent period of four months. The discriminating characteristics used offer several interesting qualities. The algorithms concerning the measure of the characteristics on one hand, the speakers' classification on the other hand, are simple. The results obtained in real time with a minicomputer are satisfactory. Furthermore they probably could be improved if we considered other speaker's discriminating characteristics but this was unfortunately not in our possibilities. (author) [fr

Application of robust face recognition in video surveillance systems

Science.gov (United States)

Zhang, De-xin; An, Peng; Zhang, Hao-xiang

2018-03-01

In this paper, we propose a video searching system that utilizes face recognition as searching indexing feature. As the applications of video cameras have great increase in recent years, face recognition makes a perfect fit for searching targeted individuals within the vast amount of video data. However, the performance of such searching depends on the quality of face images recorded in the video signals. Since the surveillance video cameras record videos without fixed postures for the object, face occlusion is very common in everyday video. The proposed system builds a model for occluded faces using fuzzy principal component analysis (FPCA), and reconstructs the human faces with the available information. Experimental results show that the system has very high efficiency in processing the real life videos, and it is very robust to various kinds of face occlusions. Hence it can relieve people reviewers from the front of the monitors and greatly enhances the efficiency as well. The proposed system has been installed and applied in various environments and has already demonstrated its power by helping solving real cases.

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)

A Malaysian Vehicle License Plate Localization and Recognition System

OpenAIRE

Ganapathy Velappa; Dennis LUI Wen Lik

2008-01-01

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,...

A Massively Parallel Face Recognition System

Directory of Open Access Journals (Sweden)

Lahdenoja Olli

2007-01-01

Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

A Massively Parallel Face Recognition System

Directory of Open Access Journals (Sweden)

Ari Paasio

2006-12-01

Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

A novel hybrid biometric electronic voting system: integrating finger print face recognition

International Nuclear Information System (INIS)

Najam, S.S.; Shaikh, A.Z.; Naqvi, S.

2018-01-01

A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition. (author)

Performance Assessment of Dynaspeak Speech Recognition System on Inflight Databases

National Research Council Canada - National Science Library

Barry, Timothy

2004-01-01

.... To aid in the assessment of various commercially available speech recognition systems, several aircraft speech databases have been developed at the Air Force Research Laboratory's Human Effectiveness Directorate...

A Robust and Device-Free System for the Recognition and Classification of Elderly Activities.

Science.gov (United States)

Li, Fangmin; Al-Qaness, Mohammed Abdulaziz Aide; Zhang, Yong; Zhao, Bihai; Luan, Xidao

2016-12-01

Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise.

Body posture recognition and turning recording system for the care of bed bound patients.

Science.gov (United States)

Hsiao, Rong-Shue; Mi, Zhenqiang; Yang, Bo-Ru; Kau, Lih-Jen; Bitew, Mekuanint Agegnehu; Li, Tzu-Yu

2015-01-01

This paper proposes body posture recognition and turning recording system for assisting the care of bed bound patients in nursing homes. The system continuously detects the patient's body posture and records the length of time for each body posture. If the patient remains in the same body posture long enough to develop pressure ulcers, the system notifies caregivers to change the patient's body posture. The objective of recording is to provide the log of body turning for querying of patients' family members. In order to accurately detect patient's body posture, we developed a novel pressure sensing pad which contains force sensing resistor sensors. Based on the proposed pressure sensing pad, we developed a bed posture recognition module which includes a bed posture recognition algorithm. The algorithm is based on fuzzy theory. The body posture recognition algorithm can detect the patient's bed posture whether it is right lateral decubitus, left lateral decubitus, or supine. The detected information of patient's body posture can be then transmitted to the server of healthcare center by the communication module to perform the functions of recording and notification. Experimental results showed that the average posture recognition accuracy for our proposed module is 92%.

Cross domains Arabic named entity recognition system

KAUST Repository

Al-Ahmari, S. Saad

2016-07-11

Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Cross domains Arabic named entity recognition system

KAUST Repository

Al-Ahmari, S. Saad; Abdullatif Al-Johar, B.

2016-01-01

Named Entity Recognition (NER) plays an important role in many Natural Language Processing (NLP) applications such as; Information Extraction (IE), Question Answering (QA), Text Clustering, Text Summarization and Word Sense Disambiguation. This paper presents the development and implementation of domain independent system to recognize three types of Arabic named entities. The system works based on a set of domain independent grammar-rules along with Arabic part of speech tagger in addition to gazetteers and lists of trigger words. The experimental results shown, that the system performed as good as other systems with better results in some cases of cross-domains corpora. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Functional magnetic resonance imaging with ultra-high fields

International Nuclear Information System (INIS)

Windischberger, C.; Schoepf, V.; Sladky, R.; Moser, E.; Fischmeister, F.P.S.

2010-01-01

Functional magnetic resonance imaging (fMRI) is currently the primary method for non-invasive functional localization in the brain. With the emergence of MR systems with field strengths of 4 Tesla and above, neuronal activation may be studied with unprecedented accuracy. In this article we present different approaches to use the improved sensitivity and specificity for expanding current fMRT resolution limits in space and time based on several 7 Tesla studies. In addition to the challenges that arise with ultra-high magnetic fields possible solutions will be discussed. (orig.) [de

Ultra-high energy cosmic rays and prompt TeV gamma rays from ...

Indian Academy of Sciences (India)

physics pp. 789-792. Ultra-high energy cosmic rays and prompt. TeV gamma rays from gamma ray bursts ... The origin of the observed ultra-high energy cosmic ray (UHECR) events with ... are proton and electron rest mass, respectively.

Structural insight into RNA recognition motifs: versatile molecular Lego building blocks for biological systems.

Science.gov (United States)

Muto, Yutaka; Yokoyama, Shigeyuki

2012-01-01

'RNA recognition motifs (RRMs)' are common domain-folds composed of 80-90 amino-acid residues in eukaryotes, and have been identified in many cellular proteins. At first they were known as RNA binding domains. Through discoveries over the past 20 years, however, the RRMs have been shown to exhibit versatile molecular recognition activities and to behave as molecular Lego building blocks to construct biological systems. Novel RNA/protein recognition modes by RRMs are being identified, and more information about the molecular recognition by RRMs is becoming available. These RNA/protein recognition modes are strongly correlated with their biological significance. In this review, we would like to survey the recent progress on these versatile molecular recognition modules. Copyright © 2012 John Wiley & Sons, Ltd.

A Presence-Based Context-Aware Chronic Stress Recognition System

Directory of Open Access Journals (Sweden)

Andrej Kos

2012-11-01

Full Text Available Stressors encountered in daily life may play an important role in personal well-being. Chronic stress can have a serious long-term impact on our physical as well as our psychological health, due to ongoing increased levels of the chemicals released in the ‘fight or flight’ response. The currently available stress assessment methods are usually not suitable for daily chronic stress measurement. The paper presents a context-aware chronic stress recognition system that addresses this problem. The proposed system obtains contextual data from various mobile sensors and other external sources in order to calculate the impact of ongoing stress. By identifying and visualizing ongoing stress situations of an individual user, he/she is able to modify his/her behavior in order to successfully avoid them. Clinical evaluation of the proposed methodology has been made in parallel by using electrodermal activity sensor. To the best of our knowledge, the system presented herein is the first one that enables recognition of chronic stress situations on the basis of user context.

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)

Research and Application of WCF Technology in Data Acquisition of Ultra-high Speed Packaging Machine

Directory of Open Access Journals (Sweden)

Qian Jie

2016-01-01

Full Text Available By introducing WCF technology on data acquisition of ultra-high speed packaging machine, data acquisition system reads dates of machine in polling mode through the WCF client, which can achieve accurate data collection, and effectively isolate the data acquisition system and the machine control system. It enhances the security of data interaction between systems, but also reduces the coupling degree between systems.

Fast and Low-Cost Mechatronic Recognition System for Persian Banknotes

Directory of Open Access Journals (Sweden)

Majid Behjat

2014-03-01

Full Text Available In this paper, we designed a fast and low-cost mechatronic system for recognition of eight current Persian banknotes in circulation. Firstly, we proposed a mechanical solution for avoiding extra processing time caused by detecting the place of banknote and paper angle correction in an input image. We also defined new parameters for feature extraction, including colour features (RGBR values, size features (LWR and texture features (CRLVR value. Then, we used a Multi-Layer Perceptron (MLP neural network in the recognition phase to reduce the necessary processing time. In this research, we collected a perfect database of Persian banknote images (about 4000 double-sided prevalent images. We reached about 99.06% accuracy (average for each side in final banknote recognition by testing 800 different worn, torn and new banknotes which were not part of the initial learning phase. This accuracy could increase to 99.62% in double-sided decision mode. Finally, we designed an ATmega32 microcontroller-based hardware with 16MHz clock frequency for implementation of our proposed system which can recognize sample banknotes at about 480ms and 560ms for single-sided detection and double-sided detection respectively, after image scanning.

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

Sudden Event Recognition: A Survey

Directory of Open Access Journals (Sweden)

Mohd Asyraf Zulkifley

2013-08-01

Full Text Available Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1 the importance of a sudden event over a general anomalous event; (2 frameworks used in sudden event recognition; (3 the requirements and comparative studies of a sudden event recognition system and (4 various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition.

42 CFR 403.322 - Termination of agreements for Medicare recognition of State systems.

Science.gov (United States)

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Termination of agreements for Medicare recognition of State systems. 403.322 Section 403.322 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS SPECIAL PROGRAMS AND PROJECTS Recognition of State...

Source Separation via Spectral Masking for Speech Recognition Systems

Directory of Open Access Journals (Sweden)

Gustavo Fernandes Rodrigues

2012-12-01

Full Text Available In this paper we present an insight into the use of spectral masking techniques in time-frequency domain, as a preprocessing step for the speech signal recognition. Speech recognition systems have their performance negatively affected in noisy environments or in the presence of other speech signals. The limits of these masking techniques for different levels of the signal-to-noise ratio are discussed. We show the robustness of the spectral masking techniques against four types of noise: white, pink, brown and human speech noise (bubble noise. The main contribution of this work is to analyze the performance limits of recognition systems  using spectral masking. We obtain an increase of 18% on the speech hit rate, when the speech signals were corrupted by other speech signals or bubble noise, with different signal-to-noise ratio of approximately 1, 10 and 20 dB. On the other hand, applying the ideal binary masks to mixtures corrupted by white, pink and brown noise, results an average growth of 9% on the speech hit rate, with the same different signal-to-noise ratio. The experimental results suggest that the masking spectral techniques are more suitable for the case when it is applied a bubble noise, which is produced by human speech, than for the case of applying white, pink and brown noise.

Production of ultrahigh magnetic fields. Technical progress report

International Nuclear Information System (INIS)

1985-01-01

The objective was to produce and measure controlled ultrahigh magnetic fields by imploding a plasma in which a magnetic field has been entrained. The novel method for producing the ultrahigh fields using a gas-puff Z pinch was tested successfully and found to work as well as predicted in some respects and better in others, such as field amplification. Moreover, in testing this concept, we may have created the only megagauss facility in the world with a 3-minute repetition rate and long lifetime. Most megagauss facilities are single-shot, owing to material deformations or the use of explosives

Shock characterization of an ultra-high strength concrete

International Nuclear Information System (INIS)

Erzar, B.; Pontiroli, C.; Buzaud, E.

2016-01-01

Nowadays, the design of protective structures may imply ultra-high performance concretes. These materials present a compressive strength 5 times higher than standard concretes. However, few reliable data on the shock response of such materials are available in the literature. Thus, a characterization of an ultra-high strength concrete has been conducted by means of hydrostatic and triaxial tests in the quasi-static regime, and plate impact experiments for shock response. Data have been gathered up to 6 GPa and a simple modelling approach has been applied to get a reliable representation of the shock compression of this concrete. (authors)

An Evolutionary Approach to Driving Tendency Recognition for Advanced Driver Assistance Systems

Directory of Open Access Journals (Sweden)

Lee Jong-Hyun

2016-01-01

Full Text Available Driving tendency recognition is important for constructing Advanced Driver Assistance Systems (ADAS. However, it had not been a lot of research using vehicle sensing data, due to the high difficulty to define it. In this paper, we attempt to improve the learning capability of a machine learning method using evolutionary computation. We propose a driving tendency recognition method, with consideration of data characteristics. Comparison of our classification system with conventional methods demonstrated the effectiveness and accuracy over 92% in our system. Our proposed evolutionary approach is confirmed that improve the classification accuracy of the learning method through evolution in the experiment.

Face Detection and Recognition

National Research Council Canada - National Science Library

Jain, Anil K

2004-01-01

This report describes research efforts towards developing algorithms for a robust face recognition system to overcome many of the limitations found in existing two-dimensional facial recognition systems...

[Application study of qualitatively diagnosing prostate cancer using ultrahigh b-value DWI].

Science.gov (United States)

Ji, L B; Lu, Z H; Yao, H H; Cao, Y; Lu, W W; Qian, W X; Wang, X M; Hu, C H

2017-07-18

Objective: To explore the value of ultrahigh b-value DWI in diagnosis of prostate cancer. Methods: From October 2015 to October 2016, a total of 84 cases from Affiliated Changshu Hospital of Soochow University(39 cases of prostate cancer with a total of 57 lesions, 45 cases of benign prostate hyperplasia) were examined with T(2)WI, high b-value DWI (b=1 000 s/mm(2)) and ultrahigh b-value DWI (b=2 000 s/mm(2)) .Three image sets were rated respectively based on PI-RADS V2 by two radiologists and the scores were compared with biopsy results.The differences of the area under the ROC curve (AUC) among the three groups of each observer were compared by Z test. Results: The difference of AUC between ultrahigh b-value DWI and T(2)WI in the diagnosis of peripheral and transitional zone cancer was statistically significant between the two observers ( P =0.009 9, 0.008 2, 0.010 8 and 0.004 5 respectively), and there was no significant difference of AUC between ultrahigh b-value DWI and high b-value DWI in the diagnosis of peripheral and transitional zone cancer.The inter-reader agreement was found to be perfect for all lesions, peripheral zone lesions and transition zone lesions at ultrahigh b-value DWI ( kappa values were 0.738, 0.709 and 0.768 respectively). Conclusion: The diagnostic performance of ultrahigh b-value DWI is superior to high b-value DWI and T(2)WI in both peripheral zone and transition zone cancers.

Auditory signal design for automatic number plate recognition system

NARCIS (Netherlands)

Heydra, C.G.; Jansen, R.J.; Van Egmond, R.

2014-01-01

This paper focuses on the design of an auditory signal for the Automatic Number Plate Recognition system of Dutch national police. The auditory signal is designed to alert police officers of suspicious cars in their proximity, communicating priority level and location of the suspicious car and

Object Recognition System-on-Chip Using the Support Vector Machines

Directory of Open Access Journals (Sweden)

Houzet Dominique

2005-01-01

Full Text Available The first aim of this work is to propose the design of a system-on-chip (SoC platform dedicated to digital image and signal processing, which is tuned to implement efficiently multiply-and-accumulate (MAC vector/matrix operations. The second aim of this work is to implement a recent promising neural network method, namely, the support vector machine (SVM used for real-time object recognition, in order to build a vision machine. With such a reconfigurable and programmable SoC platform, it is possible to implement any SVM function dedicated to any object recognition problem. The final aim is to obtain an automatic reconfiguration of the SoC platform, based on the results of the learning phase on an objects' database, which makes it possible to recognize practically any object without manual programming. Recognition can be of any kind that is from image to signal data. Such a system is a general-purpose automatic classifier. Many applications can be considered as a classification problem, but are usually treated specifically in order to optimize the cost of the implemented solution. The cost of our approach is more important than a dedicated one, but in a near future, hundreds of millions of gates will be common and affordable compared to the design cost. What we are proposing here is a general-purpose classification neural network implemented on a reconfigurable SoC platform. The first version presented here is limited in size and thus in object recognition performances, but can be easily upgraded according to technology improvements.

The intergalactic propagation of ultrahigh energy cosmic ray nuclei

Energy Technology Data Exchange (ETDEWEB)

Hooper, Dan; /Fermilab; Sarkar, Subir; /Oxford U., Theor. Phys.; Taylor, Andrew M.; /Oxford U.

2006-08-01

We investigate the propagation of ultra-high energy cosmic ray nuclei (A = 1-56) from cosmologically distant sources through the cosmic radiation backgrounds. Various models for the injected composition and spectrum and of the cosmic infrared background are studied using updated photodisintegration cross-sections. The observational data on the spectrum and the composition of ultra-high energy cosmic rays are jointly consistent with a model where all of the injected primary cosmic rays are iron nuclei (or a mixture of heavy and light nuclei).

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.

Involvement of the intrinsic/default system in movement-related self recognition.

Science.gov (United States)

Salomon, Roy; Malach, Rafael; Lamy, Dominique

2009-10-21

The question of how people recognize themselves and separate themselves from the environment and others has long intrigued philosophers and scientists. Recent findings have linked regions of the 'default brain' or 'intrinsic system' to self-related processing. We used a paradigm in which subjects had to rely on subtle sensory-motor synchronization differences to determine whether a viewed movement belonged to them or to another person, while stimuli and task demands associated with the "responded self" and "responded other" conditions were precisely matched. Self recognition was associated with enhanced brain activity in several ROIs of the intrinsic system, whereas no differences emerged within the extrinsic system. This self-related effect was found even in cases where the sensory-motor aspects were precisely matched. Control conditions ruled out task difficulty as the source of the differential self-related effects. The findings shed light on the neural systems underlying bodily self recognition.

Ultrahigh-frequency ultrasound of fascicles in the median nerve at the wrist.

Science.gov (United States)

Cartwright, Michael S; Baute, Vanessa; Caress, James B; Walker, Francis O

2017-10-01

An ultrahigh-frequency (70 MHZ) ultrasound device has recently been approved for human use. This study seeks to determine whether this device facilitates counting of fascicles within the median nerve at the wrist. Twenty healthy volunteers underwent imaging of the median nerve at the wrist bilaterally. The number of fascicles in each nerve was counted by two independent raters. The mean fascicle number was 22.68. Correlation was strong between the two raters (r = 0.68, P nerve area did not predict fascicle number. Those with bifid median nerves and persistent median arteries had lower fascicle density than those without anatomic anomalies (1.79 vs. 2.29; P = 0.01). Fascicles within the median nerve at the wrist can be readily imaged. Ultrahigh-frequency ultrasound technology may be informative in a variety of disorders affecting the peripheral nervous system. Muscle Nerve 56: 819-822, 2017. © 2017 Wiley Periodicals, Inc.

Enhancing ultra-high CPV passive cooling using least-material finned heat sinks

Energy Technology Data Exchange (ETDEWEB)

Micheli, Leonardo, E-mail: lm409@exeter.ac.uk; Mallick, Tapas K., E-mail: T.K.Mallick@exeter.ac.uk [Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall TR10 9FE (United Kingdom); Fernandez, Eduardo F., E-mail: E.Fernandez-Fernandez2@exeter.ac.uk [Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall TR10 9FE (United Kingdom); Centre of Advanced Studies in Energy and Environment, University of Jaen, Jaen 23071 (Spain); Almonacid, Florencia, E-mail: facruz@ujaen.es [Centre of Advanced Studies in Energy and Environment, University of Jaen, Jaen 23071 (Spain); Reddy, K. S., E-mail: ksreddy@iitm.ac.in [Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai, 600036 (India)

2015-09-28

Ultra-high concentrating photovoltaic (CPV) systems aim to increase the cost-competiveness of CPV by increasing the concentrations over 2000 suns. In this work, the design of a heat sink for ultra-high concentrating photovoltaic (CPV) applications is presented. For the first time, the least-material approach, widely used in electronics to maximize the thermal dissipation while minimizing the weight of the heat sink, has been applied in CPV. This method has the potential to further decrease the cost of this technology and to keep the multijunction cell within the operative temperature range. The designing procedure is described in the paper and the results of a thermal simulation are shown to prove the reliability of the solution. A prediction of the costs is also reported: a cost of 0.151$/W{sub p} is expected for a passive least-material heat sink developed for 4000x applications.

A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition

Directory of Open Access Journals (Sweden)

Shahram Najam

2018-01-01

Full Text Available A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis and K-NN (K-Nearest Neighbor. It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.

Introduction and Overview of the Vicens-Reddy Speech Recognition System.

Science.gov (United States)

Kameny, Iris; Ritea, H.

The Vicens-Reddy System is unique in the sense that it approaches the problem of speech recognition as a whole, rather than treating particular aspects of the problems as in previous attempts. For example, where earlier systems treated only segmentation of speech into phoneme groups, or detected phonemes in a given context, the Vicens-Reddy System…

Interactions of the humoral pattern recognition molecule PTX3 with the complement system

DEFF Research Database (Denmark)

Doni, Andrea; Garlanda, Cecilia; Bottazzi, Barbara

2012-01-01

The innate immune system comprises a cellular and a humoral arm. The long pentraxin PTX3 is a fluid phase pattern recognition molecule, which acts as an essential component of the humoral arm of innate immunity. PTX3 has antibody-like properties including interactions with complement components....... PTX3 interacts with C1q, ficolin-1 and ficolin-2 as well as mannose-binding lectin, recognition molecules in the classical and lectin complement pathways. The formation of these heterocomplexes results in cooperative pathogen recognition and complement activation. Interactions with C4b binding protein...

ISOLATED SPEECH RECOGNITION SYSTEM FOR TAMIL LANGUAGE USING STATISTICAL PATTERN MATCHING AND MACHINE LEARNING TECHNIQUES

Directory of Open Access Journals (Sweden)

VIMALA C.

2015-05-01

Full Text Available In recent years, speech technology has become a vital part of our daily lives. Various techniques have been proposed for developing Automatic Speech Recognition (ASR system and have achieved great success in many applications. Among them, Template Matching techniques like Dynamic Time Warping (DTW, Statistical Pattern Matching techniques such as Hidden Markov Model (HMM and Gaussian Mixture Models (GMM, Machine Learning techniques such as Neural Networks (NN, Support Vector Machine (SVM, and Decision Trees (DT are most popular. The main objective of this paper is to design and develop a speaker-independent isolated speech recognition system for Tamil language using the above speech recognition techniques. The background of ASR system, the steps involved in ASR, merits and demerits of the conventional and machine learning algorithms and the observations made based on the experiments are presented in this paper. For the above developed system, highest word recognition accuracy is achieved with HMM technique. It offered 100% accuracy during training process and 97.92% for testing process.

Pattern-recognition software detecting the onset of failures in complex systems

International Nuclear Information System (INIS)

Mott, J.; King, R.

1987-01-01

A very general mathematical framework for embodying learned data from a complex system and combining it with a current observation to estimate the true current state of the system has been implemented using nearly universal pattern-recognition algorithms and applied to surveillance of the EBR-II power plant. In this application the methodology can provide signal validation and replacement of faulty signals on a near-real-time basis for hundreds of plant parameters. The mathematical framework, the pattern-recognition algorithms, examples of the learning and estimating process, and plant operating decisions made using this methodology are discussed. The entire methodology has been reduced to a set of FORTRAN subroutines which are small, fast, robust and executable on a personal computer with a serial link to the system's data acquisition computer, or on the data acquisition computer itself

Two-step calibration method for multi-algorithm score-based face recognition systems by minimizing discrimination loss

NARCIS (Netherlands)

Susyanto, N.; Veldhuis, R.N.J.; Spreeuwers, L.J.; Klaassen, C.A.J.; Fierrez, J.; Li, S.Z.; Ross, A.; Veldhuis, R.; Alonso-Fernandez, F.; Bigun, J.

2016-01-01

We propose a new method for combining multi-algorithm score-based face recognition systems, which we call the two-step calibration method. Typically, algorithms for face recognition systems produce dependent scores. The two-step method is based on parametric copulas to handle this dependence. Its

Design and implementation of face recognition system based on Windows

Science.gov (United States)

Zhang, Min; Liu, Ting; Li, Ailan

2015-07-01

In view of the basic Windows login password input way lacking of safety and convenient operation, we will introduce the biometrics technology, face recognition, into the computer to login system. Not only can it encrypt the computer system, also according to the level to identify administrators at all levels. With the enhancement of the system security, user input can neither be a cumbersome nor worry about being stolen password confidential.

Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

Science.gov (United States)

Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

New pattern recognition system in the e-nose for Chinese spirit identification

International Nuclear Information System (INIS)

Zeng Hui; Li Qiang; Gu Yu

2016-01-01

This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (S f ), crest factor value (C f ), impulse factor value (I f ), clearance factor value (CL f ), kurtosis factor value (K v ) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively. (paper)

Improving a HMM-based off-line handwriting recognition system using MME-PSO optimization

Science.gov (United States)

Hamdani, Mahdi; El Abed, Haikal; Hamdani, Tarek M.; Märgner, Volker; Alimi, Adel M.

2011-01-01

One of the trivial steps in the development of a classifier is the design of its architecture. This paper presents a new algorithm, Multi Models Evolvement (MME) using Particle Swarm Optimization (PSO). This algorithm is a modified version of the basic PSO, which is used to the unsupervised design of Hidden Markov Model (HMM) based architectures. For instance, the proposed algorithm is applied to an Arabic handwriting recognizer based on discrete probability HMMs. After the optimization of their architectures, HMMs are trained with the Baum- Welch algorithm. The validation of the system is based on the IfN/ENIT database. The performance of the developed approach is compared to the participating systems at the 2005 competition organized on Arabic handwriting recognition on the International Conference on Document Analysis and Recognition (ICDAR). The final system is a combination between an optimized HMM with 6 other HMMs obtained by a simple variation of the number of states. An absolute improvement of 6% of word recognition rate with about 81% is presented. This improvement is achieved comparing to the basic system (ARAB-IfN). The proposed recognizer outperforms also most of the known state-of-the-art systems.

A Human Activity Recognition System Using Skeleton Data from RGBD Sensors.

Science.gov (United States)

Cippitelli, Enea; Gasparrini, Samuele; Gambi, Ennio; Spinsante, Susanna

2016-01-01

The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

A Human Activity Recognition System Using Skeleton Data from RGBD Sensors

Directory of Open Access Journals (Sweden)

Enea Cippitelli

2016-01-01

Full Text Available The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

Micro-damage propagation in ultra-high vacuum seals

CERN Document Server

Lutkiewicz, P; Garion, C

2010-01-01

The paper addresses a fundamental problem of tightness of ultra-high vacuum systems (UHV) at cryogenic temperatures in the light of continuum damage mechanics (CDM). The problem of indentation of a rigid punch into an elastic-plastic half-space is investigated based on rate independent plasticity with mixed kinematic and isotropic hardening. The micro-damage fields are modeled by using an anisotropic approach with a kinetic law of damage evolution suitable for ductile materials and cryogenic temperatures. The model has been experimentally validated and the results are used to predict the onset of macro-cracking (loss of tightness) and the corresponding load (contact pressure). The algorithm is applied in the design of UHV systems for particle accelerators. (C) 2009 Published by Elsevier Ltd.

Development of Portable Automatic Number Plate Recognition System on Android Mobile Phone

Science.gov (United States)

Mutholib, Abdul; Gunawan, Teddy S.; Chebil, Jalel; Kartiwi, Mira

2013-12-01

The Automatic Number Plate Recognition (ANPR) System has performed as the main role in various access control and security, such as: tracking of stolen vehicles, traffic violations (speed trap) and parking management system. In this paper, the portable ANPR implemented on android mobile phone is presented. The main challenges in mobile application are including higher coding efficiency, reduced computational complexity, and improved flexibility. Significance efforts are being explored to find suitable and adaptive algorithm for implementation of ANPR on mobile phone. ANPR system for mobile phone need to be optimize due to its limited CPU and memory resources, its ability for geo-tagging image captured using GPS coordinates and its ability to access online database to store the vehicle's information. In this paper, the design of portable ANPR on android mobile phone will be described as follows. First, the graphical user interface (GUI) for capturing image using built-in camera was developed to acquire vehicle plate number in Malaysia. Second, the preprocessing of raw image was done using contrast enhancement. Next, character segmentation using fixed pitch and an optical character recognition (OCR) using neural network were utilized to extract texts and numbers. Both character segmentation and OCR were using Tesseract library from Google Inc. The proposed portable ANPR algorithm was implemented and simulated using Android SDK on a computer. Based on the experimental results, the proposed system can effectively recognize the license plate number at 90.86%. The required processing time to recognize a license plate is only 2 seconds on average. The result is consider good in comparison with the results obtained from previous system that was processed in a desktop PC with the range of result from 91.59% to 98% recognition rate and 0.284 second to 1.5 seconds recognition time.

Military personnel recognition system using texture, colour, and SURF features

Science.gov (United States)

Irhebhude, Martins E.; Edirisinghe, Eran A.

2014-06-01

This paper presents an automatic, machine vision based, military personnel identification and classification system. Classification is done using a Support Vector Machine (SVM) on sets of Army, Air Force and Navy camouflage uniform personnel datasets. In the proposed system, the arm of service of personnel is recognised by the camouflage of a persons uniform, type of cap and the type of badge/logo. The detailed analysis done include; camouflage cap and plain cap differentiation using gray level co-occurrence matrix (GLCM) texture feature; classification on Army, Air Force and Navy camouflaged uniforms using GLCM texture and colour histogram bin features; plain cap badge classification into Army, Air Force and Navy using Speed Up Robust Feature (SURF). The proposed method recognised camouflage personnel arm of service on sets of data retrieved from google images and selected military websites. Correlation-based Feature Selection (CFS) was used to improve recognition and reduce dimensionality, thereby speeding the classification process. With this method success rates recorded during the analysis include 93.8% for camouflage appearance category, 100%, 90% and 100% rates of plain cap and camouflage cap categories for Army, Air Force and Navy categories, respectively. Accurate recognition was recorded using SURF for the plain cap badge category. Substantial analysis has been carried out and results prove that the proposed method can correctly classify military personnel into various arms of service. We show that the proposed method can be integrated into a face recognition system, which will recognise personnel in addition to determining the arm of service which the personnel belong. Such a system can be used to enhance the security of a military base or facility.

System for automatic crate recognition

Directory of Open Access Journals (Sweden)

Radovan Kukla

2012-01-01

Full Text Available This contribution describes usage of computer vision and artificial intelligence methods for application. The method solves abuse of reverse vending machine. This topic has been solved as innovation voucher for the South Moravian Region. It was developed by Mendel university in Brno (Department of informatics – Faculty of Business and Economics and Department of Agricultural, Food and Environmental Engineering – Faculty of Agronomy together with the Czech subsidiary of Tomra. The project is focused on a possibility of integration industrial cameras and computers to process recognition of crates in the verse vending machine. The aim was the effective security system that will be able to save hundreds-thousands financial loss. As suitable development and runtime platform there was chosen product ControlWeb and VisionLab developed by Moravian Instruments Inc.

Automatic micropropagation of plants--the vision-system: graph rewriting as pattern recognition

Science.gov (United States)

Schwanke, Joerg; Megnet, Roland; Jensch, Peter F.

1993-03-01

The automation of plant-micropropagation is necessary to produce high amounts of biomass. Plants have to be dissected on particular cutting-points. A vision-system is needed for the recognition of the cutting-points on the plants. With this background, this contribution is directed to the underlying formalism to determine cutting-points on abstract-plant models. We show the usefulness of pattern recognition by graph-rewriting along with some examples in this context.

Social context predicts recognition systems in ant queens

DEFF Research Database (Denmark)

Dreier, Stéphanie Agnès Jeanine; d'Ettorre, Patrizia

2009-01-01

Recognition of group-members is a key feature of sociality. Ants use chemical communication to discriminate nestmates from intruders, enhancing kin cooperation and preventing parasitism. The recognition code is embedded in their cuticular chemical profile, which typically varies between colonies....... We predicted that ants might be capable of accurate recognition in unusual situations when few individuals interact repeatedly, as new colonies started by two to three queens. Individual recognition would be favoured by selection when queens establish dominance hierarchies, because repeated fights...... for dominance are costly; but it would not evolve in absence of hierarchies. We previously showed that Pachycondyla co-founding queens, which form dominance hierarchies, have accurate individual recognition based on chemical cues. Here, we used the ant Lasius niger to test the null hypothesis that individual...

Multimodal Biometric System Based on the Recognition of Face and Both Irises

Directory of Open Access Journals (Sweden)

Yeong Gon Kim

2012-09-01

Full Text Available The performance of unimodal biometric systems (based on a single modality such as face or fingerprint has to contend with various problems, such as illumination variation, skin condition and environmental conditions, and device variations. Therefore, multimodal biometric systems have been used to overcome the limitations of unimodal biometrics and provide high accuracy recognition. In this paper, we propose a new multimodal biometric system based on score level fusion of face and both irises' recognition. Our study has the following novel features. First, the device proposed acquires images of the face and both irises simultaneously. The proposed device consists of a face camera, two iris cameras, near-infrared illuminators and cold mirrors. Second, fast and accurate iris detection is based on two circular edge detections, which are accomplished in the iris image on the basis of the size of the iris detected in the face image. Third, the combined accuracy is enhanced by combining each score for the face and both irises using a support vector machine. The experimental results show that the equal error rate for the proposed method is 0.131%, which is lower than that of face or iris recognition and other fusion methods.

Neuro System Structure for Vehicle Recognition and Count in Floating Bridge Specific Conditions

Directory of Open Access Journals (Sweden)

Slobodan Beroš

2012-10-01

Full Text Available The paper presents the research of the sophisticated vehiclerecognition and count system based on the application of theneural network. The basic elements of neural network andadaptive logic network for object recognition are discussed. Theadaptive logic network solution ability based on simple digitalcircuits as crucial in real-time applications is pointed out. Thesimulation based on the use of reduced high level noise pictureand a tree 2. 7. software have shown excellent results. The consideredand simulated adaptive neural network based systemwith its good recognition and convergence is a useful real-timesolution for vehicle recognition and count in the floating bridgesevere conditions.

IN VITRO FLOW ANALYSIS OF NOVEL DOUBLE-CUTTING, OPEN-PORT, ULTRAHIGH-SPEED VITRECTOMY SYSTEMS.

Science.gov (United States)

Zehetner, Claus; Moelgg, Marion; Bechrakis, Emmanouil; Linhart, Caroline; Bechrakis, Nikolaos E

2017-10-09

To analyze the performance and flow characteristics of novel double-cutting, open-port, 23-, 25-, and 27-gauge ultrahigh-speed vitrectomy systems. In vitro fluidic measurements were performed to assess the volumetric aspiration profiles of several vitrectomy systems in basic salt solution and egg white. Double-cutting open-port vitrectomy probes delivered stable aspiration flow rates that were less prone to flow variation affected by the cutting speed. Increase in cutting frequency to the maximum level resulted in flow reduction of less than 10% (0.0%-9.5%). Commercially available 23-, 25-, and 27-G double-cutting probes exhibited higher egg-white and basic salt solution flow rates at all evaluated cut rates, with aspirational efficiencies being 1.1 to 2.9 times the flow rates of standard single-blade vitrectomy probes of the same caliber at the maximum preset vacuum. The highest relative differences were observed at faster cut rates. The newly introduced double-cutting open-port vitrectomy probes delivered stable aspiration flow rates that were less prone to flow variation affected by the cutting speed. The fluidic principle of constant flow even at the highest cut rates and low vacuum levels might impact surgical strategies, especially when performing manipulations close to the retina.

Feature Screening for Ultrahigh Dimensional Categorical Data with Applications.

Science.gov (United States)

Huang, Danyang; Li, Runze; Wang, Hansheng

2014-01-01

Ultrahigh dimensional data with both categorical responses and categorical covariates are frequently encountered in the analysis of big data, for which feature screening has become an indispensable statistical tool. We propose a Pearson chi-square based feature screening procedure for categorical response with ultrahigh dimensional categorical covariates. The proposed procedure can be directly applied for detection of important interaction effects. We further show that the proposed procedure possesses screening consistency property in the terminology of Fan and Lv (2008). We investigate the finite sample performance of the proposed procedure by Monte Carlo simulation studies, and illustrate the proposed method by two empirical datasets.

Effects of anesthetic agents on brain blood oxygenation level revealed with ultra-high field MRI

International Nuclear Information System (INIS)

Ciobanu, Luisa; Reynaud, Olivier; Le Bihan, Denis; Uhrig, Lynn; Jarraya, Bechir

2012-01-01

During general anesthesia it is crucial to control systemic hemodynamics and oxygenation levels. However, anesthetic agents can affect cerebral hemodynamics and metabolism in a drug-dependent manner, while systemic hemodynamics is stable. Brain-wide monitoring of this effect remains highly challenging. Because T2'*-weighted imaging at ultra-high magnetic field strengths benefits from a dramatic increase in contrast to noise ratio, we hypothesized that it could monitor anesthesia effects on brain blood oxygenation. We scanned rat brains at 7 T and 17.2 T under general anesthesia using different anesthetics (isoflurane, ketamine-xylazine, medetomidine). We showed that the brain/vessels contrast in T2'*- weighted images at 17.2 T varied directly according to the applied pharmacological anesthetic agent, a phenomenon that was visible, but to a much smaller extent at 7 T. This variation is in agreement with the mechanism of action of these agents. These data demonstrate that preclinical ultra-high field MRI can monitor the effects of a given drug on brain blood oxygenation level in the absence of systemic blood oxygenation changes and of any neural stimulation. (authors)

Ultrahigh-energy particles from cosmic strings

International Nuclear Information System (INIS)

Bhattacharjee, P.

1991-02-01

The idea of production of ultrahigh-energy particles in the present universe due to annihilation or collapse of topological defects is discussed. Topological defects, formed in symmetry-breaking phase transitions in the early universe, can survive till today owing to their topological stability. However, under certain circumstances, topological defects may be physically destroyed. When topological defects are destroyed, the energy contained in the defects can be released in the form of massive gauge- and Higgs bosons of the underlying spontaneously broken gauge theory. Subsequent decay of these massive particles can give rise to energetic particles ranging up to an energy on the order of the mass of the original particles released from the defects. This may give us a ''natural'' mechanism of production of extremely energetic cosmic ray particles in the universe today, without the need for any acceleration mechanism. To illustrate this idea, I describe in detail the calculation of the expected ultrahigh-energy proton spectrum due to a specific process which involves collapse or multiple self-intersections of a class of closed cosmic string loops formed in a phase transition at a grand unification energy scale. I discuss the possibility that some of the highest-energy cosmic ray particles are of this origin. By comparing with the observational results on the ultrahigh-energy cosmic rays, we derive an upper limit to the average fraction of the total energy in all ''primary'' cosmic string loops that may be released in the form of particles due to collapse or multiple self-intersections of these loops. No nuclei such as α's or Fe's are in the spectrum. 43 refs., 3 figs

Multi-font printed Mongolian document recognition system

Science.gov (United States)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

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.

Edge detection techniques for iris recognition system

International Nuclear Information System (INIS)

Tania, U T; Motakabber, S M A; Ibrahimy, M I

2013-01-01

Nowadays security and authentication are the major parts of our daily life. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate

Constraining sources of ultrahigh energy cosmic rays and shear acceleration mechanism of particles in relativistic jets

Energy Technology Data Exchange (ETDEWEB)

Liu, Ruoyu

2015-06-10

Ultrahigh energy cosmic rays are extreme energetic particles from outer space. They have aroused great interest among scientists for more than fifty years. However, due to the rarity of the events and complexity of the process of their propagation to Earth, they are still one of the biggest puzzles in modern high energy astrophysics. This dissertation is dedicated to study the origin of ultrahigh energy cosmic rays from various aspects. Firstly, we discuss a possible link between recently discovered sub-PeV/PeV neutrinos and ultrahigh energy cosmic rays. If these two kinds of particles share the same origin, the observation of neutrinos may provide additional and non-trivial constraints on the sources of ultrahigh energy cosmic rays. Secondly, we jointly employ the chemical composition measurement and the arrival directions of ultrahigh energy cosmic rays, and find a robust upper limit for distances of sources of ultrahigh energy cosmic rays above ∝55 EeV, as well as a lower limit for their metallicities. Finally, we study the shear acceleration mechanism in relativistic jets, which is a more efficient mechanism for the acceleration of higher energy particle. We compute the acceleration efficiency and the time-dependent particle energy spectrum, and explore the feature of synchrotron radiation of the accelerated particles. The possible realizations of this mechanism for acceleration of ultrahigh energy cosmic rays in different astrophysical environments is also discussed.

Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

Science.gov (United States)

Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

2018-04-01

To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

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.

Expectations for ultra-high energy interactions

International Nuclear Information System (INIS)

Feynman, R.P.

1978-01-01

Strong interactions at ultra-high energies are discussed with emphasis on the hadrons produced in high energy collisions. Evidence is considered that quantum chromodynamics might be the right theory, and also some estimates are given of quantum chromodynamics asymptotic-freedom phenomena, the work under discussion being very preliminary. 6 references

Automated alignment system for optical wireless communication systems using image recognition.

Science.gov (United States)

Brandl, Paul; Weiss, Alexander; Zimmermann, Horst

2014-07-01

In this Letter, we describe the realization of a tracked line-of-sight optical wireless communication system for indoor data distribution. We built a laser-based transmitter with adaptive focus and ray steering by a microelectromechanical systems mirror. To execute the alignment procedure, we used a CMOS image sensor at the transmitter side and developed an algorithm for image recognition to localize the receiver's position. The receiver is based on a self-developed optoelectronic integrated chip with low requirements on the receiver optics to make the system economically attractive. With this system, we were able to set up the communication link automatically without any back channel and to perform error-free (bit error rate <10⁻⁹) data transmission over a distance of 3.5 m with a data rate of 3 Gbit/s.

Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Zorins Aleksejs

2016-12-01

Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

Multivariate statistical pattern recognition system for reactor noise analysis

International Nuclear Information System (INIS)

Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

1976-01-01

A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system

Multivariate statistical pattern recognition system for reactor noise analysis

International Nuclear Information System (INIS)

Gonzalez, R.C.; Howington, L.C.; Sides, W.H. Jr.; Kryter, R.C.

1975-01-01

A multivariate statistical pattern recognition system for reactor noise analysis was developed. The basis of the system is a transformation for decoupling correlated variables and algorithms for inferring probability density functions. The system is adaptable to a variety of statistical properties of the data, and it has learning, tracking, and updating capabilities. System design emphasizes control of the false-alarm rate. The ability of the system to learn normal patterns of reactor behavior and to recognize deviations from these patterns was evaluated by experiments at the ORNL High-Flux Isotope Reactor (HFIR). Power perturbations of less than 0.1 percent of the mean value in selected frequency ranges were detected by the system. 19 references

Architecture of top down, parallel pattern recognition system TOPS and its application to the MR head images

International Nuclear Information System (INIS)

Matsunoshita, Jun-ichi; Akamatsu, Shigeo; Yamamoto, Shinji.

1993-01-01

This paper describes about the system architecture of a new image recognition system TOPS (top-down parallel pattern recognition system), and its application to the automatic extraction of brain organs (cerebrum, cerebellum, brain stem) from 3D-MRI images. Main concepts of TOPS are as follows: (1) TOPS is the top-down type recognition system, which allows parallel models in each level of hierarchy structure. (2) TOPS allows parallel image processing algorithms for one purpose (for example, for extraction of one special organ). This results in multiple candidates for one purpose, and judgment to get unique solution for it will be made at upper level of hierarchy structure. (author)

A Vision-Based Counting and Recognition System for Flying Insects in Intelligent Agriculture

Directory of Open Access Journals (Sweden)

Yuanhong Zhong

2018-05-01

Full Text Available Rapid and accurate counting and recognition of flying insects are of great importance, especially for pest control. Traditional manual identification and counting of flying insects is labor intensive and inefficient. In this study, a vision-based counting and classification system for flying insects is designed and implemented. The system is constructed as follows: firstly, a yellow sticky trap is installed in the surveillance area to trap flying insects and a camera is set up to collect real-time images. Then the detection and coarse counting method based on You Only Look Once (YOLO object detection, the classification method and fine counting based on Support Vector Machines (SVM using global features are designed. Finally, the insect counting and recognition system is implemented on Raspberry PI. Six species of flying insects including bee, fly, mosquito, moth, chafer and fruit fly are selected to assess the effectiveness of the system. Compared with the conventional methods, the test results show promising performance. The average counting accuracy is 92.50% and average classifying accuracy is 90.18% on Raspberry PI. The proposed system is easy-to-use and provides efficient and accurate recognition data, therefore, it can be used for intelligent agriculture applications.

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

Defect-engineered graphene chemical sensors with ultrahigh sensitivity.

Science.gov (United States)

Lee, Geonyeop; Yang, Gwangseok; Cho, Ara; Han, Jeong Woo; Kim, Jihyun

2016-05-25

We report defect-engineered graphene chemical sensors with ultrahigh sensitivity (e.g., 33% improvement in NO2 sensing and 614% improvement in NH3 sensing). A conventional reactive ion etching system was used to introduce the defects in a controlled manner. The sensitivity of graphene-based chemical sensors increased with increasing defect density until the vacancy-dominant region was reached. In addition, the mechanism of gas sensing was systematically investigated via experiments and density functional theory calculations, which indicated that the vacancy defect is a major contributing factor to the enhanced sensitivity. This study revealed that defect engineering in graphene has significant potential for fabricating ultra-sensitive graphene chemical sensors.

Design of ultrahigh brightness solar-pumped disk laser.

Science.gov (United States)

Liang, Dawei; Almeida, Joana

2012-09-10

To significantly improve the solar-pumped laser beam brightness, a multi-Fresnel lens scheme is proposed for side-pumping either a single-crystal Nd:YAG or a core-doped ceramic Sm(3+) Nd:YAG disk. Optimum laser system parameters are found through ZEMAX and LASCAD numerical analysis. An ultrahigh laser beam figure of merit B of 53 W is numerically calculated, corresponding to a significant enhancement of more than 180 times over the previous record. 17.7 W/m(2) collection efficiency is also numerically attained. The strong thermal effects that have hampered present-day rod-type solar-pumped lasers can also be largely alleviated.

Dewaterability of five sewage sludges in Guangzhou conditioned with Fenton's reagent/lime and pilot-scale experiments using ultrahigh pressure filtration system.

Science.gov (United States)

Liang, Jialin; Huang, Shaosong; Dai, Yongkang; Li, Lei; Sun, Shuiyu

2015-11-01

Sludge conditioning with Fenton's reagent and lime is a valid method for sludge dewatering. This study investigated the influence of different organic matter content sludge on sludge dewatering and discussed the main mechanism of sludge conditioning by combined Fenton's reagent and lime. The results indicated that the specific resistance to filterability (SRF) of sludge was reduced efficiently by approximately 90%, when conditioned with Fenton's reagent and lime. Through single factor experiments, the optimal conditioning combinations were found. In addition, the relationship between VSS% and consumption of the reagents was detected. Furthermore, it was also demonstrated that the SRF and filtrate TOC values had a significant correlation with VSS% of sludge (including raw and conditioned). The main mechanism of sludge dewatering was also investigated. Firstly, it revealed that the dewaterability of sludge was closely correlated to extracellular polymeric substances (EPS) and bound water contents. Secondly, the results of scanning electron microscopy (SEM) stated that sludge particles were to be smaller and thinner after conditioning. And this structure could easily form outflow channels for releasing free water. Additionally, with the ultrahigh pressure filtration system, the water content of sludge cake conditioned with Fenton's reagent and lime could be reduced to below 50%. Moreover, the economic assessment shows that Fenton's reagent and lime combined with ultrahigh pressure filtration system can be an economical and viable technology for sewage sludge dewatering. Finally, three types of sludge were classified: (1) Fast to dewater; (2) Moderately fast to dewater; (3) Slow to dewater sludge. Copyright © 2015 Elsevier Ltd. All rights reserved.

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

Science.gov (United States)

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

Iris analysis for biometric recognition systems

CERN Document Server

Bodade, Rajesh M

2014-01-01

The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

Flexible Piezoelectric Sensor-Based Gait Recognition

Directory of Open Access Journals (Sweden)

Youngsu Cha

2018-02-01

Full Text Available Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over 93 %.

A novel ultra-high vacuum manipulator with six degrees of freedom

International Nuclear Information System (INIS)

Auciello, O.; Lulich, C.; Alonso, E.V.; Baragiola, R.A.

1977-01-01

An ultra-high vacuum goniometer of novel design for use in experiments with ion beams is described. The goniometer uses a wire system to transmit movements, is bakeable to 200 0 C and is reproducible in its angular positions to within 1.3 X 10 -4 rad (0.008 0 ). It allows a sample to be rotated around two axes over 360 0 , around a third over 180 0 , and to be translated along three perpendicular axes. (Auth.)

Working in the magnetic field of ultrahigh field MRI

International Nuclear Information System (INIS)

Leitgeb, N.; Gombotz, H.

2013-01-01

Development of magnetic resonance imaging (MRI) device technology continues to increase the static magnetic flux densities applied and consequently leads to considerably increased occupational exposure. This has already made it necessary to review limits of occupational exposure and to postpone European legal regulations for occupational exposure to electromagnetic fields. This raises the question whether and if so which adverse health effects and health risks might be associated with occupational exposure to MRI ultra-high static magnetic fields. Based on a survey on interaction mechanisms recommendations and safety rules are presented to help minimize adverse health effects of emerging ultra-high field MRI. (orig.) [de

Toward an ultra-high resolution community climate system model for the BlueGene platform

International Nuclear Information System (INIS)

Dennis, John M; Jacob, Robert; Vertenstein, Mariana; Craig, Tony; Loy, Raymond

2007-01-01

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10 0 resolution for CICE, POP, and CLM models and 1/4 0 resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Science.gov (United States)

Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

2015-01-01

A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

The neuro-immunological interface in an evolutionary perspective: the dynamic relationship between effector and recognition systems.

Science.gov (United States)

Ottaviani, E; Valensin, S; Franceschi, C

1998-04-16

The evolutionary perspective indicates that an immune-neuroendocrine effector system integrating innate immunity, stress and inflammation is present in invertebrates. This defense network, centered on the macrophage and exerting primitive and highly promiscuous recognition units, is very effective, ancestral and appears to have been conserved throughout evolution from invertebrates to higher vertebrates. It would seem that there was a "big bang" in the recognition system of lower vertebrates, and T and B cell repertoires, MHC and antibodies suddenly appeared. We argue that this phenomenon is the counterpart of the increasing complexity of the internal circuitry and recognition units in the effector system. The immediate consequences were a progressive enlargement of the pathogen repertoire and new problems regarding self/not-self discrimination. Probably not by chance, a new organ appeared, capable of purging cells able of excessive self recognition. This organ, the thymus, appears to be the result of a well known evolutionary strategy of re-using pre-existing material (neuroendocrine cells and mediators constituting the thymic microenvironment). This bricolage at an organ level is similar to the effect we have already described at the level of molecules and functions of the defense network, and has a general counterpart at genetic level. Thus, in vertebrates, the conserved immune-neuroendocrine effector system remains of fundamental importance in defense against pathogens, while its efficiency has increased through synergy with the new, clonotipical recognition repertoire.

Electric gun: a new tool for ultrahigh-pressure research

International Nuclear Information System (INIS)

Weingart, R.C.; Chau, H.H.; Goosman, D.R.; Hofer, W.W.; Honodel, C.A.; Lee, R.S.; Steinberg, D.J.; Stroud, J.R.

1979-01-01

We have developed a new tool for ultrahigh-pressure research at LLL. This system, which we call the electric gun, has already achieved thin flyer plate velocities in excess of 20 km/s and pressures of the order of 2 TPa in tantalum. We believe that the electric gun is competitive with laser- and nuclear-driven methods of producing shocks in the 1-to-5 TPa range because of its precision and ease and economy of operation. Its development is recommended for shock initiation studies, dry runs for Site 300 hydroshots, and as a shock wave generator for surface studies

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

Science.gov (United States)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Pattern-recognition system application to EBR-II plant-life extension

International Nuclear Information System (INIS)

King, R.W.; Radtke, W.H.; Mott, J.E.

1988-01-01

A computer-based pattern-recognition system, the System State Analyzer (SSA), is being used as part of the EBR-II plant-life extension program for detection of degradation and other abnormalities in plant systems. The SSA is used for surveillance of the EBR-II primary system instrumentation, primary sodium pumps, and plant heat balances. Early results of this surveillance indicate that the SSA can detect instrumentation degradation and system performance degradation over varying time intervals, and can provide derived signal values to replace signals from failed critical sensors. These results are being used in planning for extended-life operation of EBR-II

Performance Evaluation of Speech Recognition Systems as a Next-Generation Pilot-Vehicle Interface Technology

Science.gov (United States)

Arthur, Jarvis J., III; Shelton, Kevin J.; Prinzel, Lawrence J., III; Bailey, Randall E.

2016-01-01

During the flight trials known as Gulfstream-V Synthetic Vision Systems Integrated Technology Evaluation (GV-SITE), a Speech Recognition System (SRS) was used by the evaluation pilots. The SRS system was intended to be an intuitive interface for display control (rather than knobs, buttons, etc.). This paper describes the performance of the current "state of the art" Speech Recognition System (SRS). The commercially available technology was evaluated as an application for possible inclusion in commercial aircraft flight decks as a crew-to-vehicle interface. Specifically, the technology is to be used as an interface from aircrew to the onboard displays, controls, and flight management tasks. A flight test of a SRS as well as a laboratory test was conducted.

Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

International Nuclear Information System (INIS)

Lee, Inho; Oh, Jaesung; Oh, Jun-Ho; Kim, Inhyeok

2017-01-01

This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

Camera-laser fusion sensor system and environmental recognition for humanoids in disaster scenarios

Energy Technology Data Exchange (ETDEWEB)

Lee, Inho [Institute for Human and Machine Cognition (IHMC), Florida (United States); Oh, Jaesung; Oh, Jun-Ho [Korea Advanced Institute of Science and Technology (KAIST), Daejeon (Korea, Republic of); Kim, Inhyeok [NAVER Green Factory, Seongnam (Korea, Republic of)

2017-06-15

This research aims to develop a vision sensor system and a recognition algorithm to enable a humanoid to operate autonomously in a disaster environment. In disaster response scenarios, humanoid robots that perform manipulation and locomotion tasks must identify the objects in the environment from those challenged by the call by the United States’ Defense Advanced Research Projects Agency, e.g., doors, valves, drills, debris, uneven terrains, and stairs, among others. In order for a humanoid to undertake a number of tasks, we con- struct a camera–laser fusion system and develop an environmental recognition algorithm. Laser distance sensor and motor are used to obtain 3D cloud data. We project the 3D cloud data onto a 2D image according to the intrinsic parameters of the camera and the distortion model of the lens. In this manner, our fusion sensor system performs functions such as those performed by the RGB-D sensor gener- ally used in segmentation research. Our recognition algorithm is based on super-pixel segmentation and random sampling. The proposed approach clusters the unorganized cloud data according to geometric characteristics, namely, proximity and co-planarity. To assess the feasibility of our system and algorithm, we utilize the humanoid robot, DRC-HUBO, and the results are demonstrated in the accompanying video.

From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

Science.gov (United States)

Yildiz, Izzet B; von Kriegstein, Katharina; Kiebel, Stefan J

2013-01-01

Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

Directory of Open Access Journals (Sweden)

Izzet B Yildiz

Full Text Available Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

Ultra-high density aligned Carbon-nanotube with controled nano-morphology for supercapacitors

Science.gov (United States)

Ghaffari, Mehdi; Zhao, Ran; Liu, Yang; Zhou, Yue; Cheng, Jiping; Guzman de Villoria, Roberto; Wardle, B. L.; Zhang, Q. M.

2012-02-01

Recent advances in fabricating controlled-morphology vertically aligned carbon nanotubes (VA-CNTs) with ultrahigh volume fractioncreate unique opportunities for developing unconventional supercapacitors with ultra-high energy density, power density, and long charge/discharge cycle life.Continuous paths through inter-VA-CNT channels allow fast ion transport, and high electrical conduction of the aligned CNTs in the composite electrodes lead to fast discharge speed. We investigate the charge-discharge characteristics of VA-CNTs with >20 vol% of CNT and ionic liquids as electrolytes. By employing both the electric and electromechanical spectroscopes, as well as nanostructured materials characterization, the ion transport and storage behaviors in porous electrodes are studied. The results suggest pathways for optimizing the electrode morphology in supercapacitorsusing ultra-high volume fraction VA-CNTs to further enhance performance.

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%.

Entrance C - New Automatic Number Plate Recognition System

CERN Multimedia

2013-01-01

Entrance C (Satigny) is now equipped with a latest-generation Automatic Number Plate Recognition (ANPR) system and a fast-action road gate.   During the month of August, Entrance C will be continuously open from 7.00 a.m. to 7.00 p.m. (working days only). The security guards will open the gate as usual from 7.00 a.m. to 9.00 a.m. and from 5.00 p.m. to 7.00 p.m. For the rest of the working day (9.00 a.m. to 5.00 p.m.) the gate will operate automatically. Please observe the following points:       Stop at the STOP sign on the ground     Position yourself next to the card reader for optimal recognition     Motorcyclists must use their CERN card     Cyclists may not activate the gate and should use the bicycle turnstile     Keep a safe distance from the vehicle in front of you   If access is denied, please check that your vehicle regist...

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data

Directory of Open Access Journals (Sweden)

Alessandro Manzi

2017-05-01

Full Text Available Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM, trained with Sequential Minimal Optimization (SMO. The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60 and the Telecommunication Systems Team (TST Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

Science.gov (United States)

Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

2017-05-11

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

Cherry Picking Robot Vision Recognition System Based on OpenCV

Directory of Open Access Journals (Sweden)

Zhang Qi Rong

2016-01-01

Full Text Available Through OpenCV function, the cherry in a natural environment image after image preprocessing, color recognition, threshold segmentation, morphological filtering, edge detection, circle Hough transform, you can draw the cherry’s center and circular contour, to carry out the purpose of the machine picking. The system is simple and effective.

A Biometric Face Recognition System Using an Algorithm Based on the Principal Component Analysis Technique

Directory of Open Access Journals (Sweden)

Gheorghe Gîlcă

2015-06-01

Full Text Available This article deals with a recognition system using an algorithm based on the Principal Component Analysis (PCA technique. The recognition system consists only of a PC and an integrated video camera. The algorithm is developed in MATLAB language and calculates the eigenfaces considered as features of the face. The PCA technique is based on the matching between the facial test image and the training prototype vectors. The mathcing score between the facial test image and the training prototype vectors is calculated between their coefficient vectors. If the matching is high, we have the best recognition. The results of the algorithm based on the PCA technique are very good, even if the person looks from one side at the video camera.

Ultra-High Field Magnets for X-Ray and Neutron Scattering using High Temperature Superconductors

Energy Technology Data Exchange (ETDEWEB)

Winn, Barry L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Broholm, C. [Johns Hopkins Univ., Baltimore, MD (United States); Bird, M. [Florida State Univ., Tallahassee, FL (United States). National High Magnetic Field Lab. (MagLab); Breneman, Bruce C. [General Atomics, San Diego, CA (United States); Coffey, Michael [Cryomagnetics, Oak Ridge, TN (United States); Cutler, Roy I. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Duckworth, Robert C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Erwin, R. [National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States); Hahn, Seungyong [Florida State Univ., Tallahassee, FL (United States). National High Magnetic Field Lab. (MagLab); Hernandez, Yamali [National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States); Herwig, Kenneth W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Holland, Leo D. [General Atomics, San Diego, CA (United States); Lonergan, Kevin M. [Oxford Instruments, Abingdon (United Kingdom); Melhem, Ziad [Oxford Instruments, Abingdon (United Kingdom); Minter, Stephen J. [Cryomagnetics, Oak Ridge, TN (United States); Nelson, C. [Brookhaven National Lab. (BNL), Upton, NY (United States); Paranthaman, M. Parans [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pierce, Josh [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ruff, Jacob [Cornell Univ., Ithaca, NY (United States); Shen, Tengming [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sherline, Todd E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Smeibidl, Peter G. [Helmholtz-Zentrum Berlin (HZB), (Germany); Tennant, David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); van der Laan, Danko [Advanced Conductor Technologies, LLC, Boulder, CO (United States); Wahle, Robert J. [Helmholtz-Zentrum Berlin (HZB), (Germany); Zhang, Yifei [SuperPower, Inc., Schenectady, NY (United States)

2017-01-01

X-ray and neutron scattering techniques are capable of acquiring information about the structure and dynamics of quantum matter. However, the high-field magnet systems currently available at x-ray and neutron scattering facilities in the United States are limited to fields of 16 tesla (T) at maximum, which precludes applications that require and/or study ultra-high field states of matter. This gap in capability—and the need to address it—is a central conclusion of the 2005 National Academy of Sciences report by the Committee on Opportunities in High Magnetic Field Science. To address this gap, we propose a magnet development program that would more than double the field range accessible to scattering experiments. With the development and use of new ultra-high field–magnets, the program would bring into view new worlds of quantum matter with profound impacts on our understanding of advanced electronic materials.

Effects of anesthetic agents on brain blood oxygenation level revealed with ultra-high field MRI.

Directory of Open Access Journals (Sweden)

Luisa Ciobanu

Full Text Available During general anesthesia it is crucial to control systemic hemodynamics and oxygenation levels. However, anesthetic agents can affect cerebral hemodynamics and metabolism in a drug-dependent manner, while systemic hemodynamics is stable. Brain-wide monitoring of this effect remains highly challenging. Because T(2*-weighted imaging at ultra-high magnetic field strengths benefits from a dramatic increase in contrast to noise ratio, we hypothesized that it could monitor anesthesia effects on brain blood oxygenation. We scanned rat brains at 7T and 17.2T under general anesthesia using different anesthetics (isoflurane, ketamine-xylazine, medetomidine. We showed that the brain/vessels contrast in T(2*-weighted images at 17.2T varied directly according to the applied pharmacological anesthetic agent, a phenomenon that was visible, but to a much smaller extent at 7T. This variation is in agreement with the mechanism of action of these agents. These data demonstrate that preclinical ultra-high field MRI can monitor the effects of a given drug on brain blood oxygenation level in the absence of systemic blood oxygenation changes and of any neural stimulation.

Systematic Calibration for Ultra-High Accuracy Inertial Measurement Units

Directory of Open Access Journals (Sweden)

Qingzhong Cai

2016-06-01

Full Text Available An inertial navigation system (INS has been widely used in challenging GPS environments. With the rapid development of modern physics, an atomic gyroscope will come into use in the near future with a predicted accuracy of 5 × 10−6°/h or better. However, existing calibration methods and devices can not satisfy the accuracy requirements of future ultra-high accuracy inertial sensors. In this paper, an improved calibration model is established by introducing gyro g-sensitivity errors, accelerometer cross-coupling errors and lever arm errors. A systematic calibration method is proposed based on a 51-state Kalman filter and smoother. Simulation results show that the proposed calibration method can realize the estimation of all the parameters using a common dual-axis turntable. Laboratory and sailing tests prove that the position accuracy in a five-day inertial navigation can be improved about 8% by the proposed calibration method. The accuracy can be improved at least 20% when the position accuracy of the atomic gyro INS can reach a level of 0.1 nautical miles/5 d. Compared with the existing calibration methods, the proposed method, with more error sources and high order small error parameters calibrated for ultra-high accuracy inertial measurement units (IMUs using common turntables, has a great application potential in future atomic gyro INSs.

Telescope Array Radar (TARA) observatory for Ultra-High Energy Cosmic Rays

Energy Technology Data Exchange (ETDEWEB)

Abbasi, R.; Othman, M. Abou Bakr [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Allen, C. [University of Kansas, Lawrence, KS 66045 (United States); Beard, L. [Purdue University, West Lafayette, IN 47907 (United States); Belz, J. [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Besson, D. [University of Kansas, Lawrence, KS 66045 (United States); Moscow Engineering and Physics Institute, 31 Kashirskaya Shosse, Moscow 115409 (Russian Federation); Byrne, M.; Farhang-Boroujeny, B.; Gardner, A. [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Gillman, W.H. [Gillman and Associates, Salt Lake City, UT 84106 (United States); Hanlon, W. [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Hanson, J. [University of Kansas, Lawrence, KS 66045 (United States); Jayanthmurthy, C. [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Kunwar, S. [University of Kansas, Lawrence, KS 66045 (United States); Larson, S.L. [Utah State University, Logan, Utah 84322 (United States); Myers, I., E-mail: isaac@cosmic.utah.edu [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Prohira, S.; Ratzlaff, K. [University of Kansas, Lawrence, KS 66045 (United States); Sokolsky, P. [University of Utah, 115 S 1400 E #201 JFB, Salt Lake City, UT 84112 (United States); Takai, H. [Brookhaven National Laboratory, Upton, NY 11973 (United States); and others

2014-12-11

Construction was completed during summer 2013 on the Telescope Array RAdar (TARA) bi-static radar observatory for Ultra-High Energy Cosmic Rays (UHECR). TARA is co-located with the Telescope Array, the largest “conventional” cosmic ray detector in the Northern Hemisphere, in radio-quiet Western Utah. TARA employs an 8 MW Effective Radiated Power (ERP) VHF transmitter and smart receiver system based on a 250 MS/s data acquisition system in an effort to detect the scatter of sounding radiation by UHECR-induced atmospheric ionization. TARA seeks to demonstrate bi-static radar as a useful new remote sensing technique for UHECRs. In this report, we describe the design and performance of the TARA transmitter and receiver systems.

Telescope Array Radar (TARA) observatory for Ultra-High Energy Cosmic Rays

International Nuclear Information System (INIS)

Abbasi, R.; Othman, M. Abou Bakr; Allen, C.; Beard, L.; Belz, J.; Besson, D.; Byrne, M.; Farhang-Boroujeny, B.; Gardner, A.; Gillman, W.H.; Hanlon, W.; Hanson, J.; Jayanthmurthy, C.; Kunwar, S.; Larson, S.L.; Myers, I.; Prohira, S.; Ratzlaff, K.; Sokolsky, P.; Takai, H.

2014-01-01

Construction was completed during summer 2013 on the Telescope Array RAdar (TARA) bi-static radar observatory for Ultra-High Energy Cosmic Rays (UHECR). TARA is co-located with the Telescope Array, the largest “conventional” cosmic ray detector in the Northern Hemisphere, in radio-quiet Western Utah. TARA employs an 8 MW Effective Radiated Power (ERP) VHF transmitter and smart receiver system based on a 250 MS/s data acquisition system in an effort to detect the scatter of sounding radiation by UHECR-induced atmospheric ionization. TARA seeks to demonstrate bi-static radar as a useful new remote sensing technique for UHECRs. In this report, we describe the design and performance of the TARA transmitter and receiver systems

Telescope Array Radar (TARA) observatory for Ultra-High Energy Cosmic Rays

Science.gov (United States)

Abbasi, R.; Othman, M. Abou Bakr; Allen, C.; Beard, L.; Belz, J.; Besson, D.; Byrne, M.; Farhang-Boroujeny, B.; Gardner, A.; Gillman, W. H.; Hanlon, W.; Hanson, J.; Jayanthmurthy, C.; Kunwar, S.; Larson, S. L.; Myers, I.; Prohira, S.; Ratzlaff, K.; Sokolsky, P.; Takai, H.; Thomson, G. B.; Von Maluski, D.

2014-12-01

Construction was completed during summer 2013 on the Telescope Array RAdar (TARA) bi-static radar observatory for Ultra-High Energy Cosmic Rays (UHECR). TARA is co-located with the Telescope Array, the largest "conventional" cosmic ray detector in the Northern Hemisphere, in radio-quiet Western Utah. TARA employs an 8 MW Effective Radiated Power (ERP) VHF transmitter and smart receiver system based on a 250 MS/s data acquisition system in an effort to detect the scatter of sounding radiation by UHECR-induced atmospheric ionization. TARA seeks to demonstrate bi-static radar as a useful new remote sensing technique for UHECRs. In this report, we describe the design and performance of the TARA transmitter and receiver systems.

Kernel learning algorithms for face recognition

CERN Document Server

Li, Jun-Bao; Pan, Jeng-Shyang

2013-01-01

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

Ultrahigh-speed X-ray imaging of hypervelocity projectiles

Science.gov (United States)

Miller, Stuart; Singh, Bipin; Cool, Steven; Entine, Gerald; Campbell, Larry; Bishel, Ron; Rushing, Rick; Nagarkar, Vivek V.

2011-08-01

High-speed X-ray imaging is an extremely important modality for healthcare, industrial, military and research applications such as medical computed tomography, non-destructive testing, imaging in-flight projectiles, characterizing exploding ordnance, and analyzing ballistic impacts. We report on the development of a modular, ultrahigh-speed, high-resolution digital X-ray imaging system with large active imaging area and microsecond time resolution, capable of acquiring at a rate of up to 150,000 frames per second. The system is based on a high-resolution, high-efficiency, and fast-decay scintillator screen optically coupled to an ultra-fast image-intensified CCD camera designed for ballistic impact studies and hypervelocity projectile imaging. A specially designed multi-anode, high-fluence X-ray source with 50 ns pulse duration provides a sequence of blur-free images of hypervelocity projectiles traveling at speeds exceeding 8 km/s (18,000 miles/h). This paper will discuss the design, performance, and high frame rate imaging capability of the system.

Intelligent color recognition system using micro-controller

International Nuclear Information System (INIS)

Mohd Ashhar Khalid; Khairiah Yazid; Nur Aira Abd Rahman; Azaman Ahmad

2006-01-01

Color is widely used in categorizing the quality of products as well as a marker for automatic selection and discrimination of products. Most of color recognizing process is done manually and due to the fact that human perceived color differently, different of opinion frequently occur. This paper deals with the development of an intelligent color recognition system used for discriminating the ripeness of oil palm fruits into three categories namely ripe, under-ripe and un-ripe. In deciding the categories of fruit a sample belong, a technique of decision making similar to human thinking called neural network has been implemented. Implementation of neural network using a micro-controller is not so common, due to a limited capability in floating point calculation. To overcome the problem, a floating-point co-processor specially designed for micro-controller is used. The paper will report the system design and the network training and implementation methods. The effectiveness of the system compared to human decision method is also reported. (Author)

Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

Directory of Open Access Journals (Sweden)

Jiangyi Qin

Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

Online handwritten mathematical expression recognition

Science.gov (United States)

Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

2007-01-01

We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

Science.gov (United States)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

2005-09-01

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

Evaluating a voice recognition system: finding the right product for your department.

Science.gov (United States)

Freeh, M; Dewey, M; Brigham, L

2001-06-01

The Department of Radiology at the University of Utah Health Sciences Center has been in the process of transitioning from the traditional film-based department to a digital imaging department for the past 2 years. The department is now transitioning from the traditional method of dictating reports (dictation by radiologist to transcription to review and signing by radiologist) to a voice recognition system. The transition to digital operations will not be complete until we have the ability to directly interface the dictation process with the image review process. Voice recognition technology has advanced to the level where it can and should be an integral part of the new way of working in radiology and is an integral part of an efficient digital imaging department. The transition to voice recognition requires the task of identifying the product and the company that will best meet a department's needs. This report introduces the methods we used to evaluate the vendors and the products available as we made our purchasing decision. We discuss our evaluation method and provide a checklist that can be used by other departments to assist with their evaluation process. The criteria used in the evaluation process fall into the following major categories: user operations, technical infrastructure, medical dictionary, system interfaces, service support, cost, and company strength. Conclusions drawn from our evaluation process will be detailed, with the intention being to shorten the process for others as they embark on a similar venture. As more and more organizations investigate the many products and services that are now being offered to enhance the operations of a radiology department, it becomes increasingly important that solid methods are used to most effectively evaluate the new products. This report should help others complete the task of evaluating a voice recognition system and may be adaptable to other products as well.

Multi-Modal Activity Recognition Systems with Minimal Training Data and Unobtrusive Environmental Instrumentations

OpenAIRE

Bauer, Gerald

2014-01-01

The recognition of day-to-day activities is still a very challenging and important research topic. During recent years, a lot of research has gone into designing and realizing smart environ- ments in different application areas such as health care, maintenance, sports or smart homes. As a result, a large amount of sensor modalities were developed, different types of activity and context recognition services were implemented and the resulting systems were benchmarked using state-of-the-art eva...

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

Directory of Open Access Journals (Sweden)

Minglin Wu

2016-10-01

Full Text Available In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

Ultrahigh Field NMR and MRI: Science at a Crossroads Workshop Report

International Nuclear Information System (INIS)

Polenova, Tatyana; Budinger, Thomas F.

2016-01-01

The workshop ''Ultrahigh Field NMR and MRI: Science at Crossroads'', initiated by the scientific community and supported by the National Science Foundation, the Department of Energy, and the National Institutes of Health, took place on November 12-13, 2015, in Bethesda, MD, on the NIH campus. The meeting was held to assess the science drivers, technological challenges, prospects for achieving field strengths for NMR and MRI nearly double their current value, and strategies on how to provide ultrahigh field NMR/MRI capabilities to a national user community.

A Russian Keyword Spotting System Based on Large Vocabulary Continuous Speech Recognition and Linguistic Knowledge

Directory of Open Access Journals (Sweden)

Valentin Smirnov

2016-01-01

Full Text Available The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variation algorithm, and the experimental results on the real-life telecom data are provided. The description of system architecture and the user interface is provided. The system is based on CMU Sphinx open-source speech recognition platform and on the linguistic models and algorithms developed by Speech Drive LLC. The effective combination of baseline statistic methods, real-world training data, and the intensive use of linguistic knowledge led to a quality result applicable to industrial use.

Study on creep of fiber reinforced ultra-high strength concrete based on strength

Science.gov (United States)

Peng, Wenjun; Wang, Tao

2018-04-01

To complement the creep performance of ultra-high strength concrete, the long creep process of fiber reinforced concrete was studied in this paper. The long-term creep process and regularity of ultra-high strength concrete with 0.5% PVA fiber under the same axial compression were analyzed by using concrete strength (C80/C100/C120) as a variable. The results show that the creep coefficient of ultra-high strength concrete decreases with the increase of concrete strength. Compared with ACI209R (92), GL2000 models, it is found that the predicted value of ACI209R (92) are close to the experimental value, and the creep prediction model suitable for this experiment is proposed based on ACI209R (92).

Predicting Performance of a Face Recognition System Based on Image Quality

NARCIS (Netherlands)

Dutta, A.

2015-01-01

In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

Ultrahigh-energy cosmic rays: facts, myths and legends

International Nuclear Information System (INIS)

Anchordoqui, L.A.

2011-01-01

This is a written version of a series of lectures aimed at graduate students in astrophysics and theoretical/experimental particle physics. In the first part, we explain the important progress made in recent years towards understanding the experimental data on cosmic rays with energies > or approx. 10 8 GeV. We begin with a brief survey of the available data, including a description of the energy spectrum, mass composition and arrival directions. At this point we also give a short overview of experimental techniques. After that, we introduce the fundamentals of acceleration and propagation in order to discuss the conjectured nearby cosmic-ray sources, and emphasize some of the prospects for a new (multiparticle) astronomy. Next, we survey the state of the art regarding the ultrahigh-energy cosmic neutrinos that should be produced in association with the observed cosmic rays. In the second part, we summarize the phenomenology of cosmic-ray air showers. We explain the hadronic interaction models used to extrapolate results from collider data to ultrahigh energies, and describe the prospects for insights into forward physics at the Large Hadron Collider. We also explain the main electromagnetic processes that govern the longitudinal shower evolution. Armed with these two principal shower ingredients and motivation from the underlying physics, we describe the different methods proposed to distinguish primary species. In the last part, we outline how ultrahigh-energy cosmic-ray interactions can be used to probe new physics beyond the electroweak scale. (author)

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.

Indoor navigation by image recognition

Science.gov (United States)

Choi, Io Teng; Leong, Chi Chong; Hong, Ka Wo; Pun, Chi-Man

2017-07-01

With the progress of smartphones hardware, it is simple on smartphone using image recognition technique such as face detection. In addition, indoor navigation system development is much slower than outdoor navigation system. Hence, this research proves a usage of image recognition technique for navigation in indoor environment. In this paper, we introduced an indoor navigation application that uses the indoor environment features to locate user's location and a route calculating algorithm to generate an appropriate path for user. The application is implemented on Android smartphone rather than iPhone. Yet, the application design can also be applied on iOS because the design is implemented without using special features only for Android. We found that digital navigation system provides better and clearer location information than paper map. Also, the indoor environment is ideal for Image recognition processing. Hence, the results motivate us to design an indoor navigation system using image recognition.

Hardware/Software Co-Design of a Traffic Sign Recognition System Using Zynq FPGAs

Directory of Open Access Journals (Sweden)

Yan Han

2015-12-01

Full Text Available Traffic sign recognition (TSR, taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which achieves invariance to rotated, skewed and occluded signs. In addition to the accuracy and robustness issues, a TSR system should target a real-time implementation on an embedded system. Therefore, a hardware/software co-design architecture for a Zynq-7000 FPGA is presented as a major objective of this work. The sign detection operations are accelerated by programmable hardware logic that searches the potential candidates for sign classification. Sign recognition and classification uses a feature extraction and matching algorithm, which is implemented as a software component that runs on the embedded ARM CPU.

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.

Toward an ultra-high resolution community climate system model for the BlueGene platform

Energy Technology Data Exchange (ETDEWEB)

Dennis, John M [Computer Science Section, National Center for Atmospheric Research, Boulder, CO (United States); Jacob, Robert [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States); Vertenstein, Mariana [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Craig, Tony [Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO (United States); Loy, Raymond [Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL (United States)

2007-07-15

Global climate models need to simulate several small, regional-scale processes which affect the global circulation in order to accurately simulate the climate. This is particularly important in the ocean where small scale features such as oceanic eddies are currently represented with adhoc parameterizations. There is also a need for higher resolution to provide climate predictions at small, regional scales. New high-performance computing platforms such as the IBM BlueGene can provide the necessary computational power to perform ultra-high resolution climate model integrations. We have begun to investigate the scaling of the individual components of the Community Climate System Model to prepare it for integrations on BlueGene and similar platforms. Our investigations show that it is possible to successfully utilize O(32K) processors. We describe the scalability of five models: the Parallel Ocean Program (POP), the Community Ice CodE (CICE), the Community Land Model (CLM), and the new CCSM sequential coupler (CPL7) which are components of the next generation Community Climate System Model (CCSM); as well as the High-Order Method Modeling Environment (HOMME) which is a dynamical core currently being evaluated within the Community Atmospheric Model. For our studies we concentrate on 1/10{sup 0} resolution for CICE, POP, and CLM models and 1/4{sup 0} resolution for HOMME. The ability to simulate high resolutions on the massively parallel petascale systems that will dominate high-performance computing for the foreseeable future is essential to the advancement of climate science.

AMANDA Observations Constrain the Ultrahigh Energy Neutrino Flux

Energy Technology Data Exchange (ETDEWEB)

Halzen, Francis; /Wisconsin U., Madison; Hooper, Dan; /Fermilab

2006-05-01

A number of experimental techniques are currently being deployed in an effort to make the first detection of ultra-high energy cosmic neutrinos. To accomplish this goal, techniques using radio and acoustic detectors are being developed, which are optimally designed for studying neutrinos with energies in the PeV-EeV range and above. Data from the AMANDA experiment, in contrast, has been used to place limits on the cosmic neutrino flux at less extreme energies (up to {approx}10 PeV). In this letter, we show that by adopting a different analysis strategy, optimized for much higher energy neutrinos, the same AMANDA data can be used to place a limit competitive with radio techniques at EeV energies. We also discuss the sensitivity of the IceCube experiment, in various stages of deployment, to ultra-high energy neutrinos.

PALESTINE AUTOMOTIVE LICENSE IDENTITY RECOGNITION FOR INTELLIGENT PARKING SYSTEM

Directory of Open Access Journals (Sweden)

ANEES ABU SNEINEH

2017-05-01

Full Text Available 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 system. An intelligent automotive parking system is effectively implemented by integrating image processing technologies and an Arduino controller. Results show that intelligent parking is successfully implemented based on car ID image capture to meet the need for managing and organizing car parking systems.

CHICSi--a compact ultra-high vacuum compatible detector system for nuclear reaction experiments at storage rings. III. readout system

Energy Technology Data Exchange (ETDEWEB)

Carlen, L.; Foerre, G.; Golubev, P.; Jakobsson, B. E-mail: bo.jakobsson@kosufy.lu.se; Kolozhvari, A.; Marciniewski, P.; Siwek, A.; Veldhuizen, E.J. van; Westerberg, L.; Whitlow, H.J.; Oestby, J.M

2004-01-11

(CHICSi) Celsius Heavy Ion Collaboration Si detector system is a high granularity, modular detector telescope array for operation around the cluster-jet target/circulating beam intersection of the CELSIUS storage ring at the The. Svedberg Laboratory in Uppsala, Sweden. It is able to provide identity and momentum vector of up to 100 charged particles and fragments from proton-nucleus and nucleus-nucleus collisions at intermediate energies, 50-1000A MeV. All detector telescopes as well as the major part of electronic readout system are placed inside the target chamber in ultra-high vacuum (UHV, 10{sup -9}-10{sup -7} Pa). This requires Very Large Scale Integrated (VLSI) microchip for the spectroscopic signal processing and the generation and transport of digital control signals. Eighteen telescopes, read out with chip-on-board technique by ceramics Mother Boards (MB) and corresponding 18 microchips are mounted on a 450x45 mm{sup 2} Grand Mother Board (GMB), processed on FR4 glass-fibre material. Each of these 28 GMB units contains a daisy-chain organisation of the VLSI chips and associated protection circuits. Analogue-to-digital conversion of the spectroscopic signals is performed on a board outside the chamber which is connected on one side to a power distribution board, directly attached to a UHV mounting flange, and on the other side to the VME-based data acquisition system (CHICSiDAQ). This in its turn is connected via a fibre-optic link to the general TSL acquisition system (SVEDAQ), and in this way data from auxiliary detector systems, read out in CAMAC mode, can be stored in coincidence with CHICSi data.

CHICSi--a compact ultra-high vacuum compatible detector system for nuclear reaction experiments at storage rings. III. readout system

International Nuclear Information System (INIS)

Carlen, L.; Foerre, G.; Golubev, P.; Jakobsson, B.; Kolozhvari, A.; Marciniewski, P.; Siwek, A.; Veldhuizen, E.J. van; Westerberg, L.; Whitlow, H.J.; Oestby, J.M.

2004-01-01

(CHICSi) Celsius Heavy Ion Collaboration Si detector system is a high granularity, modular detector telescope array for operation around the cluster-jet target/circulating beam intersection of the CELSIUS storage ring at the The. Svedberg Laboratory in Uppsala, Sweden. It is able to provide identity and momentum vector of up to 100 charged particles and fragments from proton-nucleus and nucleus-nucleus collisions at intermediate energies, 50-1000A MeV. All detector telescopes as well as the major part of electronic readout system are placed inside the target chamber in ultra-high vacuum (UHV, 10 -9 -10 -7 Pa). This requires Very Large Scale Integrated (VLSI) microchip for the spectroscopic signal processing and the generation and transport of digital control signals. Eighteen telescopes, read out with chip-on-board technique by ceramics Mother Boards (MB) and corresponding 18 microchips are mounted on a 450x45 mm 2 Grand Mother Board (GMB), processed on FR4 glass-fibre material. Each of these 28 GMB units contains a daisy-chain organisation of the VLSI chips and associated protection circuits. Analogue-to-digital conversion of the spectroscopic signals is performed on a board outside the chamber which is connected on one side to a power distribution board, directly attached to a UHV mounting flange, and on the other side to the VME-based data acquisition system (CHICSiDAQ). This in its turn is connected via a fibre-optic link to the general TSL acquisition system (SVEDAQ), and in this way data from auxiliary detector systems, read out in CAMAC mode, can be stored in coincidence with CHICSi data

Fusing Facial Features for Face Recognition

Directory of Open Access Journals (Sweden)

Jamal Ahmad Dargham

2012-06-01

Full Text Available Face recognition is an important biometric method because of its potential applications in many fields, such as access control, surveillance, and human-computer interaction. In this paper, a face recognition system that fuses the outputs of three face recognition systems based on Gabor jets is presented. The first system uses the magnitude, the second uses the phase, and the third uses the phase-weighted magnitude of the jets. The jets are generated from facial landmarks selected using three selection methods. It was found out that fusing the facial features gives better recognition rate than either facial feature used individually regardless of the landmark selection method.

Active feedback wide-field optical low-coherence interferometry for ultrahigh-speed three-dimensional morphometry

International Nuclear Information System (INIS)

Choi, Woo June; Choi, Hae Young; Lee, Byeong Ha; Na, Jihoon; Eom, Jonghyun

2010-01-01

A novel optical interferometric scheme for ultrahigh-speed three-dimensional morphometry is proposed. The system is based on wide-field optical coherence tomography (WF-OCT) but with optically chopped illumination. The chopping frequency is feedback-controlled to be always matched with the Doppler frequency of the OCT interferometer, which provides an efficient page-wide demodulation suitable for ultrahigh-speed volumetric imaging. To compensate the unwanted variation in the OCT Doppler frequency of the system, the illumination frequency is phase-locked with an auxiliary laser interferometer which shares the reference arm with the OCT interferometer. The two-dimensional (2D) interference signals projected on the 2D array pixels of a 200 Hz CCD are accumulated during one imaging frame of the CCD. Then, each pixel of the CCD demodulates the OCT signal automatically. Owing to the proposed active frequency-locked illumination scheme, the demodulation does not depend on the variation in the axial scanning speed. Volumetric topograms or/and tomograms of several samples were achieved and rendered with a sensitivity of 58 dB at an axial scan speed of 0.805 mm s −1

High-emulation mask recognition with high-resolution hyperspectral video capture system

Science.gov (United States)

Feng, Jiao; Fang, Xiaojing; Li, Shoufeng; Wang, Yongjin

2014-11-01

We present a method for distinguishing human face from high-emulation mask, which is increasingly used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral information of the observed face. Experiments show that mask made of silica gel has different spectral reflectance compared with the human skin. As multispectral image offers additional spectral information about physical characteristics, high-emulation mask can be easily recognized.

Status of Ultra-High Energy Cosmic Rays

CERN Multimedia

CERN. Geneva

2015-01-01

I will review the recent results on Ultra-High energy cosmic rays obtained by the Auger and Telescope Array Observatories, and discuss some of the Astrophysical scenarios that could account for them, a connection with LHC results  as well as the possible connections to neutrino and gamma ray observations.

Ultrahigh Field NMR and MRI: Science at a Crossroads Workshop Report

Energy Technology Data Exchange (ETDEWEB)

Polenova, Tatyana [Univ. of Delaware, Newark, DE (United States); Budinger, Thomas F. [Univ. of California, Berkeley, CA (United States)

2016-01-04

The workshop “Ultrahigh Field NMR and MRI: Science at Crossroads”, initiated by the scientific community and supported by the National Science Foundation, the Department of Energy, and the National Institutes of Health, took place on November 12-13, 2015, in Bethesda, MD, on the NIH campus. The meeting was held to assess the science drivers, technological challenges, prospects for achieving field strengths for NMR and MRI nearly double their current value, and strategies on how to provide ultrahigh field NMR/MRI capabilities to a national user community.

Micromotor endoscope catheter for in vivo, ultrahigh-resolution optical coherence tomography

Science.gov (United States)

Herz, P. R.; Chen, Y.; Aguirre, A. D.; Schneider, K.; Hsiung, P.; Fujimoto, J. G.; Madden, K.; Schmitt, J.; Goodnow, J.; Petersen, C.

2004-10-01

A distally actuated, rotational-scanning micromotor endoscope catheter probe is demonstrated for ultrahigh-resolution in vivo endoscopic optical coherence tomography (OCT) imaging. The probe permits focus adjustment for visualization of tissue morphology at varying depths with improved transverse resolution compared with standard OCT imaging probes. The distal actuation avoids nonuniform scanning motion artifacts that are present with other probe designs and can permit a wider range of imaging speeds. Ultrahigh-resolution endoscopic imaging is demonstrated in a rabbit with micromotor endoscope catheter probe promises to improve OCT imaging performance in future endoscopic imaging applications.

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

Science.gov (United States)

Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

2018-04-01

Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

Compact holographic optical neural network system for real-time pattern recognition

Science.gov (United States)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

A REVIEW: OPTICAL CHARACTER RECOGNITION

OpenAIRE

Swati Tomar*1 & Amit Kishore2

2018-01-01

This paper presents detailed review in the field of Optical Character Recognition. Various techniques are determine that have been proposed to realize the center of character recognition in an optical character recognition system. Even though, sufficient studies and papers are describes the techniques for converting textual content from a paper document into machine readable form. Optical character recognition is a process where the computer understands automatically the image of handwritten ...

Laser beam welding of new ultra-high strength and supra-ductile steels

OpenAIRE

Dahmen, M.

2015-01-01

Ultra-high strength and supra-ductile are entering fields of new applications. Those materials are excellent candidates for modern light-weight construction and functional integration. As ultra-high strength steels the stainless martensitic grade 1.4034 and the bainitic steel UNS 53835 are investigated. For the supra-ductile steels stand two high austenitic steels with 18 and 28 % manganese. As there are no processing windows an approach from the metallurgical base on is required. Adjusting t...

A Classification Framework for Large-Scale Face Recognition Systems

OpenAIRE

Zhou, Ziheng; Deravi, Farzin

2009-01-01

This paper presents a generic classification framework for large-scale face recognition systems. Within the framework, a data sampling strategy is proposed to tackle the data imbalance when image pairs are sampled from thousands of face images for preparing a training dataset. A modified kernel Fisher discriminant classifier is proposed to make it computationally feasible to train the kernel-based classification method using tens of thousands of training samples. The framework is tested in an...

Geometric scaling in ultrahigh energy neutrinos and nonlinear perturbative QCD

International Nuclear Information System (INIS)

Machado, Magno V.T.

2011-01-01

The ultrahigh energy neutrino cross section is a crucial ingredient in the calculation of the event rate in high energy neutrino telescopes. Currently there are several approaches which predict different behaviors for its magnitude for ultrahigh energies. In this contribution is presented a summary of current predictions based on the non-linear QCD evolution equations, the so-called perturbative saturation physics. In particular, predictions are shown based on the parton saturation approaches and the consequences of geometric scaling property at high energies are discussed. The scaling property allows an analytical computation of the neutrino scattering on nucleon/nucleus at high energies, providing a theoretical parameterization. (author)

Laser beam welding of new ultra-high strength and supra-ductile steels

Science.gov (United States)

Dahmen, Martin

2015-03-01

Ultra-high strength and supra-ductile are entering fields of new applications. Those materials are excellent candidates for modern light-weight construction and functional integration. As ultra-high strength steels the stainless martensitic grade 1.4034 and the bainitic steel UNS 53835 are investigated. For the supra-ductile steels stand two high austenitic steels with 18 and 28 % manganese. As there are no processing windows an approach from the metallurgical base on is required. Adjusting the weld microstructure the Q+P and the QT steels require weld heat treatment. The HSD steel is weldable without. Due to their applications the ultra-high strength steels are welded in as-rolled and strengthened condition. Also the reaction of the weld on hot stamping is reflected for the martensitic grades. The supra-ductile steels are welded as solution annealed and work hardened by 50%. The results show the general suitability for laser beam welding.

Enhancing thermal reliability of fiber-optic sensors for bio-inspired applications at ultra-high temperatures

Science.gov (United States)

Kang, Donghoon; Kim, Heon-Young; Kim, Dae-Hyun

2014-07-01

The rapid growth of bio-(inspired) sensors has led to an improvement in modern healthcare and human-robot systems in recent years. Higher levels of reliability and better flexibility, essential features of these sensors, are very much required in many application fields (e.g. applications at ultra-high temperatures). Fiber-optic sensors, and fiber Bragg grating (FBG) sensors in particular, are being widely studied as suitable sensors for improved structural health monitoring (SHM) due to their many merits. To enhance the thermal reliability of FBG sensors, thermal sensitivity, generally expressed as αf + ξf and considered a constant, should be investigated more precisely. For this purpose, the governing equation of FBG sensors is modified using differential derivatives between the wavelength shift and the temperature change in this study. Through a thermal test ranging from RT to 900 °C, the thermal sensitivity of FBG sensors is successfully examined and this guarantees thermal reliability of FBG sensors at ultra-high temperatures. In detail, αf + ξf has a non-linear dependence on temperature and varies from 6.0 × 10-6 °C-1 (20 °C) to 10.6 × 10-6 °C-1 (650 °C). Also, FBGs should be carefully used for applications at ultra-high temperatures due to signal disappearance near 900 °C.

Foundations for a syntatic pattern recognition system for genomic DNA sequences

Energy Technology Data Exchange (ETDEWEB)

Searles, D.B.

1993-03-01

The goal of the proposed work is the creation of a software system that will perform sophisticated pattern recognition and related functions at a level of abstraction and with expressive power beyond current general-purpose pattern-matching systems for biological sequences; and with a more uniform language, environment, and graphical user interface, and with greater flexibility, extensibility, embeddability, and ability to incorporate other algorithms, than current special-purpose analytic software.

Object Recognition System in Remote Controlled Weapon Station using SIFT and SURF Methods

Directory of Open Access Journals (Sweden)

Midriem Mirdanies

2013-12-01

Full Text Available Object recognition system using computer vision that is implemented on Remote Controlled Weapon Station (RCWS is discussed. This system will make it easier to identify and shoot targeted object automatically. Algorithm was created to recognize real time multiple objects using two methods i.e. Scale Invariant Feature Transform (SIFT and Speeded Up Robust Features (SURF combined with K-Nearest Neighbors (KNN and Random Sample Consensus (RANSAC for verification. The algorithm is designed to improve object detection to be more robust and to minimize the processing time required. Objects are registered on the system consisting of the armored personnel carrier, tanks, bus, sedan, big foot, and police jeep. In addition, object selection can use mouse to shoot another object that has not been registered on the system. Kinect™ is used to capture RGB images and to find the coordinates x, y, and z of the object. The programming language used is C with visual studio IDE 2010 and opencv libraries. Object recognition program is divided into three parts: 1 reading image from kinect™ and simulation results, 2 object recognition process, and 3 transfer of the object data to the ballistic computer. Communication between programs is performed using shared memory. The detected object data is sent to the ballistic computer via Local Area Network (LAN using winsock for ballistic calculation, and then the motor control system moves the direction of the weapon model to the desired object. The experimental results show that the SIFT method is more suitable because more accurate and faster than SURF with the average processing time to detect one object is 430.2 ms, two object is 618.4 ms, three objects is 682.4 ms, and four objects is 756.2 ms. Object recognition program is able to recognize multi-objects and the data of the identified object can be processed by the ballistic computer in realtime.

Soliton-based ultra-high speed optical communications

Indian Academy of Sciences (India)

All these facts are the outcome of research on optical solitons in fibers in spite of the fact that the commonly used RZ format is not always called a soliton format. The overview presented here attempts to incorporate the role of soliton-based communications research in present day ultra-high speed communications.

Proton-proton elastic scattering at ultrahigh energies

Energy Technology Data Exchange (ETDEWEB)

Saleem, M.; Shaukat, M.A.; Fazal-e-Aleem (University of the Punjab, Lahore (Pakistan). Dept. of Physics)

1981-05-30

The authors use a geometrical model of high-energy pp elastic scattering as proposed by Chou and Yong to analyse experimental data available at present and consider the predictions of the dipole pomeron model for pp elastic scattering at ultrahigh energies. Theoretical results for differential cross sections are compared with experimental data.

Theoretical Aspects of the Patterns Recognition Statistical Theory Used for Developing the Diagnosis Algorithms for Complicated Technical Systems

Science.gov (United States)

Obozov, A. A.; Serpik, I. N.; Mihalchenko, G. S.; Fedyaeva, G. A.

2017-01-01

In the article, the problem of application of the pattern recognition (a relatively young area of engineering cybernetics) for analysis of complicated technical systems is examined. It is shown that the application of a statistical approach for hard distinguishable situations could be the most effective. The different recognition algorithms are based on Bayes approach, which estimates posteriori probabilities of a certain event and an assumed error. Application of the statistical approach to pattern recognition is possible for solving the problem of technical diagnosis complicated systems and particularly big powered marine diesel engines.

A field study of the accuracy and reliability of a biometric iris recognition system.

Science.gov (United States)

Latman, Neal S; Herb, Emily

2013-06-01

The iris of the eye appears to satisfy the criteria for a good anatomical characteristic for use in a biometric system. The purpose of this study was to evaluate a biometric iris recognition system: Mobile-Eyes™. The enrollment, verification, and identification applications were evaluated in a field study for accuracy and reliability using both irises of 277 subjects. Independent variables included a wide range of subject demographics, ambient light, and ambient temperature. A sub-set of 35 subjects had alcohol-induced nystagmus. There were 2710 identification and verification attempts, which resulted in 1,501,340 and 5540 iris comparisons respectively. In this study, the system successfully enrolled all subjects on the first attempt. All 277 subjects were successfully verified and identified on the first day of enrollment. None of the current or prior eye conditions prevented enrollment, verification, or identification. All 35 subjects with alcohol-induced nystagmus were successfully verified and identified. There were no false verifications or false identifications. Two conditions were identified that potentially could circumvent the use of iris recognitions systems in general. The Mobile-Eyes™ iris recognition system exhibited accurate and reliable enrollment, verification, and identification applications in this study. It may have special applications in subjects with nystagmus. Copyright © 2012 Forensic Science Society. Published by Elsevier Ireland Ltd. All rights reserved.

Cortico-Striatal GABAergic and Glutamatergic Dysregulations in Subjects at Ultra-High Risk for Psychosis Investigated with Proton Magnetic Resonance Spectroscopy

Science.gov (United States)

Reyes-Madrigal, Francisco; Mao, Xiangling; León-Ortiz, Pablo; Rodríguez-Mayoral, Oscar; Solís-Vivanco, Rodolfo; Favila, Rafael; Graff-Guerrero, Ariel; Shungu, Dikoma C.

2016-01-01

Background: Dysregulations of the major inhibitory and excitatory amino neurotransmitter systems of γ-aminobutyric acid and glutamate, respectively, have been described in patients with schizophrenia. However, it is unclear whether these abnormalities are present in subjects at ultra-high risk for psychosis. Methods: Twenty-three antipsychotic naïve subjects at ultra-high risk and 24 healthy control subjects, matched for age, sex, handedness, cigarette smoking, and parental education, underwent proton magnetic resonance spectroscopy scans in the dorsal caudate bilaterally and the medial prefrontal cortex at 3T. Levels of γ-aminobutyric acid and of the combined resonance of glutamate and glutamine (Glx) were obtained using the standard J-editing technique and expressed as peak area ratios relative to the synchronously acquired unsuppressed voxel water signal. Results: Higher levels of γ-aminobutyric acid (P<.001) and Glx (P=.007) were found in the dorsal caudate of the subjects at ultra-high risk than in the healthy controls. In the medial prefrontal cortex, likewise, both γ-aminobutyric acid (P=.03) and Glx (P=.006) levels were higher in the ultra-high risk group than in the healthy controls. No group differences were found for any of the other metabolites (N-acetylaspartate, total choline, or total creatine) in the 2 regions of interest. Conclusions: This study presents the first evidence of abnormal elevations, in subjects at ultra-high risk, of γ-aminobutyric acid and Glx in 2 brain regions that have been implicated in the pathophysiology of psychosis, warranting longitudinal studies to assess whether these neurotransmitter abnormalities can serve as noninvasive biomarkers of conversion risk to psychosis as well as of illness progression and treatment response. PMID:26364273

Ultrahigh Sensitivity Piezoresistive Pressure Sensors for Detection of Tiny Pressure.

Science.gov (United States)

Li, Hongwei; Wu, Kunjie; Xu, Zeyang; Wang, Zhongwu; Meng, Yancheng; Li, Liqiang

2018-05-31

High sensitivity pressure sensors are crucial for the ultra-sensitive touch technology and E-skin, especially at the tiny pressure range below 100 Pa. However, it is highly challenging to substantially promote sensitivity beyond the current level at several to two hundred kPa -1 , and to improve the detection limit lower than 0.1 Pa, which is significant for the development of pressure sensors toward ultrasensitive and highly precise detection. Here, we develop an efficient strategy to greatly improve the sensitivity near to 2000 kPa -1 by using short channel coplanar device structure and sharp microstructure, which is systematically proposed for the first time and rationalized by the mathematic calculation and analysis. Significantly, benefiting from the ultrahigh sensitivity, the detection limit is improved to be as small as 0.075 Pa. The sensitivity and detection limit are both superior to the current levels, and far surpass the function of human skin. Furthermore, the sensor shows fast response time (50 μs), excellent reproducibility and stability, and low power consumption. Remarkably, the sensor shows excellent detection capacity in the tiny pressure range including LED switching with a pressure of 7 Pa, ringtone (2-20 Pa) recognition, and ultrasensitive (0.1 Pa) electronic glove. This work represents a performance and strategic progress in the field of pressure sensing.

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...

Development of remote handling system based on 3-D shape recognition technique

International Nuclear Information System (INIS)

Tomizuka, Chiaki; Takeuchi, Yutaka

2006-01-01

In a nuclear facility, the maintenance and repair activities must be done remotely in a radioactive environment. Fuji Electric Systems Co., Ltd. has developed a remote handling system based on 3-D recognition technique. The system recognizes the pose and position of the target to manipulate, and visualizes the scene with the target in 3-D, enabling an operator to handle it easily. This paper introduces the concept and the key features of this system. (author)

Scaling violations at ultra-high energies

International Nuclear Information System (INIS)

Tung, W.K.

1979-01-01

The paper discusses some of the features of high energy lepton-hadron scattering, including the observed (Bjorken) scaling behavior. The cross-sections where all hadron final states are summed over, are examined and the general formulas for the differential cross-section are examined. The subjects of scaling, breaking and phenomenological consequences are studied, and a list of what ultra-high energy neutrino physics can teach QCD is given

Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

Science.gov (United States)

Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

2017-03-01

Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

Bridging the gap between system and cell: The role of ultra-high field MRI in human neuroscience.

Science.gov (United States)

Turner, Robert; De Haan, Daniel

2017-01-01

The volume of published research at the levels of systems and cellular neuroscience continues to increase at an accelerating rate. At the same time, progress in psychiatric medicine has stagnated and scientific confidence in cognitive psychology research is under threat due to careless analysis methods and underpowered experiments. With the advent of ultra-high field MRI, with submillimeter image voxels, imaging neuroscience holds the potential to bridge the cellular and systems levels. Use of these accurate and precisely localized quantitative measures of brain activity may go far in providing more secure foundations for psychology, and hence for more appropriate treatment and management of psychiatric illness. However, fundamental issues regarding the construction of testable mechanistic models using imaging data require careful consideration. This chapter summarizes the characteristics of acceptable models of brain function and provides concise descriptions of the relevant types of neuroimaging data that have recently become available. Approaches to data-driven experiments and analyses are described that may lead to more realistic conceptions of the competences of neural assemblages, as they vary across the brain's complex neuroanatomy. © 2017 Elsevier B.V. All rights reserved.

An automatic speech recognition system with speaker-independent identification support

Science.gov (United States)

Caranica, Alexandru; Burileanu, Corneliu

2015-02-01

The novelty of this work relies on the application of an open source research software toolkit (CMU Sphinx) to train, build and evaluate a speech recognition system, with speaker-independent support, for voice-controlled hardware applications. Moreover, we propose to use the trained acoustic model to successfully decode offline voice commands on embedded hardware, such as an ARMv6 low-cost SoC, Raspberry PI. This type of single-board computer, mainly used for educational and research activities, can serve as a proof-of-concept software and hardware stack for low cost voice automation systems.

Development of a System for Automatic Recognition of Speech

Directory of Open Access Journals (Sweden)

Roman Jarina

2003-01-01

Full Text Available The article gives a review of a research on processing and automatic recognition of speech signals (ARR at the Department of Telecommunications of the Faculty of Electrical Engineering, University of iilina. On-going research is oriented to speech parametrization using 2-dimensional cepstral analysis, and to an application of HMMs and neural networks for speech recognition in Slovak language. The article summarizes achieved results and outlines future orientation of our research in automatic speech recognition.

Ultrahigh Sensitive and Flexible Magnetoelectronics with Magnetic Nanocomposites: Toward an Additional Perception of Artificial Intelligence.

Science.gov (United States)

Cai, Shu-Yi; Chang, Cheng-Han; Lin, Hung-I; Huang, Yuan-Fu; Lin, Wei-Ju; Lin, Shih-Yao; Liou, Yi-Rou; Shen, Tien-Lin; Huang, Yen-Hsiang; Tsao, Po-Wei; Tzou, Chen-Yang; Liao, Yu-Ming; Chen, Yang-Fang

2018-05-23

In recent years, flexible magnetoelectronics has attracted a great attention for its intriguing functionalities and potential applications, such as healthcare, memory, soft robots, navigation, and touchless human-machine interaction systems. Here, we provide the first attempt to demonstrate a new type of magneto-piezoresistance device, which possesses an ultrahigh sensitivity with several orders of resistance change under an external magnetic field (100 mT). In our device, Fe-Ni alloy powders are embedded in the silver nanowire-coated micropyramid polydimethylsiloxane films. Our devices can not only serve as an on/off switch but also act as a sensor that can detect different magnetic fields because of its ultrahigh sensitivity, which is very useful for the application in analog signal communication. Moreover, our devices contain several key features, including large-area and easy fabrication processes, fast response time, low working voltage, low power consumption, excellent flexibility, and admirable compatibility onto a freeform surface, which are the critical criteria for the future development of touchless human-machine interaction systems. On the basis of all of these unique characteristics, we have demonstrated a nontouch piano keyboard, instantaneous magnetic field visualization, and autonomous power system, making our new devices be integrable with magnetic field and enable to be implemented into our daily life applications with unfamiliar human senses. Our approach therefore paves a useful route for the development of wearable electronics and intelligent systems.

Real-time image restoration for iris recognition systems.

Science.gov (United States)

Kang, Byung Jun; Park, Kang Ryoung

2007-12-01

In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower recognition performance, since iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time iris image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: 1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input iris images; 2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; 3) because the PSF parameter can be obtained by using a predetermined equation, iris image restoration can be done in real-time; 4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and 5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of image blurring. Experimental results showed that iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous iris-restoration methods.

Authentication: From Passwords to Biometrics: An implementation of a speaker recognition system on Android

OpenAIRE

Heimark, Erlend

2012-01-01

We implement a biometric authentication system on the Android platform, which is based on text-dependent speaker recognition. The Android version used in the application is Android 4.0. The application makes use of the Modular Audio Recognition Framework, from which many of the algorithms are adapted in the processes of preprocessing and feature extraction. In addition, we employ the Dynamic Time Warping (DTW) algorithm for the comparison of different voice features. A training procedure is i...

Testing and Modeling Ultra-High Temperature Ceramic (UHTC) Materials For Hypersonic Flight

Science.gov (United States)

2011-11-30

Ridge, D. G. Fletcher, C. O. Asma , O. Chazot, and J. Thömel, “Oxidation of ZrB2-SiC Ultra-High Temperature Ceramic Composites in Dissociated Air...Fletcher, C. O. Asma , “Characterization of ZrB2-SiC Ceramics Tested by Plasma Stream Oxidation,” poster, 32 th International Conference...Fahrenholtz, W.G., Hilmas, G.E., Zhu, S.M., Ridge, J., Fletcher, D.G., Asma , C.O., and Thomel, J., "Oxidation of ZrB2-SiC Ultrahigh-Temperature

Ultrahigh temperature deformation microstructures in felsic granulites of the Napier Complex, Antarctica

DEFF Research Database (Denmark)

Lund, Majbritt Deichgræber; Piazolo, Sandra; Harley, Simon L

2006-01-01

Detailed electron microscope and microstructural analysis of two ultrahigh temperature felsic granulites from Tonagh Island, Napier Complex, Antarctica show deformation microstructures produced at ∼1000 °C at 8-10 kbar. High temperature orthopyroxene (Al ∼7 wt.% and ∼11 wt.%), exhibits crystallog......Detailed electron microscope and microstructural analysis of two ultrahigh temperature felsic granulites from Tonagh Island, Napier Complex, Antarctica show deformation microstructures produced at ∼1000 °C at 8-10 kbar. High temperature orthopyroxene (Al ∼7 wt.% and ∼11 wt.%), exhibits...

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.

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.

An improved single cell ultrahigh throughput screening method based on in vitro compartmentalization.

Directory of Open Access Journals (Sweden)

Fuqiang Ma

Full Text Available High-throughput screening is a key technique in discovery and engineering of enzymes. In vitro compartmentalization based fluorescence-activated cell sorting (IVC-FACS has recently emerged as a powerful tool for ultrahigh-throughput screening of biocatalysts. However, the accuracy of current IVC-FACS assays is severely limited by the wide polydispersity of micro-reactors generated by homogenizing. Here, an improved protocol based on membrane-extrusion technique was reported to generate the micro-reactors in a more uniform manner. This crucial improvement enables ultrahigh-throughput screening of enzymatic activity at a speed of >10⁸ clones/day with an accuracy that could discriminate as low as two-fold differences in enzymatic activity inside the micro-reactors, which is higher than similar IVC-FACS systems ever have reported. The enzymatic reaction in the micro-reactors has very similar kinetic behavior compared to the bulk reaction system and shows wide dynamic range. By using the modified IVC-FACS, E. coli cells with esterase activity could be enriched 330-fold from large excesses of background cells through a single round of sorting. The utility of this new IVC-FACS system was further illustrated by the directed evolution of thermophilic esterase AFEST. The catalytic activity of the very efficient esterase was further improved by ∼2-fold, resulting in several improved mutants with k(cat/K(M values approaching the diffusion-limited efficiency of ∼10⁸ M⁻¹s⁻¹.

Point spread function engineering for iris recognition system design.

Science.gov (United States)

Ashok, Amit; Neifeld, Mark A

2010-04-01

Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

Markov Models for Handwriting Recognition

CERN Document Server

Plotz, Thomas

2011-01-01

Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

Experimental Investigation of Magnetic Superconducting and other Phase Transitions in Novel f-Electron Materials at Ultra-high Pressures using Designer Diamond Anvils

International Nuclear Information System (INIS)

Maple, M. Brian; Jeffries, Jason R.; Ho, Pei-Chun; Butch, Nicholas P.

2004-01-01

Pressure is often used as a controlled parameter for the investigation of condensed matter systems. In particular, pressure experiments can provide valuable information into the nature of superconductivity, magnetism, and the coexistence of these two phenomena. Some f-electron, heavy-fermion materials display interesting and novel behavior at moderately low pressures achievable with conventional experimental techniques; however, a growing number of condensed matter systems require ultrahigh pressure techniques, techniques that generate significantly higher pressures than conventional methods, to sufficiently explore their important properties. To that end, we have been funded to develop an ultrahigh pressure diamond anvil cell facility at the University of California, San Diego (UCSD) in order to investigate superconductivity, magnetism, non-Fermi liquid behavior, and other phenomena. Our goals for the first year of this grant were as follows: (a) set up and test a suitable refrigerator; (b) set up a laser and spectrometer fluorescence system to determine the pressure within the diamond anvil cell; (c) perform initial resistivity measurements at moderate pressures from room temperature to liquid helium temperatures (∼1K); (d) investigate f-electron materials within our current pressure capabilities to find candidate materials for high-pressure studies. During the past year, we have ordered almost all the components required to set up a diamond anvil cell facility at UCSD, we have received and implemented many of the components that have been ordered, we have performed low pressure research on several materials, and we have engaged in a collaborative effort with Sam Weir at Lawrence Livermore National Lab (LLNL) to investigate Au4V under ultrahigh pressure in a designer diamond anvil cell (dDAC). This report serves to highlight the progress we have made towards developing an ultrahigh pressure research facility at UCSD, the research performed in the past year, as

Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

Science.gov (United States)

Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

2016-09-01

Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Data structures, computer graphics, and pattern recognition

CERN Document Server

Klinger, A; Kunii, T L

1977-01-01

Data Structures, Computer Graphics, and Pattern Recognition focuses on the computer graphics and pattern recognition applications of data structures methodology.This book presents design related principles and research aspects of the computer graphics, system design, data management, and pattern recognition tasks. The topics include the data structure design, concise structuring of geometric data for computer aided design, and data structures for pattern recognition algorithms. The survey of data structures for computer graphics systems, application of relational data structures in computer gr

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors

Directory of Open Access Journals (Sweden)

Tuyen Danh Pham

2015-07-01

Full Text Available Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

Nonintrusive Finger-Vein Recognition System Using NIR Image Sensor and Accuracy Analyses According to Various Factors.

Science.gov (United States)

Pham, Tuyen Danh; Park, Young Ho; Nguyen, Dat Tien; Kwon, Seung Yong; Park, Kang Ryoung

2015-07-13

Biometrics is a technology that enables an individual person to be identified based on human physiological and behavioral characteristics. Among biometrics technologies, face recognition has been widely used because of its advantages in terms of convenience and non-contact operation. However, its performance is affected by factors such as variation in the illumination, facial expression, and head pose. Therefore, fingerprint and iris recognitions are preferred alternatives. However, the performance of the former can be adversely affected by the skin condition, including scarring and dryness. In addition, the latter has the disadvantages of high cost, large system size, and inconvenience to the user, who has to align their eyes with the iris camera. In an attempt to overcome these problems, finger-vein recognition has been vigorously researched, but an analysis of its accuracies according to various factors has not received much attention. Therefore, we propose a nonintrusive finger-vein recognition system using a near infrared (NIR) image sensor and analyze its accuracies considering various factors. The experimental results obtained with three databases showed that our system can be operated in real applications with high accuracy; and the dissimilarity of the finger-veins of different people is larger than that of the finger types and hands.

Heat Transfer and Failure Mode Analyses of Ultrahigh-Temperature Ceramic Thermal Protection System of Hypersonic Vehicles

Directory of Open Access Journals (Sweden)

Tianbao Cheng

2014-01-01

Full Text Available The transient temperature distribution of the ultrahigh-temperature ceramic (UHTC thermal protection system (TPS of hypersonic vehicles is calculated using finite volume method. Convective cooling enables a balance of heat increment and loss to be achieved. The temperature in the UHTC plate at the balance is approximately proportional to the surface heat flux and is approximately inversely proportional to the convective heat transfer coefficient. The failure modes of the UHTCs are presented by investigating the thermal stress field of the UHTC TPS under different thermal environments. The UHTCs which act as the thermal protection materials of hypersonic vehicles can fail because of the tensile stress at the lower surface, an area above the middle plane, and the upper surface as well as because of the compressive stress at the upper surface. However, the area between the lower surface and the middle plane and a small area near the upper surface are relatively safe. Neither the compressive stress nor the tensile stress will cause failure of these areas.

Efficient Ultra-High Speed Communication with Simultaneous Phase and Amplitude Regenerative Sampling (SPARS)

Science.gov (United States)

Carlowitz, Christian; Girg, Thomas; Ghaleb, Hatem; Du, Xuan-Quang

2017-09-01

For ultra-high speed communication systems at high center frequencies above 100 GHz, we propose a disruptive change in system architecture to address major issues regarding amplifier chains with a large number of amplifier stages. They cause a high noise figure and high power consumption when operating close to the frequency limits of the underlying semiconductor technologies. Instead of scaling a classic homodyne transceiver system, we employ repeated amplification in single-stage amplifiers through positive feedback as well as synthesizer-free self-mixing demodulation at the receiver to simplify the system architecture notably. Since the amplitude and phase information for the emerging oscillation is defined by the input signal and the oscillator is only turned on for a very short time, it can be left unstabilized and thus come without a PLL. As soon as gain is no longer the most prominent issue, relaxed requirements for all the other major components allow reconsidering their implementation concepts to achieve further improvements compared to classic systems. This paper provides the first comprehensive overview of all major design aspects that need to be addressed upon realizing a SPARS-based transceiver. At system level, we show how to achieve high data rates and a noise performance comparable to classic systems, backed by scaled demonstrator experiments. Regarding the transmitter, design considerations for efficient quadrature modulation are discussed. For the frontend components that replace PA and LNA amplifier chains, implementation techniques for regenerative sampling circuits based on super-regenerative oscillators are presented. Finally, an analog-to-digital converter with outstanding performance and complete interfaces both to the analog baseband as well as to the digital side completes the set of building blocks for efficient ultra-high speed communication.

Study on reactor building structure using ultrahigh strength materials - Part 9: Summary of the study

International Nuclear Information System (INIS)

Tanaka, H.; Odajima, M.; Irino, K.; Hashiba, T.

1993-01-01

Considerations for longevity of nuclear facilities and ease of decommissioning are of great importance for future nuclear power plants. To this end, a concept of an optimal structural concept for nuclear reactor buildings has been studied: the main feature of this concept is to utilize large-sized, light weight prefabricated members with ultrahigh strength materials. The following two items have been selected to study the prospective structure: (1) Applicability of ultrahigh strength materials for reinforced concrete shear walls (2) Construction using large sized prefabricated members As the first step (1), material and structural tests using ultrahigh strength materials, and the subsequent analysis of those tests for reinforced concrete shear walls, has been conducted. The positive results of this study show a bright future for the use of ultrahigh strength materials for the reinforced concrete shear walls of nuclear reactor buildings. As the second step (2), tests on a mixed structure with precasted members have been conducted. Our results positively suggest the use of these materials and methods to improve prospective nuclear power plants. (author)

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

Science.gov (United States)

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

2014-11-01

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

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

Science.gov (United States)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase

Enhancing thermal reliability of fiber-optic sensors for bio-inspired applications at ultra-high temperatures

International Nuclear Information System (INIS)

Kang, Donghoon; Kim, Heon-Young; Kim, Dae-Hyun

2014-01-01

The rapid growth of bio-(inspired) sensors has led to an improvement in modern healthcare and human–robot systems in recent years. Higher levels of reliability and better flexibility, essential features of these sensors, are very much required in many application fields (e.g. applications at ultra-high temperatures). Fiber-optic sensors, and fiber Bragg grating (FBG) sensors in particular, are being widely studied as suitable sensors for improved structural health monitoring (SHM) due to their many merits. To enhance the thermal reliability of FBG sensors, thermal sensitivity, generally expressed as α f + ξ f and considered a constant, should be investigated more precisely. For this purpose, the governing equation of FBG sensors is modified using differential derivatives between the wavelength shift and the temperature change in this study. Through a thermal test ranging from RT to 900 °C, the thermal sensitivity of FBG sensors is successfully examined and this guarantees thermal reliability of FBG sensors at ultra-high temperatures. In detail, α f + ξ f has a non-linear dependence on temperature and varies from 6.0 × 10 −6  °C −1 (20 °C) to 10.6 × 10 −6  °C −1 (650 °C). Also, FBGs should be carefully used for applications at ultra-high temperatures due to signal disappearance near 900 °C. (paper)

Improved RGB-D-T based Face Recognition

DEFF Research Database (Denmark)

Oliu Simon, Marc; Corneanu, Ciprian; Nasrollahi, Kamal

2016-01-01

years. At the same time a multimodal facial recognition is a promising approach. This paper combines the latest successes in both directions by applying deep learning Convolutional Neural Networks (CNN) to the multimodal RGB-D-T based facial recognition problem outperforming previously published results......Reliable facial recognition systems are of crucial importance in various applications from entertainment to security. Thanks to the deep-learning concepts introduced in the field, a significant improvement in the performance of the unimodal facial recognition systems has been observed in the recent...

Historical evolution toward achieving ultrahigh vacuum in JEOL electron microscopes

CERN Document Server

Yoshimura, Nagamitsu

2014-01-01

This book describes the developmental history of the vacuum system of the transmission electron microscope (TEM) at the Japan Electron Optics Laboratory (JEOL) from its inception to its use in today’s high-technology microscopes. The author and his colleagues were engaged in developing vacuum technology for electron microscopes (JEM series) at JEOL for many years. This volume presents a summary and explanation of their work and the technology that makes possible a clean ultrahigh vacuum. The typical users of the TEM are top-level researchers working at the frontiers of new materials or with new biological specimens. They often use the TEM under extremely severe conditions, with problems sometimes occurring in the vacuum system of the microscopes. JEOL engineers then must work as quickly as possible to improve the vacuum evacuation system so as to prevent the recurrence of such problems. Among the wealth of explanatory material in this book are examples of users’ reports of problems in the vacuum system of...

A neural network based artificial vision system for licence plate recognition.

Science.gov (United States)

Draghici, S

1997-02-01

This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

[Reparative Osteogenesis and Angiogenesis in Low Intensity Electromagnetic Radiation of Ultra-High Frequency].

Science.gov (United States)

Iryanov, Y M; Kiryanov, N A

2015-01-01

Non-drug correction of reparative bone tissue regeneration in different pathological states - one of the most actual problems of modern medicine. Our aim was to conduct morphological analysis of the influence of electromagnetic radiation of ultra-high frequency and low intensity on reparative osteogenesis and angiogenesis in fracture treatment under transosseous osteosynthesis. A controlled nonrandomized study was carried out. In the experiment conducted on rats we modeled tibial fracture with reposition and fixation of the bone fragments both in control and experimental groups. In the animals of the experimental group the fracture zone was exposed to low intensity electromagnetic radiation of ultra-high frequency. Exposure simulation was performed in the control group. The operated bones were examined using radiography, light and electronic microscopy, X-ray electronic probe microanalysis. It has been established that electromagnetic radiation of ultra-high frequency sessions in fracture treatment stimulate secretory activity and degranulation of mast cells, produce microcirculatory bed vascular permeability increase, endotheliocyte migration phenotype expression, provide endovascular endothelial outgrowth formation, activate reparative osteogenesis and angiogenesis while fracture reparation becomes the one of the primary type. The full periosteal, intermediary and intraosteal bone union was defined in 28 days. Among the therapeutic benefits of electromagnetic radiation of ultra-high frequency in fracture treatment we can detect mast cell secretorv activity stimulation and endovascular anziozenesis activation.

Neuropeptide S interacts with the basolateral amygdala noradrenergic system in facilitating object recognition memory consolidation.

Science.gov (United States)

Han, Ren-Wen; Xu, Hong-Jiao; Zhang, Rui-San; Wang, Pei; Chang, Min; Peng, Ya-Li; Deng, Ke-Yu; Wang, Rui

2014-01-01

The noradrenergic activity in the basolateral amygdala (BLA) was reported to be involved in the regulation of object recognition memory. As the BLA expresses high density of receptors for Neuropeptide S (NPS), we investigated whether the BLA is involved in mediating NPS's effects on object recognition memory consolidation and whether such effects require noradrenergic activity. Intracerebroventricular infusion of NPS (1nmol) post training facilitated 24-h memory in a mouse novel object recognition task. The memory-enhancing effect of NPS could be blocked by the β-adrenoceptor antagonist propranolol. Furthermore, post-training intra-BLA infusions of NPS (0.5nmol/side) improved 24-h memory for objects, which was impaired by co-administration of propranolol (0.5μg/side). Taken together, these results indicate that NPS interacts with the BLA noradrenergic system in improving object recognition memory during consolidation. Copyright © 2013 Elsevier Inc. All rights reserved.

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

OpenAIRE

Yadav, Poonam

2015-01-01

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

NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment.

Science.gov (United States)

Mezgec, Simon; Koroušić Seljak, Barbara

2017-06-27

Automatic food image recognition systems are alleviating the process of food-intake estimation and dietary assessment. However, due to the nature of food images, their recognition is a particularly challenging task, which is why traditional approaches in the field have achieved a low classification accuracy. Deep neural networks have outperformed such solutions, and we present a novel approach to the problem of food and drink image detection and recognition that uses a newly-defined deep convolutional neural network architecture, called NutriNet. This architecture was tuned on a recognition dataset containing 225,953 512 × 512 pixel images of 520 different food and drink items from a broad spectrum of food groups, on which we achieved a classification accuracy of 86 . 72 % , along with an accuracy of 94 . 47 % on a detection dataset containing 130 , 517 images. We also performed a real-world test on a dataset of self-acquired images, combined with images from Parkinson's disease patients, all taken using a smartphone camera, achieving a top-five accuracy of 55 % , which is an encouraging result for real-world images. Additionally, we tested NutriNet on the University of Milano-Bicocca 2016 (UNIMIB2016) food image dataset, on which we improved upon the provided baseline recognition result. An online training component was implemented to continually fine-tune the food and drink recognition model on new images. The model is being used in practice as part of a mobile app for the dietary assessment of Parkinson's disease patients.

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.

Simple test system for single molecule recognition force microscopy

International Nuclear Information System (INIS)

Riener, Christian K.; Stroh, Cordula M.; Ebner, Andreas; Klampfl, Christian; Gall, Alex A.; Romanin, Christoph; Lyubchenko, Yuri L.; Hinterdorfer, Peter; Gruber, Hermann J.

2003-01-01

We have established an easy-to-use test system for detecting receptor-ligand interactions on the single molecule level using atomic force microscopy (AFM). For this, avidin-biotin, probably the best characterized receptor-ligand pair, was chosen. AFM sensors were prepared containing tethered biotin molecules at sufficiently low surface concentrations appropriate for single molecule studies. A biotin tether, consisting of a 6 nm poly(ethylene glycol) (PEG) chain and a functional succinimide group at the other end, was newly synthesized and covalently coupled to amine-functionalized AFM tips. In particular, PEG 800 diamine was glutarylated, the mono-adduct NH 2 -PEG-COOH was isolated by ion exchange chromatography and reacted with biotin succinimidylester to give biotin-PEG-COOH which was then activated as N-hydroxysuccinimide (NHS) ester to give the biotin-PEG-NHS conjugate which was coupled to the aminofunctionalized AFM tip. The motional freedom provided by PEG allows for free rotation of the biotin molecule on the AFM sensor and for specific binding to avidin which had been adsorbed to mica surfaces via electrostatic interactions. Specific avidin-biotin recognition events were discriminated from nonspecific tip-mica adhesion by their typical unbinding force (∼40 pN at 1.4 nN/s loading rate), unbinding length (<13 nm), the characteristic nonlinear force-distance relation of the PEG linker, and by specific block with excess of free d-biotin. The convenience of the test system allowed to evaluate, and compare, different methods and conditions of tip aminofunctionalization with respect to specific binding and nonspecific adhesion. It is concluded that this system is well suited as calibration or start-up kit for single molecule recognition force microscopy

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

Directory of Open Access Journals (Sweden)

Hongqiang Li

2016-10-01

Full Text Available Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

Social cognition in patients at ultra-high risk for psychosis: What is the relation to social skills and functioning?

Science.gov (United States)

Glenthøj, Louise B; Fagerlund, Birgitte; Hjorthøj, Carsten; Jepsen, Jens R M; Bak, Nikolaj; Kristensen, Tina D; Wenneberg, Christina; Krakauer, Kristine; Roberts, David L; Nordentoft, Merete

2016-09-01

Patients at ultra-high risk (UHR) for psychosis show significant impairments in functioning. It is essential to determine which factors influence functioning, as it may have implications for intervention strategies. This study examined whether social cognitive abilities and clinical symptoms are associated with functioning and social skills. The study included 65 UHR patients and 30 healthy controls. Social cognitive function, social skills, and a broad range of functioning measures were assessed. The UHR patients demonstrated significant decrements on The Awareness of Social Inferences Task total score (p = .046, d  = .51), and on the CANTAB emotion recognition task total percent correct (p = .023, d  = .54) displaying particular difficulties in negative affect recognition. The patients exhibited significant impairments in social skills measured with the High Risk Social Challenge (p˂.001, d  = 1.05). Aspects of emotion recognition were associated with role functioning and social skill performance. The level of attributional bias was associated with overall functioning, and theory of mind ability was associated with self-reported functioning. Negative symptoms were associated with all measures of functioning (p ≤ .05). Significant impairments in social cognition and social skills were found in UHR patients. The patients' social cognitive function was associated with overall functioning and social skills. Negative symptoms appear to play an important role for functioning. Research is needed to investigate how the relations between social cognition, social skills and functioning develop from the UHR state to the stage of manifest illness. Research into how deficits in social cognition and social skills can be ameliorated in UHR patients is warranted.

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

Sign Language Recognition System using Neural Network for Digital Hardware Implementation

International Nuclear Information System (INIS)

Vargas, Lorena P; Barba, Leiner; Torres, C O; Mattos, L

2011-01-01

This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

Individual recognition of social rank and social memory performance depends on a functional circadian system.

Science.gov (United States)

Müller, L; Weinert, D

2016-11-01

In a natural environment, social abilities of an animal are important for its survival. Particularly, it must recognize its own social rank and the social rank of a conspecific and have a good social memory. While the role of the circadian system for object and spatial recognition and memory is well known, the impact of the social rank and circadian disruptions on social recognition and memory were not investigated so far. In the present study, individual recognition of social rank and social memory performance of Djungarian hamsters revealing different circadian phenotypes were investigated. Wild type (WT) animals show a clear and well-synchronized daily activity rhythm, whereas in arrhythmic (AR) hamsters, the suprachiasmatic nuclei (SCN) do not generate a circadian signal. The aim of the study was to investigate putative consequences of these deteriorations in the circadian system for animalś cognitive abilities. Hamsters were bred and kept under standardized housing conditions with food and water ad libitum and a 14l/10 D lighting regimen. Experimental animals were assigned to different groups (WT and AR) according to their activity pattern obtained by means of infrared motion sensors. Before the experiments, the animals were given to develop a dominant-subordinate relationship in a dyadic encounter. Experiment 1 dealt with individual recognition of social rank. Subordinate and dominant hamsters were tested in an open arena for their behavioral responses towards a familiar (known from the agonistic encounters) or an unfamiliar hamster (from another agonistic encounter) which had the same or an opposite social rank. The investigation time depended on the social rank of the WT subject hamster and its familiarity with the stimulus animal. Both subordinate and dominant WT hamsters preferred an unfamiliar subordinate stimulus animal. In contrast, neither subordinate nor dominant AR hamsters preferred any of the stimulus animals. Thus, disruptions in circadian

Oriented nanocomposites of ultrahigh-molecular-weight polyethylene and gold

NARCIS (Netherlands)

Heffels, W.; Bastiaansen, C.W.M.; Caseri, W.R.; Smith, P.

2000-01-01

Polymer nanocomposites were prepd. by mixing ultrahigh-mol.-wt. polyethylene and gold colloids coated with a self-assembled monolayer of dodecanethiol. Subsequently, these materials were oriented by solid state drawing which induced the formation of uniaxially oriented arrays of gold particles. As a

Social Cognition in Individuals at Ultra-High Risk for Psychosis: A Meta-Analysis.

Directory of Open Access Journals (Sweden)

R J M van Donkersgoed

Full Text Available Treatment in the ultra-high risk stage for a psychotic episode is critical to the course of symptoms. Markers for the development of psychosis have been studied, to optimize the detection of people at risk of psychosis. One possible marker for the transition to psychosis is social cognition. To estimate effect sizes for social cognition based on a quantitative integration of the published evidence, we conducted a meta-analysis of social cognitive performance in people at ultra high risk (UHR.A literature search (1970-July 2015 was performed in PubMed, PsychINFO, Medline, Embase, and ISI Web of Science, using the search terms 'social cognition', 'theory of mind', 'emotion recognition', 'attributional style', 'social knowledge', 'social perception', 'empathy', 'at risk mental state', 'clinical high risk', 'psychosis prodrome', and 'ultra high risk'. The pooled effect size (Cohen's D and the effect sizes for each domain of social cognition were calculated. A random effects model with 95% confidence intervals was used.Seventeen studies were included in the analysis. The overall significant effect was of medium magnitude (d = 0.52, 95% Cl = 0.38-0.65. No moderator effects were found for age, gender and sample size. Sub-analyses demonstrated that individuals in the UHR phase show significant moderate deficits in affect recognition and affect discrimination in faces as well as in voices and in verbal Theory of Mind (TOM. Due to an insufficient amount of studies, we did not calculate an effect size for attributional bias and social perception/ knowledge. A majority of studies did not find a correlation between social cognition deficits and transition to psychosis, which may suggest that social cognition in general is not a useful marker for the development of psychosis. However some studies suggest the possible predictive value of verbal TOM and the recognition of specific emotions in faces for the transition into psychosis. More research is needed on

Computer versus paper system for recognition and management of sepsis in surgical intensive care.

Science.gov (United States)

Croft, Chasen A; Moore, Frederick A; Efron, Philip A; Marker, Peggy S; Gabrielli, Andrea; Westhoff, Lynn S; Lottenberg, Lawrence; Jordan, Janeen; Klink, Victoria; Sailors, R Matthew; McKinley, Bruce A

2014-02-01

A system to provide surveillance, diagnosis, and protocolized management of surgical intensive care unit (SICU) sepsis was undertaken as a performance improvement project. A system for sepsis management was implemented for SICU patients using paper followed by a computerized system. The hypothesis was that the computerized system would be associated with improved process and outcomes. A system was designed to provide early recognition and guide patient-specific management of sepsis including (1) modified early warning signs-sepsis recognition score (MEWS-SRS; summative point score of ranges of vital signs, mental status, white blood cell count; after every 4 hours) by bedside nurse; (2) suspected site assessment (vascular access, lung, abdomen, urinary tract, soft tissue, other) at bedside by physician or extender; (3) sepsis management protocol (replicable, point-of-care decisions) at bedside by nurse, physician, and extender. The system was implemented first using paper and then a computerized system. Sepsis severity was defined using standard criteria. In January to May 2012, a paper system was used to manage 77 consecutive sepsis encounters (3.9 ± 0.5 cases per week) in 65 patients (77% male; age, 53 ± 2 years). In June to December 2012, a computerized system was used to manage 132 consecutive sepsis encounters (4.4 ± 0.4 cases per week) in 119 patients (63% male; age, 58 ± 2 years). MEWS-SRS elicited 683 site assessments, and 201 had sepsis diagnosis and protocol management. The predominant site of infection was abdomen (paper, 58%; computer, 53%). Recognition of early sepsis tended to occur more using the computerized system (paper, 23%; computer, 35%). Hospital mortality rate for surgical ICU sepsis (paper, 20%; computer, 14%) was less with the computerized system. A computerized sepsis management system improves care process and outcome. Early sepsis is recognized and managed with greater frequency compared with severe sepsis or septic shock. The system

IoT-Based Image Recognition System for Smart Home-Delivered Meal Services

Directory of Open Access Journals (Sweden)

Hsiao-Ting Tseng

2017-07-01

Full Text Available Population ageing is an important global issue. The Taiwanese government has used various Internet of Things (IoT applications in the “10-year long-term care program 2.0”. It is expected that the efficiency and effectiveness of long-term care services will be improved through IoT support. Home-delivered meal services for the elderly are important for home-based long-term care services. To ensure that the right meals are delivered to the right recipient at the right time, the runners need to take a picture of the meal recipient when the meal is delivered. This study uses the IoT-based image recognition system to design an integrated service to improve the management of image recognition. The core technology of this IoT-based image recognition system is statistical histogram-based k-means clustering for image segmentation. However, this method is time-consuming. Therefore, we proposed using the statistical histogram to obtain a probability density function of pixels of a figure and segmenting these with weighting for the same intensity. This aims to increase the computational performance and achieve the same results as k-means clustering. We combined histogram and k-means clustering in order to overcome the high computational cost for k-means clustering. The results indicate that the proposed method is significantly faster than k-means clustering by more than 10 times.

Industry-relevant magnetron sputtering and cathodic arc ultra-high vacuum deposition system for in situ x-ray diffraction studies of thin film growth using high energy synchrotron radiation

OpenAIRE

Schroeder, Jeremy; Thomson, W.; Howard, B.; Schell, N.; Näslund, Lars-Åke; Rogström, Lina; Johansson-Jöesaar, Mats P.; Ghafoor, Naureen; Odén, Magnus; Nothnagel, E.; Shepard, A.; Greer, J.; Birch, Jens

2015-01-01

We present an industry-relevant, large-scale, ultra-high vacuum (UHV) magnetron sputtering and cathodic arc deposition system purposefully designed for time-resolved in situ thin film deposition/annealing studies using high-energy (greater than50 keV), high photon flux (greater than10(12) ph/s) synchrotron radiation. The high photon flux, combined with a fast-acquisition-time (less than1 s) two-dimensional (2D) detector, permits time-resolved in situ structural analysis of thin film formation...

Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System

Directory of Open Access Journals (Sweden)

Miguel Gavilán

2012-01-01

Full Text Available This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM. A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

Complete vision-based traffic sign recognition supported by an I2V communication system.

Science.gov (United States)

García-Garrido, Miguel A; Ocaña, Manuel; Llorca, David F; Arroyo, Estefanía; Pozuelo, Jorge; Gavilán, Miguel

2012-01-01

This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.

A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier

Directory of Open Access Journals (Sweden)

Haryati Jaafar

2015-01-01

Full Text Available Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN, was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%.

Case-Based Policy and Goal Recognition

Science.gov (United States)

2015-09-30

Policy and Goal Recognizer (PaGR), a case- based system for multiagent keyhole recognition. PaGR is a knowledge recognition component within a decision...However, unlike our agent in the BVR domain, these recognition agents have access to perfect information. Single-agent keyhole plan recognition can be...listed below: 1. Facing Target 2. Closing on Target 3. Target Range 4. Within a Target’s Weapon Range 5. Has Target within Weapon Range 6. Is in Danger

Paradigms in object recognition

International Nuclear Information System (INIS)

Mutihac, R.; Mutihac, R.C.

1999-09-01

A broad range of approaches has been proposed and applied for the complex and rather difficult task of object recognition that involves the determination of object characteristics and object classification into one of many a priori object types. Our paper revises briefly the three main different paradigms in pattern recognition, namely Bayesian statistics, neural networks, and expert systems. (author)

Optimization of Monochromated TEM for Ultimate Resolution Imaging and Ultrahigh Resolution Electron Energy Loss Spectroscopy

KAUST Repository

Lopatin, Sergei; Cheng, Bin; Liu, Wei-Ting; Tsai, Meng-Lin; He, Jr-Hau; Chuvilin, Andrey

2017-01-01

The performance of a monochromated transmission electron microscope with Wien type monochromator is optimized to achieve an extremely narrow energy spread of electron beam and an ultrahigh energy resolution with spectroscopy. The energy spread in the beam is improved by almost an order of magnitude as compared to specified values. The optimization involves both the monochromator and the electron energy loss detection system. We demonstrate boosted capability of optimized systems with respect to ultra-low loss EELS and sub-angstrom resolution imaging (in a combination with spherical aberration correction).

Optimization of Monochromated TEM for Ultimate Resolution Imaging and Ultrahigh Resolution Electron Energy Loss Spectroscopy

KAUST Repository

Lopatin, Sergei

2017-09-01

The performance of a monochromated transmission electron microscope with Wien type monochromator is optimized to achieve an extremely narrow energy spread of electron beam and an ultrahigh energy resolution with spectroscopy. The energy spread in the beam is improved by almost an order of magnitude as compared to specified values. The optimization involves both the monochromator and the electron energy loss detection system. We demonstrate boosted capability of optimized systems with respect to ultra-low loss EELS and sub-angstrom resolution imaging (in a combination with spherical aberration correction).

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.

Fiber based hydrophones for ultra-high energy neutrino detection

NARCIS (Netherlands)

Buis, E.J.; Doppenberg, E.J.J.; Eijk, D. van; Lahmann, R.; Nieuwland, R.A.; Toet, P.M.

2014-01-01

It is a well studied process [1, 2] that energy deposition of cosmic ray particles in water that generate thermo-acoustic signals. Hydrophones of sufficient sensitivity could measure this signal and provide a means of detecting ultra-high energetic cosmic neutrinos. We investigate optical

Ultrahigh energy cosmic rays from nearby starburst galaxies

Science.gov (United States)

Attallah, Reda; Bouchachi, Dallel

2018-04-01

Ultrahigh energy cosmic rays are the most energetic of any subatomic particles ever observed in nature. The quest for their mysterious origin is currently a major scientific challenge. Here we explore the possibility that these particles originate from nearby starburst galaxies, a scenario that matches the recent observation by the Telescope Array experiment of a cosmic-ray hotspot above 57 EeV not far from the direction of the starburst galaxy M82. Specifically, we study the stochastic propagation in space of ultrahigh energy cosmic rays through the state-of-the-art simulation framework CRPropa 3, taking into account all relevant particle interactions as well as deflections by the intervening magnetic fields. To ensure a comprehensive understanding of this model, we consider the energy spectrum, the cosmogenic neutrinos and gamma rays, and the distribution of arrival directions. The starburst galaxy scenario reproduces well observations from both the Telescope Array and Pierre Auger Observatories, making it very attractive for explaining the origin of cosmic rays at the highest energies.

Application of high-power lasers to equation-of-state research at ultrahigh pressures

International Nuclear Information System (INIS)

Trainor, R.J.; Graboske, H.C.; Long, K.S.; Shaner, J.W.

1978-01-01

The application of high-power pulsed lasers to ultrahigh pressure equation-of-state (EOS) experiments is discussed. It is shown that pressures along the principal Hugoniot between 1 and 10 TPa can be produced with existing lasers used for inertial-confinement fusion research. The relevance of measurements in this pressure regime to improving our understanding of condensed matter physics is also discussed. New experimental techniques as well as potential experimental problems are described, and EOS experiments on the Janus and Argus laser systems are proposed

Experimental differentiation of intraocular masses using ultrahigh-field magnetic resonance imaging--a case series.

Directory of Open Access Journals (Sweden)

Karen Falke

Full Text Available PURPOSE: The case reports presented here were compiled to demonstrate the potential for improved diagnosis and monitoring of disease progress of intraocular lesions using ultrahigh-field magnetic resonance microscopy (MRM at 7.1 Tesla. METHODS: High-resolution ex vivo ocular magnetic resonance (MR images were acquired on an ultrahigh-field MR system (7.1 Tesla, ClinScan, Bruker BioScan, Germany using a 2-channel coil with 4 coil elements and T2-weighted turbo spin echo (TSE sequences of human eyes enucleated because of different intraocular lesions. Imaging parameters were: 40×40 mm field of view, 512×512 matrix, and 700 µm slice thickness. The results were correlated with in vivo ultrasound and histology of the enucleated eyes. RESULTS: Imaging was performed in enucleated eyes with choroidal melanoma, malignant melanoma of iris and ciliary body with scleral perforation, ciliary body melanoma, intraocular metastasis of esophageal cancer, subretinal bleeding in the presence of perforated corneal ulcer, hemorrhagic choroidal detachment, and premature retinopathy with phthisis and ossification of bulbar structures. MR imaging allowed differentiation between solid and cystic tumor components. In case of hemorrhage, fluid-fluid levels were identified. Melanin and calcifications caused significant hypointensity. Microstructural features of eye lesions identified by MRM were confirmed by histology. CONCLUSION: This study demonstrates the potential of MRM for the visualization and differential diagnosis of intraocular lesions. At present, the narrow bore of the magnet still limits the use of this technology in humans in vivo. Further advances in ultrahigh-field MR imaging will permit visualization of tumor extent and evaluation of nonclassified intraocular structures in the near future.

Business model for sensor-based fall recognition systems.

Science.gov (United States)

Fachinger, Uwe; Schöpke, Birte

2014-01-01

AAL systems require, in addition to sophisticated and reliable technology, adequate business models for their launch and sustainable establishment. This paper presents the basic features of alternative business models for a sensor-based fall recognition system which was developed within the context of the "Lower Saxony Research Network Design of Environments for Ageing" (GAL). The models were developed parallel to the R&D process with successive adaptation and concretization. An overview of the basic features (i.e. nine partial models) of the business model is given and the mutual exclusive alternatives for each partial model are presented. The partial models are interconnected and the combinations of compatible alternatives lead to consistent alternative business models. However, in the current state, only initial concepts of alternative business models can be deduced. The next step will be to gather additional information to work out more detailed models.

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

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)

Haar-like Features for Robust Real-Time Face Recognition

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2013-01-01

Face recognition is still a very challenging task when the input face image is noisy, occluded by some obstacles, of very low-resolution, not facing the camera, and not properly illuminated. These problems make the feature extraction and consequently the face recognition system unstable....... The proposed system in this paper introduces the novel idea of using Haar-like features, which have commonly been used for object detection, along with a probabilistic classifier for face recognition. The proposed system is simple, real-time, effective and robust against most of the mentioned problems....... Experimental results on public databases show that the proposed system indeed outperforms the state-of-the-art face recognition systems....

Probing physics at extreme energies with cosmic ultra-high energy ...

Indian Academy of Sciences (India)

testing new particle physics. Keywords. Ultra-high ... conventional theories of CR origin based on acceleration of charged particles in powerful ... Before discussing specific scenarios for UHECR origin we give a short account of the numerical ...

Towards evidence-based, quality-controlled health promotion: the Dutch recognition system for health promotion interventions.

NARCIS (Netherlands)

Brug, J.; Dale, D. van; Lanting, L.; Kremers, S.; Veenhof, C.; Leurs, M.; Yperen, T. van; Kok, G.

2010-01-01

Registration or recognition systems for best-practice health promotion interventions may contribute to better quality assurance and control in health promotion practice. In the Netherlands, such a system has been developed and is being implemented aiming to provide policy makers and professionals

Applied learning-based color tone mapping for face recognition in video surveillance system

Science.gov (United States)

Yew, Chuu Tian; Suandi, Shahrel Azmin

2012-04-01

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

Post-mortem inference of the human hippocampal connectivity and microstructure using ultra-high field diffusion MRI at 11.7 T.

Science.gov (United States)

Beaujoin, Justine; Palomero-Gallagher, Nicola; Boumezbeur, Fawzi; Axer, Markus; Bernard, Jeremy; Poupon, Fabrice; Schmitz, Daniel; Mangin, Jean-François; Poupon, Cyril

2018-06-01

The human hippocampus plays a key role in memory management and is one of the first structures affected by Alzheimer's disease. Ultra-high magnetic resonance imaging provides access to its inner structure in vivo. However, gradient limitations on clinical systems hinder access to its inner connectivity and microstructure. A major target of this paper is the demonstration of diffusion MRI potential, using ultra-high field (11.7 T) and strong gradients (750 mT/m), to reveal the extra- and intra-hippocampal connectivity in addition to its microstructure. To this purpose, a multiple-shell diffusion-weighted acquisition protocol was developed to reach an ultra-high spatio-angular resolution with a good signal-to-noise ratio. The MRI data set was analyzed using analytical Q-Ball Imaging, Diffusion Tensor Imaging (DTI), and Neurite Orientation Dispersion and Density Imaging models. High Angular Resolution Diffusion Imaging estimates allowed us to obtain an accurate tractography resolving more complex fiber architecture than DTI models, and subsequently provided a map of the cross-regional connectivity. The neurite density was akin to that found in the histological literature, revealing the three hippocampal layers. Moreover, a gradient of connectivity and neurite density was observed between the anterior and the posterior part of the hippocampus. These results demonstrate that ex vivo ultra-high field/ultra-high gradients diffusion-weighted MRI allows the mapping of the inner connectivity of the human hippocampus, its microstructure, and to accurately reconstruct elements of the polysynaptic intra-hippocampal pathway using fiber tractography techniques at very high spatial/angular resolutions.

Manganese oxide micro-supercapacitors with ultra-high areal capacitance

Science.gov (United States)

Wang, Xu; Myers, Benjamin D.; Yan, Jian; Shekhawat, Gajendra; Dravid, Vinayak; Lee, Pooi See

2013-05-01

A symmetric micro-supercapacitor is constructed by electrochemically depositing manganese oxide onto micro-patterned current collectors. High surface-to-volume ratio of manganese oxide and short diffusion distance between electrodes give an ultra-high areal capacitance of 56.3 mF cm-2 at a current density of 27.2 μA cm-2.A symmetric micro-supercapacitor is constructed by electrochemically depositing manganese oxide onto micro-patterned current collectors. High surface-to-volume ratio of manganese oxide and short diffusion distance between electrodes give an ultra-high areal capacitance of 56.3 mF cm-2 at a current density of 27.2 μA cm-2. Electronic supplementary information (ESI) available: Experimental procedures; optical images of micro-supercapacitors; areal capacitances of samples M-0.3C, M-0.6C and M-0.9C; illustration of interdigital finger electrodes; Nyquist plot of Co(OH)2 deposited on micro-electrodes. See DOI: 10.1039/c3nr00210a

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

Science.gov (United States)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

FY 2000 report on the results of the regional consortium R and D project - Regional consortium energy. First year report. Development of a next generation biopolymer information measuring system based on the nano channel electrophoresis; 2000 nendo chiiki consortium kenkyu kaihatsu jigyo - chiiki consortium energy. Nano channel denki eido ni motozuku jisedai seitai kobunshi joho keisoku system no kaihatsu (dai 1 nendo) seika hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

On the basis of the nano channel electrophoresis technology, the construction was proceeded with of a system which integrates the basic process such as reaction, separation and detection needed for measuring biopolymer information and analyzes a number of samples simultaneously and with high accuracy/high sensitivity. Studies were made in the following three fields: 1) development of the basement technology on extraction/amplification/separation/detection of biopolymer; 2) development of micro-processing technology and system design and study on the development of device; 3) comprehensive investigational study. In 1), developmental technology is divided into the following: technology to effectively fraction/refine biopolymer from biological samples, technology for recognition control and manipulation of biopolymer, technology of amplification use micro-reaction of biopolymer, multiple selection technology of biopolymer using the specific molecular recognition, and technology for ultra-high speed separation of biopolymer. As to the multiple selection technology, DNA terminal recognizing hemin is altered by thiol group and connected to the surface of electrode to make an electrode type hemin recognition device. (NEDO)

A Spoken English Recognition Expert System.

Science.gov (United States)

1983-09-01

34Speech Recognition by Computer," Scientific American. New York: Scientific American, April 1981: 64-76. 16. Marcus, Mitchell P. A Theo of Syntactic...prob)...) Pcssible words for voice decoder to choose from are: gents dishes issues itches ewes folks foes comunications units eunichs error * farce

USING A MICRO-UAV FOR ULTRA-HIGH RESOLUTION MULTI-SENSOR OBSERVATIONS OF ANTARCTIC MOSS BEDS

Directory of Open Access Journals (Sweden)

A. Lucieer

2012-07-01

Full Text Available This study is the first to use an Unmanned Aerial Vehicle (UAV for mapping moss beds in Antarctica. Mosses can be used as indicators for the regional effects of climate change. Mapping and monitoring their extent and health is therefore important. UAV aerial photography provides ultra-high resolution spatial data for this purpose. We developed a technique to extract an extremely dense 3D point cloud from overlapping UAV aerial photography based on structure from motion (SfM algorithms. The combination of SfM and patch-based multi-view stereo image vision algorithms resulted in a 2 cm resolution digital terrain model (DTM. This detailed topographic information combined with vegetation indices derived from a 6-band multispectral sensor enabled the assessment of moss bed health. This novel UAV system has allowed us to map different environmental characteristics of the moss beds at ultra-high resolution providing us with a better understanding of these fragile Antarctic ecosystems. The paper provides details on the different UAV instruments and the image processing framework resulting in DEMs, vegetation indices, and terrain derivatives.

Optimization Methods in Emotion Recognition System

Directory of Open Access Journals (Sweden)

L. Povoda

2016-09-01

Full Text Available Emotions play big role in our everyday communication and contain important information. This work describes a novel method of automatic emotion recognition from textual data. The method is based on well-known data mining techniques, novel approach based on parallel run of SVM (Support Vector Machine classifiers, text preprocessing and 3 optimization methods: sequential elimination of attributes, parameter optimization based on token groups, and method of extending train data sets during practical testing and production release final tuning. We outperformed current state of the art methods and the results were validated on bigger data sets (3346 manually labelled samples which is less prone to overfitting when compared to related works. The accuracy achieved in this work is 86.89% for recognition of 5 emotional classes. The experiments were performed in the real world helpdesk environment, was processing Czech language but the proposed methodology is general and can be applied to many different languages.

CHICSi - a compact ultra-high vacuum compatible detector system for nuclear reaction experiments at storage rings. I. General structure, mechanics and UHV compatibility

International Nuclear Information System (INIS)

Westerberg, L.; Avdeichikov, V.; Carlen, L.; Golubev, P.; Jakobsson, B.; Rouki, C.; Siwek, A.; Veldhuizen, E.J. van; Whitlow, H.J.

2003-01-01

CELSIUS Heavy-Ion Collision Silicon detector system (CHICSi) is a large solid angle, barrel-shaped detector system, housing up to 600 detector telescopes arranged in rotational symmetry around the beam axis. CHICSi measures charged particles and fragments from nuclear reactions. It operates at internal targets of storage rings. In order to optimize space and momentum-space coverage and minimize the low-energy detection limits, CHICSi is designed for use in ultra-high vacuum (UHV, ∼10 -8 Pa) inside a cluster-jet target chamber. This calls for materials in mechanical support, detectors, Very Large Scale Integrated (VLSI) electronics, connectors, cables and other signal transport devices with very low outgassing. Two auxiliary detector systems, which will operate in coincidence with CHICSi, a heavy-recoil, time-of-flight system (HR-TOF) also placed inside the target chamber and a projectile fragmentation wall (PF-WALL) located outside the chamber, have also been constructed. In total, this combined system registers more than 80% of all charged particles and fragments from typical heavy-ion reactions at energies of a few hundreds of MeV per nucleon

CHICSi - a compact ultra-high vacuum compatible detector system for nuclear reaction experiments at storage rings. I. General structure, mechanics and UHV compatibility

Energy Technology Data Exchange (ETDEWEB)

Westerberg, L.; Avdeichikov, V.; Carlen, L.; Golubev, P.; Jakobsson, B. E-mail: bo.jakobsson@kosufy.lu.se; Rouki, C.; Siwek, A.; Veldhuizen, E.J. van; Whitlow, H.J

2003-03-11

CELSIUS Heavy-Ion Collision Silicon detector system (CHICSi) is a large solid angle, barrel-shaped detector system, housing up to 600 detector telescopes arranged in rotational symmetry around the beam axis. CHICSi measures charged particles and fragments from nuclear reactions. It operates at internal targets of storage rings. In order to optimize space and momentum-space coverage and minimize the low-energy detection limits, CHICSi is designed for use in ultra-high vacuum (UHV, {approx}10{sup -8} Pa) inside a cluster-jet target chamber. This calls for materials in mechanical support, detectors, Very Large Scale Integrated (VLSI) electronics, connectors, cables and other signal transport devices with very low outgassing. Two auxiliary detector systems, which will operate in coincidence with CHICSi, a heavy-recoil, time-of-flight system (HR-TOF) also placed inside the target chamber and a projectile fragmentation wall (PF-WALL) located outside the chamber, have also been constructed. In total, this combined system registers more than 80% of all charged particles and fragments from typical heavy-ion reactions at energies of a few hundreds of MeV per nucleon.

Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Yu Bo

2017-01-01

Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

Contralateral comparison of wavefront-guided LASIK surgery with iris recognition versus without iris recognition using the MEL80 Excimer laser system.

Science.gov (United States)

Wu, Fang; Yang, Yabo; Dougherty, Paul J

2009-05-01

To compare outcomes in wavefront-guided LASIK performed with iris recognition software versus without iris recognition software in different eyes of the same patient. A randomised, prospective study of 104 myopic eyes of 52 patients undergoing LASIK surgery with the MEL80 excimer laser system was performed. Iris recognition software was used in one eye of each patient (study group) and not used in the other eye (control group). Higher order aberrations (HOAs), contrast sensitivity, uncorrected vision (UCV), visual acuity (VA) and corneal topography were measured and recorded pre-operatively and at one month and three months post-operatively for each eye. The mean post-operative sphere and cylinder between groups was similar, however the post-operative angles of error (AE) by refraction were significantly smaller in the study group compared to the control group both in arithmetic and absolute means (p = 0.03, p = 0.01). The mean logMAR UCV was significantly better in the study group than in the control group at one month (p = 0.01). The mean logMAR VA was significantly better in the study group than in control group at both one and three months (p = 0.01, p = 0.03). In addition, mean trefoil, total third-order aberration, total fourth-order aberration and the total scotopic root-mean-square (RMS) HOAs were significantly less in the study group than those in the control group at the third (p = 0.01, p = 0.05, p = 0.04, p = 0.02). By three months, the contrast sensitivity had recovered in both groups but the study group performed better at 2.6, 4.2 and 6.6 cpd (cycles per degree) than the control group (p = 0.01, p iris recognition results in better VA, lower mean higher-order aberrations, lower refractive post-operative angles of error and better contrast sensitivity at three months post-operatively than LASIK performed without iris recognition.

WORD LEVEL DISCRIMINATIVE TRAINING FOR HANDWRITTEN WORD RECOGNITION

NARCIS (Netherlands)

Chen, W.; Gader, P.

2004-01-01

Word level training refers to the process of learning the parameters of a word recognition system based on word level criteria functions. Previously, researchers trained lexicon­driven handwritten word recognition systems at the character level individually. These systems generally use statistical

Bond behavior of reinforcing steel in ultra-high performance concrete.

Science.gov (United States)

2014-10-01

Ultra-High Performance Concrete (UHPC) is a relatively new class of advanced cementitious composite : materials, which exhibits high compressive [above 21.7 ksi (150 MPa)] and tensile [above 0.72 ksi (5 MPa)] : strengths. The discrete steel fiber rei...

Automated target recognition and tracking using an optical pattern recognition neural network

Science.gov (United States)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Thermal characterization of Ag and Ag + N ion implanted ultra-high molecular weight polyethylene (UHMWPE)

Science.gov (United States)

Sokullu Urkac, E.; Oztarhan, A.; Tihminlioglu, F.; Kaya, N.; Ila, D.; Muntele, C.; Budak, S.; Oks, E.; Nikolaev, A.; Ezdesir, A.; Tek, Z.

2007-08-01

Most of total hip joints are composed of ultra-high molecular weight polyethylene (UHMWPE). However, as ultra-high molecular weight polyethylene is too stable in a body, wear debris may accumulate and cause biological response such as bone absorption and loosening of prosthesis. In this study, ultra-high molecular weight polyethylene samples were Ag and Ag + N hybrid ion implanted by using MEVVA ion implantation technique to improve its surface properties. Samples were implanted with a fluence of 1017 ion/cm2 and extraction voltage of 30 kV. Implanted and unimplanted samples were investigated by thermo-gravimetry analysis (TGA), differential scanning calorimetry (DSC), X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), optical microscopy (OM) and contact Angle measurement. Thermal characterization results showed that the ion bombardment induced an increase in the % crystallinity, onset and termination degradation temperatures of UHMWPE.

A NEW STRATEGY FOR IMPROVING FEATURE SETS IN A DISCRETE HMM­BASED HANDWRITING RECOGNITION SYSTEM

NARCIS (Netherlands)

Grandidier, F.; Sabourin, R.; Suen, C.Y.; Gilloux, M.

2004-01-01

In this paper we introduce a new strategy for improving a discrete HMM­based handwriting recognition system, by integrating several information sources from specialized feature sets. For a given system, the basic idea is to keep the most discriminative features, and to replace the others with new

Social cognition in patients at ultra-high risk for psychosis

DEFF Research Database (Denmark)

Glenthøj, Louise B.; Fagerlund, Birgitte; Hjorthøj, Carsten

2016-01-01

Objective: Patients at ultra-high risk (UHR) for psychosis show significant impairments in functioning. It is essential to determine which factors influence functioning, as it may have implications for intervention strategies. This study examined whether social cognitive abilities and clinical...

Template protection and its implementation in 3D face recognition systems

Science.gov (United States)

Zhou, Xuebing

2007-04-01

As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

Sistema audiovisual para reconocimiento de comandos Audiovisual system for recognition of commands

Directory of Open Access Journals (Sweden)

Alexander Ceballos

2011-08-01

Full Text Available Se presenta el desarrollo de un sistema automático de reconocimiento audiovisual del habla enfocado en el reconocimiento de comandos. La representación del audio se realizó mediante los coeficientes cepstrales de Mel y las primeras dos derivadas temporales. Para la caracterización del vídeo se hizo seguimiento automático de características visuales de alto nivel a través de toda la secuencia. Para la inicialización automática del algoritmo se emplearon transformaciones de color y contornos activos con información de flujo del vector gradiente ("GVF snakes" sobre la región labial, mientras que para el seguimiento se usaron medidas de similitud entre vecindarios y restricciones morfológicas definidas en el estándar MPEG-4. Inicialmente, se presenta el diseño del sistema de reconocimiento automático del habla, empleando únicamente información de audio (ASR, mediante Modelos Ocultos de Markov (HMMs y un enfoque de palabra aislada; posteriormente, se muestra el diseño de los sistemas empleando únicamente características de vídeo (VSR, y empleando características de audio y vídeo combinadas (AVSR. Al final se comparan los resultados de los tres sistemas para una base de datos propia en español y francés, y se muestra la influencia del ruido acústico, mostrando que el sistema de AVSR es más robusto que ASR y VSR.We present the development of an automatic audiovisual speech recognition system focused on the recognition of commands. Signal audio representation was done using Mel cepstral coefficients and their first and second order time derivatives. In order to characterize the video signal, a set of high-level visual features was tracked throughout the sequences. Automatic initialization of the algorithm was performed using color transformations and active contour models based on Gradient Vector Flow (GVF Snakes on the lip region, whereas visual tracking used similarity measures across neighborhoods and morphological

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Heracleous Panikos

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

[Neurological disease and facial recognition].

Science.gov (United States)

Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

2012-07-01

To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

Application of Business Process Management to drive the deployment of a speech recognition system in a healthcare organization.

Science.gov (United States)

González Sánchez, María José; Framiñán Torres, José Manuel; Parra Calderón, Carlos Luis; Del Río Ortega, Juan Antonio; Vigil Martín, Eduardo; Nieto Cervera, Jaime

2008-01-01

We present a methodology based on Business Process Management to guide the development of a speech recognition system in a hospital in Spain. The methodology eases the deployment of the system by 1) involving the clinical staff in the process, 2) providing the IT professionals with a description of the process and its requirements, 3) assessing advantages and disadvantages of the speech recognition system, as well as its impact in the organisation, and 4) help reorganising the healthcare process before implementing the new technology in order to identify how it can better contribute to the overall objective of the organisation.

Star pattern recognition algorithm aided by inertial information

Science.gov (United States)

Liu, Bao; Wang, Ke-dong; Zhang, Chao

2011-08-01

Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.

A Development of Hybrid Drug Information System Using Image Recognition

Directory of Open Access Journals (Sweden)

HwaMin Lee

2015-04-01

Full Text Available In order to prevent drug abuse or misuse cases and avoid over-prescriptions, it is necessary for medicine taker to be provided with detailed information about the medicine. In this paper, we propose a drug information system and develop an application to provide information through drug image recognition using a smartphone. We designed a contents-based drug image search algorithm using the color, shape and imprint of drug. Our convenient application can provide users with detailed information about drugs and prevent drug misuse.

Material recognition with the Medipix photon counting colour X-ray system

Energy Technology Data Exchange (ETDEWEB)

Norlin, B. E-mail: borje.norlin@mh.se; Manuilskiy, A.; Nilsson, H.-E.; Froejdh, C

2004-09-21

An energy sensitive imaging system like Medipix1 has proved to be promising in distinguishing different materials in an X-ray image of an object. We propose a general method utilising X-ray energy information for material recognition. For objects where the thickness of the materials is unknown, a convenient material parameter to identify is K={alpha}{sub 1}/{alpha}{sub 2}, which is the ratio of the logarithms of the measured transmissions ln(t{sub 1})/ln(t{sub 2}). If a database of the parameter K for different materials and energies is created, this method can be used for material recognition independent of the thickness of the materials. Series of images of an object consisting of aluminium and silicon were taken with different energy thresholds. The X-ray absorption for silicon and aluminium is very similar for the range 40-60 keV and only differs for lower energies. The results show that it is possible to distinguish between aluminium and silicon on images achieved by Medipix1 using a standard dental source. By decreasing the spatial resolution a better contrast between the materials was achieved. The resolution of contrasts shown by the histograms was close to the limit of the system due to the statistical noise of the signal.

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.

Channeling acceleration: A path to ultrahigh energy colliders

International Nuclear Information System (INIS)

Chen, P.; Huang, Z.; Ruth, R.D.

1995-01-01

Acceleration of charged particles along crystal channels has been proposed earlier in an attempt to achieve high acceleration gradient while at the same time to suppress excessive emittance growth. Recently the authors demonstrated that a particle in a generic focusing channel can in principle absolutely damp to its transverse ground state without any quantum excitation. This yields the minimum beam emittance that one can ever attain, γε min = ℎ/2mc, limited only by the uncertainty principle. In this paper they discuss sources of excitation when a more realistic channel is considered, including bremsstrahlung and multiple Coulomb scattering. They investigate the possibility of colliding ultrahigh energy particles in such strong focusing channels without the need of a final focusing system, where the concept of luminosity departs from the conventional approach. They show that a high luminosity can be attained with a rather modest beam power

HMM Adaptation for Improving a Human Activity Recognition System

Directory of Open Access Journals (Sweden)

Rubén San-Segundo

2016-09-01

Full Text Available When developing a fully automatic system for evaluating motor activities performed by a person, it is necessary to segment and recognize the different activities in order to focus the analysis. This process must be carried out by a Human Activity Recognition (HAR system. This paper proposes a user adaptation technique for improving a HAR system based on Hidden Markov Models (HMMs. This system segments and recognizes six different physical activities (walking, walking upstairs, walking downstairs, sitting, standing and lying down using inertial signals from a smartphone. The system is composed of a feature extractor for obtaining the most relevant characteristics from the inertial signals, a module for training the six HMMs (one per activity, and the last module for segmenting new activity sequences using these models. The user adaptation technique consists of a Maximum A Posteriori (MAP approach that adapts the activity HMMs to the user, using some activity examples from this specific user. The main results on a public dataset have reported a significant relative error rate reduction of more than 30%. In conclusion, adapting a HAR system to the user who is performing the physical activities provides significant improvement in the system’s performance.

Towards PLDA-RBM based speaker recognition in mobile environment: Designing stacked/deep PLDA-RBM systems

DEFF Research Database (Denmark)

Nautsch, Andreas; Hao, Hong; Stafylakis, Themos

2016-01-01

recognition: two deep architectures are presented and examined, which aim at suppressing channel effects and recovering speaker-discriminative information on back-ends trained on a small dataset. Experiments are carried out on the MOBIO SRE'13 database, which is a challenging and publicly available dataset...... for mobile speaker recognition with limited amounts of training data. The experiments show that the proposed system outperforms the baseline i-vector/PLDA approach by relative gains of 31% on female and 9% on male speakers in terms of half total error rate....

Pedestrian recognition using automotive radar sensors

OpenAIRE

A. Bartsch; F. Fitzek; R. H. Rasshofer

2012-01-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insight...

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...

Ultra-high resolution optical coherence tomography for encapsulation quality inspection

KAUST Repository

Czajkowski, Jakub

2011-08-28

We present the application of ultra-high resolution optical coherence tomography (UHR-OCT) in evaluation of thin, protective films used in printed electronics. Two types of sample were investigated: microscopy glass and organic field effect transistor (OFET) structure. Samples were coated with thin (1-3 μm) layer of parylene C polymer. Measurements were done using experimental UHR-OCT device based on a Kerr-lens mode locked Ti: sapphire femtosecond laser, photonic crystal fibre and modified, free-space Michelson interferometer. Submicron resolution offered by the UHR-OCT system applied in the study enables registration of both interfaces of the thin encapsulation layer. Complete, volumetric characterisation of protective layers is presented, demonstrating possibility to use OCT for encapsulation quality inspection. © Springer-Verlag 2011.

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.

A Delay Time Measurement of ULTRAS (Ultra-high Temperature Ultrasonic Response Analysis System) for a High Temperature Experiment

International Nuclear Information System (INIS)

Koo, Kil Mo; Kim, Sang Baik

2010-01-01

The temperature measurement of very high temperature core melt is of importance in a high temperature as the molten pool experiment in which gap formation between core melt and the reactor lower head, and the effect of the gap on thermal behavior are to be measured. The existing temperature measurement techniques have some problems, which the thermocouple, one of the contact methods, is restricted to under 2000 .deg. C, and the infrared thermometry, one of the non-contact methods, is unable to measure an internal temperature and very sensitive to the interference from reacted gases. In order to solve these problems, the delay time technique of ultrasonic wavelets due to high temperature has two sorts of stage. As a first stage, a delay time measurement of ULTRAS (Ultra-high Temperature Ultrasonic Response Analysis System) is suggested. As a second stage, a molten material temperature was measured up to 2300 .deg. C. Also, the optimization design of the UTS (ultrasonic temperature sensor) with persistence at the high temperature was suggested in this paper. And the utilization of the theory suggested in this paper and the efficiency of the developed system are performed by special equipment and some experiments supported by KRISS (Korea Research Institute of Standard and Science)

Ultra-high Efficiency DC-DC Converter using GaN Devices

DEFF Research Database (Denmark)

Ramachandran, Rakesh

2016-01-01

properties of GaN devices can be utilized in power converters to make them more compact and highly efficient. This thesis entitled “Ultra-high Efficiency DC-DC Converter using GaN devices” focuses on achieving ultra-high conversion efficiency in an isolated dc-dc converter by the optimal utilization of Ga...... for many decades. However, the rate of improvement slowed as the silicon power materials asymptotically approached its theoretical bounds. Compared to Si, wideband gap materials such as Silicon Carbide (SiC) and Gallium Nitride (GaN) are promising semiconductors for power devices due to their superior...... in this thesis. Efficiency measurements from the hardware prototype of both the topologies are also presented in this thesis. Finally, the bidirectional operation of an optimized isolated dc-dc converter is presented. The optimized converter has achieved an ultra-high efficiency of 98.8% in both directions...

Real-time embedded face recognition for smart home

NARCIS (Netherlands)

Zuo, F.; With, de P.H.N.

2005-01-01

We propose a near real-time face recognition system for embedding in consumer applications. The system is embedded in a networked home environment and enables personalized services by automatic identification of users. The aim of our research is to design and build a face recognition system that is

Thermal characterization of Ag and Ag + N ion implanted ultra-high molecular weight polyethylene (UHMWPE)

Energy Technology Data Exchange (ETDEWEB)

Sokullu Urkac, E. [Department of Materials Science, Izmir High Technology Institute, Gulbahcekoyu Urla, Izmir (Turkey)]. E-mail: emelsu@gmail.com; Oztarhan, A. [Bioengineering Department, Ege University, Bornova, Izmir 35100 (Turkey); Tihminlioglu, F. [Department of Chemical Engineering, Izmir High Technology Institute, Gulbahcekoyu Urla, Izmir (Turkey); Kaya, N. [Bioengineering Department, Ege University, Bornova, Izmir 35100 (Turkey); Ila, D. [Center for Irradiation of Materials, Alabama A and M University, Normal AL 35762 (United States); Muntele, C. [Center for Irradiation of Materials, Alabama A and M University, Normal AL 35762 (United States); Budak, S. [Center for Irradiation of Materials, Alabama A and M University, Normal AL 35762 (United States); Oks, E. [H C Electronics Institute, Tomsk (Russian Federation); Nikolaev, A. [H C Electronics Institute, Tomsk (Russian Federation); Ezdesir, A. [R and D Department, PETKIM Holding A.S., Aliaga, Izmir 35801 (Turkey); Tek, Z. [Department of Physics, Celal Bayar University, Manisa (Turkey)

2007-08-15

Most of total hip joints are composed of ultra-high molecular weight polyethylene (UHMWPE ). However, as ultra-high molecular weight polyethylene is too stable in a body, wear debris may accumulate and cause biological response such as bone absorption and loosening of prosthesis. In this study, ultra-high molecular weight polyethylene samples were Ag and Ag + N hybrid ion implanted by using MEVVA ion implantation technique to improve its surface properties. Samples were implanted with a fluence of 10{sup 17} ion/cm{sup 2} and extraction voltage of 30 kV. Implanted and unimplanted samples were investigated by thermo-gravimetry analysis (TGA), differential scanning calorimetry (DSC), X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), optical microscopy (OM) and contact Angle measurement. Thermal characterization results showed that the ion bombardment induced an increase in the % crystallinity, onset and termination degradation temperatures of UHMWPE.

Type I interferon production during herpes simplex virus infection is controlled by cell-type-specific viral recognition through Toll-like receptor 9, the mitochondrial antiviral signaling protein pathway, and novel recognition systems

DEFF Research Database (Denmark)

Rasmussen, Simon Brandtoft; Sørensen, Louise Nørgaard; Malmgaard, Lene

2007-01-01

Recognition of viruses by germ line-encoded pattern recognition receptors of the innate immune system is essential for rapid production of type I interferon (IFN) and early antiviral defense. We investigated the mechanisms of viral recognition governing production of type I IFN during herpes...... simplex virus (HSV) infection. We show that early production of IFN in vivo is mediated through Toll-like receptor 9 (TLR9) and plasmacytoid dendritic cells, whereas the subsequent alpha/beta IFN (IFN-alpha/beta) response is derived from several cell types and induced independently of TLR9...

Ultrahigh energy neutrinos and nonlinear QCD dynamics

International Nuclear Information System (INIS)

Machado, Magno V.T.

2004-01-01

The ultrahigh energy neutrino-nucleon cross sections are computed taking into account different phenomenological implementations of the nonlinear QCD dynamics. Based on the color dipole framework, the results for the saturation model supplemented by the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution as well as for the Balitskii-Fadin-Kuraev-Lipatov (BFKL) formalism in the geometric scaling regime are presented. They are contrasted with recent calculations using next-to-leading order DGLAP and unified BFKL-DGLAP formalisms

Proton-proton elastic scattering at ultrahigh energies

Energy Technology Data Exchange (ETDEWEB)

Saleem, M.; Shaukat, M.A.; Fazal-e-Aleem (University of the Punjab, Lahore (Pakistan). Dept. of Physics)

1981-05-30

Recent experimental results on proton-proton elastic scattering at high energies are discussed in the context of the comments by Chou and Yang. There does not appear to be any tendency that the experimental results would agree with the predictions of the geometrical model even at ultrahigh energies. The angular distribution structure as described by using the dipole pomeron is consistent with the experimental data at presently available high energies and predicts results quite different from the geometrical model.

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.

Automated Field-of-View, Illumination, and Recognition Algorithm Design of a Vision System for Pick-and-Place Considering Colour Information in Illumination and Images.

Science.gov (United States)

Chen, Yibing; Ogata, Taiki; Ueyama, Tsuyoshi; Takada, Toshiyuki; Ota, Jun

2018-05-22

Machine vision is playing an increasingly important role in industrial applications, and the automated design of image recognition systems has been a subject of intense research. This study has proposed a system for automatically designing the field-of-view (FOV) of a camera, the illumination strength and the parameters in a recognition algorithm. We formulated the design problem as an optimisation problem and used an experiment based on a hierarchical algorithm to solve it. The evaluation experiments using translucent plastics objects showed that the use of the proposed system resulted in an effective solution with a wide FOV, recognition of all objects and 0.32 mm and 0.4° maximal positional and angular errors when all the RGB (red, green and blue) for illumination and R channel image for recognition were used. Though all the RGB illumination and grey scale images also provided recognition of all the objects, only a narrow FOV was selected. Moreover, full recognition was not achieved by using only G illumination and a grey-scale image. The results showed that the proposed method can automatically design the FOV, illumination and parameters in the recognition algorithm and that tuning all the RGB illumination is desirable even when single-channel or grey-scale images are used for recognition.

Quadcopter Control Using Speech Recognition

Science.gov (United States)

Malik, H.; Darma, S.; Soekirno, S.

2018-04-01

This research reported a comparison from a success rate of speech recognition systems that used two types of databases they were existing databases and new databases, that were implemented into quadcopter as motion control. Speech recognition system was using Mel frequency cepstral coefficient method (MFCC) as feature extraction that was trained using recursive neural network method (RNN). MFCC method was one of the feature extraction methods that most used for speech recognition. This method has a success rate of 80% - 95%. Existing database was used to measure the success rate of RNN method. The new database was created using Indonesian language and then the success rate was compared with results from an existing database. Sound input from the microphone was processed on a DSP module with MFCC method to get the characteristic values. Then, the characteristic values were trained using the RNN which result was a command. The command became a control input to the single board computer (SBC) which result was the movement of the quadcopter. On SBC, we used robot operating system (ROS) as the kernel (Operating System).

Increasing the information acquisition volume in iris recognition systems.

Science.gov (United States)

Barwick, D Shane

2008-09-10

A significant hurdle for the widespread adoption of iris recognition in security applications is that the typically small imaging volume for eye placement results in systems that are not user friendly. Separable cubic phase plates at the lens pupil have been shown to ameliorate this disadvantage by increasing the depth of field. However, these phase masks have limitations on how efficiently they can capture the information-bearing spatial frequencies in iris images. The performance gains in information acquisition that can be achieved by more general, nonseparable phase masks is demonstrated. A detailed design method is presented, and simulations using representative designs allow for performance comparisons.

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.

Visible-to-visible four-photon ultrahigh resolution microscopic imaging with 730-nm diode laser excited nanocrystals.

Science.gov (United States)

Wang, Baoju; Zhan, Qiuqiang; Zhao, Yuxiang; Wu, Ruitao; Liu, Jing; He, Sailing

2016-01-25

Further development of multiphoton microscopic imaging is confronted with a number of limitations, including high-cost, high complexity and relatively low spatial resolution due to the long excitation wavelength. To overcome these problems, for the first time, we propose visible-to-visible four-photon ultrahigh resolution microscopic imaging by using a common cost-effective 730-nm laser diode to excite the prepared Nd(3+)-sensitized upconversion nanoparticles (Nd(3+)-UCNPs). An ordinary multiphoton scanning microscope system was built using a visible CW diode laser and the lateral imaging resolution as high as 161-nm was achieved via the four-photon upconversion process. The demonstrated large saturation excitation power for Nd(3+)-UCNPs would be more practical and facilitate the four-photon imaging in the application. A sample with fine structure was imaged to demonstrate the advantages of visible-to-visible four-photon ultrahigh resolution microscopic imaging with 730-nm diode laser excited nanocrystals. Combining the uniqueness of UCNPs, the proposed visible-to-visible four-photon imaging would be highly promising and attractive in the field of multiphoton imaging.

Support vector machine for automatic pain recognition

Science.gov (United States)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

Face recognition in the thermal infrared domain

Science.gov (United States)

Kowalski, M.; Grudzień, A.; Palka, N.; Szustakowski, M.

2017-10-01

Biometrics refers to unique human characteristics. Each unique characteristic may be used to label and describe individuals and for automatic recognition of a person based on physiological or behavioural properties. One of the most natural and the most popular biometric trait is a face. The most common research methods on face recognition are based on visible light. State-of-the-art face recognition systems operating in the visible light spectrum achieve very high level of recognition accuracy under controlled environmental conditions. Thermal infrared imagery seems to be a promising alternative or complement to visible range imaging due to its relatively high resistance to illumination changes. A thermal infrared image of the human face presents its unique heat-signature and can be used for recognition. The characteristics of thermal images maintain advantages over visible light images, and can be used to improve algorithms of human face recognition in several aspects. Mid-wavelength or far-wavelength infrared also referred to as thermal infrared seems to be promising alternatives. We present the study on 1:1 recognition in thermal infrared domain. The two approaches we are considering are stand-off face verification of non-moving person as well as stop-less face verification on-the-move. The paper presents methodology of our studies and challenges for face recognition systems in the thermal infrared domain.

Finite escape fraction for ultrahigh energy collisions around Kerr

Indian Academy of Sciences (India)

We investigate the issue of observability of high-energy collisions around Kerr naked singularity and show that results are in contrast with the Kerr black hole case. We had shown that it would be possible to have ultrahigh energy collisions between the particles close to the location = M around the Kerr naked singularity if ...

Finite escape fraction for ultrahigh energy collisions around Kerr ...

Indian Academy of Sciences (India)

Abstract. We investigate the issue of observability of high-energy collisions around Kerr naked singularity and show that results are in contrast with the Kerr black hole case. We had shown that it would be possible to have ultrahigh energy collisions between the particles close to the location r = M around the Kerr naked ...

Recent progress of ultrahigh voltage SiC devices for particle accelerator

International Nuclear Information System (INIS)

Fukuda, Kenji; Tsuji, Takashi; Shiomi, Hiromu; Mizushima, Tomonori; Yonezawa, Yoshiyuki; Kondo, Chikara; Otake, Yuji

2016-01-01

Silicon carbide (SiC) is the promising material for next power electronics technology used in the field such as HEV, EV, and railway, electric power infrastructure. SiC enables power devices with low loss to easily operate in an ultrahigh-voltage region because of the high breakdown electric field of SiC. In this paper, we report static and dynamic electric performances of 3300 V class SiC SBDs, IE-MOSFETs, >10 kV PiN diodes and IE-IGBTs. Especially, the electrical characteristics of IE-IGBT with the blocking voltage of 16.5 kV indicate the sufficient ability to convert the thyratron in high power RF system of an accelerator. (author)

An Evaluation of Ultra-High Pressure Regulator for Robotic Lunar Landing Spacecraft

Science.gov (United States)

Burnside, Christopher; Trinh, Huu; Pedersen, Kevin

2011-01-01

The Robotic Lunar Lander Development (RLLD) Project Office at NASA Marshall Space Flight Center (MSFC) has studied several lunar surface science mission concepts. These missions focus on spacecraft carrying multiple science instruments and power systems that will allow extended operations on the lunar surface. Initial trade studies of launch vehicle options for these mission concepts indicate that the spacecraft design will be significantly mass-constrained. To minimize mass and facilitate efficient packaging, the notional propulsion system for these landers has a baseline of an ultra-high pressure (10,000 psig) helium pressurization system that has been used on Defense missiles. The qualified regulator is capable of short duration use; however, the hardware has not been previously tested at NASA spacecraft requirements with longer duration. Hence, technical risks exist in using this missile-based propulsion component for spacecraft applications. A 10,000-psig helium pressure regulator test activity is being carried out as part of risk reduction testing for MSFC RLLD project. The goal of the test activity is to assess the feasibility of commercial off-the-shelf ultra-high pressure regulator by testing with a representative flight mission profile. Slam-start, gas blowdown, water expulsion, lock-up, and leak tests are also performed on the regulator to assess performance under various operating conditions. The preliminary test results indicated that the regulator can regulate helium to a stable outlet pressure of 740 psig within the +/- 5% tolerance band and maintain a lock-up pressure less than +5% for all tests conducted. Numerous leak tests demonstrated leakage less than 10-3 standard cubic centimeters per second (SCCS) for internal seat leakage at lock-up and less than10-5 SCCS for external leakage through the regulator ambient reference cavity. The successful tests have shown the potential for 10,000 psig helium systems in NASA spacecraft and have reduced risk

Terapascal static pressure generation with ultrahigh yield strength nanodiamond.

Science.gov (United States)

Dubrovinskaia, Natalia; Dubrovinsky, Leonid; Solopova, Natalia A; Abakumov, Artem; Turner, Stuart; Hanfland, Michael; Bykova, Elena; Bykov, Maxim; Prescher, Clemens; Prakapenka, Vitali B; Petitgirard, Sylvain; Chuvashova, Irina; Gasharova, Biliana; Mathis, Yves-Laurent; Ershov, Petr; Snigireva, Irina; Snigirev, Anatoly

2016-07-01

Studies of materials' properties at high and ultrahigh pressures lead to discoveries of unique physical and chemical phenomena and a deeper understanding of matter. In high-pressure research, an achievable static pressure limit is imposed by the strength of available strong materials and design of high-pressure devices. Using a high-pressure and high-temperature technique, we synthesized optically transparent microballs of bulk nanocrystalline diamond, which were found to have an exceptional yield strength (~460 GPa at a confining pressure of ~70 GPa) due to the unique microstructure of bulk nanocrystalline diamond. We used the nanodiamond balls in a double-stage diamond anvil cell high-pressure device that allowed us to generate static pressures beyond 1 TPa, as demonstrated by synchrotron x-ray diffraction. Outstanding mechanical properties (strain-dependent elasticity, very high hardness, and unprecedented yield strength) make the nanodiamond balls a unique device for ultrahigh static pressure generation. Structurally isotropic, homogeneous, and made of a low-Z material, they are promising in the field of x-ray optical applications.

Similarity measures for face recognition

CERN Document Server

Vezzetti, Enrico

2015-01-01

Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

Directory of Open Access Journals (Sweden)

Hiroshi Saruwatari

2007-01-01

Full Text Available We present the use of stethoscope and silicon NAM (nonaudible murmur microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible speech, but also very quietly uttered speech (nonaudible murmur. As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc. for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a 93.9% word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Industry-relevant magnetron sputtering and cathodic arc ultra-high vacuum deposition system for in situ x-ray diffraction studies of thin film growth using high energy synchrotron radiation.

Science.gov (United States)

Schroeder, J L; Thomson, W; Howard, B; Schell, N; Näslund, L-Å; Rogström, L; Johansson-Jõesaar, M P; Ghafoor, N; Odén, M; Nothnagel, E; Shepard, A; Greer, J; Birch, J

2015-09-01

We present an industry-relevant, large-scale, ultra-high vacuum (UHV) magnetron sputtering and cathodic arc deposition system purposefully designed for time-resolved in situ thin film deposition/annealing studies using high-energy (>50 keV), high photon flux (>10(12) ph/s) synchrotron radiation. The high photon flux, combined with a fast-acquisition-time (film formation processes. The high-energy synchrotron-radiation based x-rays result in small scattering angles (industry-relevant processes. We openly encourage the materials research community to contact us for collaborative opportunities using this unique and versatile scientific instrument.

Textual emotion recognition for enhancing enterprise computing

Science.gov (United States)

Quan, Changqin; Ren, Fuji

2016-05-01

The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

Fluid pipeline system leak detection based on neural network and pattern recognition

International Nuclear Information System (INIS)

Tang Xiujia

1998-01-01

The mechanism of the stress wave propagation along the pipeline system of NPP, caused by turbulent ejection from pipeline leakage, is researched. A series of characteristic index are described in time domain or frequency domain, and compress numerical algorithm is developed for original data compression. A back propagation neural networks (BPNN) with the input matrix composed by stress wave characteristics in time domain or frequency domain is first proposed to classify various situations of the pipeline, in order to detect the leakage in the fluid flow pipelines. The capability of the new method had been demonstrated by experiments and finally used to design a handy instrument for the pipeline leakage detection. Usually a pipeline system has many inner branches and often in adjusting dynamic condition, it is difficult for traditional pipeline diagnosis facilities to identify the difference between inner pipeline operation and pipeline fault. The author first proposed pipeline wave propagation identification by pattern recognition to diagnose pipeline leak. A series of pattern primitives such as peaks, valleys, horizon lines, capstan peaks, dominant relations, slave relations, etc., are used to extract features of the negative pressure wave form. The context-free grammar of symbolic representation of the negative wave form is used, and a negative wave form parsing system with application to structural pattern recognition based on the representation is first proposed to detect and localize leaks of the fluid pipelines

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.

A food recognition system for diabetic patients based on an optimized bag-of-features model.

Science.gov (United States)

Anthimopoulos, Marios M; Gianola, Lauro; Scarnato, Luca; Diem, Peter; Mougiakakou, Stavroula G

2014-07-01

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the bag-of-features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

A Monte-Carlo simulation of the equilibrium beam polarization in ultra-high energy electron (positron) storage rings

Energy Technology Data Exchange (ETDEWEB)

Duan, Zhe, E-mail: zhe.duan@ihep.ac.cn [Key Laboratory of Particle Acceleration Physics and Technology, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing (China); University of Chinese Academy of Sciences, 100049 Beijing (China); Bai, Mei [Forschungszentrum Jülich GmbH, 52428 Jülich (Germany); Barber, Desmond P. [Deutsches Elektronen-Synchrotron, DESY, 22607 Hamburg (Germany); Qin, Qing [Key Laboratory of Particle Acceleration Physics and Technology, Institute of High Energy Physics, Chinese Academy of Sciences, 100049 Beijing (China)

2015-09-01

With the recently emerging global interest in building a next generation of circular electron–positron colliders to study the properties of the Higgs boson, and other important topics in particle physics at ultra-high beam energies, it is also important to pursue the possibility of implementing polarized beams at this energy scale. It is therefore necessary to set up simulation tools to evaluate the beam polarization at these ultra-high beam energies. In this paper, a Monte-Carlo simulation of the equilibrium beam polarization based on the Polymorphic Tracking Code (PTC) (Schmidt et al., 2002 [1]) is described. The simulations are for a model storage ring with parameters similar to those of proposed circular colliders in this energy range, and they are compared with the suggestion (Derbenev et al., 1979 [2]) that there are different regimes for the spin dynamics underlying the polarization of a beam in the presence of synchrotron radiation at ultra-high beam energies. In particular, it has been suggested that the so-called “correlated” crossing of spin resonances during synchrotron oscillations at current energies evolves into “uncorrelated” crossing of spin resonances at ultra-high energies.

A Monte-Carlo simulation of the equilibrium beam polarization in ultra-high energy electron (positron) storage rings

International Nuclear Information System (INIS)

Duan, Zhe; Bai, Mei; Barber, Desmond P.; Qin, Qing

2015-04-01

With the recently emerging global interest in building a next generation of circular electron-positron colliders to study the properties of the Higgs boson, and other important topics in particle physics at ultra-high beam energies, it is also important to pursue the possibility of implementing polarized beams at this energy scale. It is therefore necessary to set up simulation tools to evaluate the beam polarization at these ultra-high beam energies. In this paper, a Monte-Carlo simulation of the equilibrium beam polarization based on the Polymorphic Tracking Code(PTC) (Schmidt et al., 2002) is described. The simulations are for a model storage ring with parameters similar to those of proposed circular colliders in this energy range, and they are compared with the suggestion (Derbenev et al., 1978) that there are different regimes for the spin dynamics underlying the polarization of a beam in the presence of synchrotron radiation at ultra-high beam energies. In particular, it has been suggested that the so-called ''correlated'' crossing of spin resonances during synchrotron oscillations at current energies, evolves into ''uncorrelated'' crossing of spin resonances at ultra-high energies.

Proton-proton elastic scattering at ultrahigh energies

International Nuclear Information System (INIS)

Saleem, M.; Shaukat, M.A.; Fazal-e-Aleem