Speech Silicon: An FPGA Architecture for Real-Time Hidden Markov-Model-Based Speech Recognition

Directory of Open Access Journals (Sweden)

Alex K. Jones

2006-11-01

Full Text Available This paper examines the design of an FPGA-based system-on-a-chip capable of performing continuous speech recognition on medium sized vocabularies in real time. Through the creation of three dedicated pipelines, one for each of the major operations in the system, we were able to maximize the throughput of the system while simultaneously minimizing the number of pipeline stalls in the system. Further, by implementing a token-passing scheme between the later stages of the system, the complexity of the control was greatly reduced and the amount of active data present in the system at any time was minimized. Additionally, through in-depth analysis of the SPHINX 3 large vocabulary continuous speech recognition engine, we were able to design models that could be efficiently benchmarked against a known software platform. These results, combined with the ability to reprogram the system for different recognition tasks, serve to create a system capable of performing real-time speech recognition in a vast array of environments.

Improving on hidden Markov models: An articulatorily constrained, maximum likelihood approach to speech recognition and speech coding

Energy Technology Data Exchange (ETDEWEB)

Hogden, J.

1996-11-05

The goal of the proposed research is to test a statistical model of speech recognition that incorporates the knowledge that speech is produced by relatively slow motions of the tongue, lips, and other speech articulators. This model is called Maximum Likelihood Continuity Mapping (Malcom). Many speech researchers believe that by using constraints imposed by articulator motions, we can improve or replace the current hidden Markov model based speech recognition algorithms. Unfortunately, previous efforts to incorporate information about articulation into speech recognition algorithms have suffered because (1) slight inaccuracies in our knowledge or the formulation of our knowledge about articulation may decrease recognition performance, (2) small changes in the assumptions underlying models of speech production can lead to large changes in the speech derived from the models, and (3) collecting measurements of human articulator positions in sufficient quantity for training a speech recognition algorithm is still impractical. The most interesting (and in fact, unique) quality of Malcom is that, even though Malcom makes use of a mapping between acoustics and articulation, Malcom can be trained to recognize speech using only acoustic data. By learning the mapping between acoustics and articulation using only acoustic data, Malcom avoids the difficulties involved in collecting articulator position measurements and does not require an articulatory synthesizer model to estimate the mapping between vocal tract shapes and speech acoustics. Preliminary experiments that demonstrate that Malcom can learn the mapping between acoustics and articulation are discussed. Potential applications of Malcom aside from speech recognition are also discussed. Finally, specific deliverables resulting from the proposed research are described.

TreeRipper web application: towards a fully automated optical tree recognition software

Directory of Open Access Journals (Sweden)

Hughes Joseph

2011-05-01

Full Text Available Abstract Background Relationships between species, genes and genomes have been printed as trees for over a century. Whilst this may have been the best format for exchanging and sharing phylogenetic hypotheses during the 20th century, the worldwide web now provides faster and automated ways of transferring and sharing phylogenetic knowledge. However, novel software is needed to defrost these published phylogenies for the 21st century. Results TreeRipper is a simple website for the fully-automated recognition of multifurcating phylogenetic trees (http://linnaeus.zoology.gla.ac.uk/~jhughes/treeripper/. The program accepts a range of input image formats (PNG, JPG/JPEG or GIF. The underlying command line c++ program follows a number of cleaning steps to detect lines, remove node labels, patch-up broken lines and corners and detect line edges. The edge contour is then determined to detect the branch length, tip label positions and the topology of the tree. Optical Character Recognition (OCR is used to convert the tip labels into text with the freely available tesseract-ocr software. 32% of images meeting the prerequisites for TreeRipper were successfully recognised, the largest tree had 115 leaves. Conclusions Despite the diversity of ways phylogenies have been illustrated making the design of a fully automated tree recognition software difficult, TreeRipper is a step towards automating the digitization of past phylogenies. We also provide a dataset of 100 tree images and associated tree files for training and/or benchmarking future software. TreeRipper is an open source project licensed under the GNU General Public Licence v3.

The Hidden Cost of Buying a Computer.

Science.gov (United States)

Johnson, Michael

1983-01-01

In order to process data in a computer, application software must be either developed or purchased. Costs for modifications of the software package and maintenance are often hidden. The decision to buy or develop software packages should be based upon factors of time and maintenance. (MLF)

Behavioral biometrics for verification and recognition of malicious software agents

Science.gov (United States)

Yampolskiy, Roman V.; Govindaraju, Venu

2008-04-01

Homeland security requires technologies capable of positive and reliable identification of humans for law enforcement, government, and commercial applications. As artificially intelligent agents improve in their abilities and become a part of our everyday life, the possibility of using such programs for undermining homeland security increases. Virtual assistants, shopping bots, and game playing programs are used daily by millions of people. We propose applying statistical behavior modeling techniques developed by us for recognition of humans to the identification and verification of intelligent and potentially malicious software agents. Our experimental results demonstrate feasibility of such methods for both artificial agent verification and even for recognition purposes.

Syntactic and semantic errors in radiology reports associated with speech recognition software.

Science.gov (United States)

Ringler, Michael D; Goss, Brian C; Bartholmai, Brian J

2017-03-01

Speech recognition software can increase the frequency of errors in radiology reports, which may affect patient care. We retrieved 213,977 speech recognition software-generated reports from 147 different radiologists and proofread them for errors. Errors were classified as "material" if they were believed to alter interpretation of the report. "Immaterial" errors were subclassified as intrusion/omission or spelling errors. The proportion of errors and error type were compared among individual radiologists, imaging subspecialty, and time periods. In all, 20,759 reports (9.7%) contained errors, of which 3992 (1.9%) were material errors. Among immaterial errors, spelling errors were more common than intrusion/omission errors ( p reports, reports reinterpreting results of outside examinations, and procedural studies (all p < .001). Error rate decreased over time ( p < .001), which suggests that a quality control program with regular feedback may reduce errors.

Hidden Markov models for labeled sequences

DEFF Research Database (Denmark)

Krogh, Anders Stærmose

1994-01-01

A hidden Markov model for labeled observations, called a class HMM, is introduced and a maximum likelihood method is developed for estimating the parameters of the model. Instead of training it to model the statistics of the training sequences it is trained to optimize recognition. It resembles MMI...

A Multilayer Hidden Markov Models-Based Method for Human-Robot Interaction

Directory of Open Access Journals (Sweden)

Chongben Tao

2013-01-01

Full Text Available To achieve Human-Robot Interaction (HRI by using gestures, a continuous gesture recognition approach based on Multilayer Hidden Markov Models (MHMMs is proposed, which consists of two parts. One part is gesture spotting and segment module, the other part is continuous gesture recognition module. Firstly, a Kinect sensor is used to capture 3D acceleration and 3D angular velocity data of hand gestures. And then, a Feed-forward Neural Networks (FNNs and a threshold criterion are used for gesture spotting and segment, respectively. Afterwards, the segmented gesture signals are respectively preprocessed and vector symbolized by a sliding window and a K-means clustering method. Finally, symbolized data are sent into Lower Hidden Markov Models (LHMMs to identify individual gestures, and then, a Bayesian filter with sequential constraints among gestures in Upper Hidden Markov Models (UHMMs is used to correct recognition errors created in LHMMs. Five predefined gestures are used to interact with a Kinect mobile robot in experiments. The experimental results show that the proposed method not only has good effectiveness and accuracy, but also has favorable real-time performance.

Voice recognition software can be used for scientific articles

DEFF Research Database (Denmark)

Pommergaard, Hans-Christian; Huang, Chenxi; Burcharth, Jacob

2015-01-01

INTRODUCTION: Dictation of scientific articles has been recognised as an efficient method for producing high-quality, first article drafts. However, standardised transcription service by a secretary may not be available for all researchers and voice recognition software (VRS) may therefore...... be an alternative. The purpose of this study was to evaluate the out-of-the-box accuracy of VRS. METHODS: Eleven young researchers without dictation experience dictated the first draft of their own scientific article after thorough preparation according to a pre-defined schedule. The dictate transcribed by VRS...

Distinguishing Hidden Markov Chains

OpenAIRE

Kiefer, Stefan; Sistla, A. Prasad

2015-01-01

Hidden Markov Chains (HMCs) are commonly used mathematical models of probabilistic systems. They are employed in various fields such as speech recognition, signal processing, and biological sequence analysis. We consider the problem of distinguishing two given HMCs based on an observation sequence that one of the HMCs generates. More precisely, given two HMCs and an observation sequence, a distinguishing algorithm is expected to identify the HMC that generates the observation sequence. Two HM...

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.

Mining Bug Databases for Unidentified Software Vulnerabilities

Energy Technology Data Exchange (ETDEWEB)

Dumidu Wijayasekara; Milos Manic; Jason Wright; Miles McQueen

2012-06-01

Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses the feasibility and necessity to mine common publicly available bug databases for vulnerabilities that are yet to be identified. We present bug database analysis of two well known and frequently used software packages, namely Linux kernel and MySQL. It is shown that for both Linux and MySQL, a significant portion of vulnerabilities that were discovered for the time period from January 2006 to April 2011 were hidden impact vulnerabilities. It is also shown that the percentage of hidden impact vulnerabilities has increased in the last two years, for both software packages. We then propose an improved hidden impact vulnerability identification methodology based on text mining bug databases, and conclude by discussing a few potential problems faced by such a classifier.

Hand Gesture Modeling and Recognition for Human and Robot Interactive Assembly Using Hidden Markov Models

Directory of Open Access Journals (Sweden)

Fei Chen

2015-04-01

Full Text Available Gesture recognition is essential for human and robot collaboration. Within an industrial hybrid assembly cell, the performance of such a system significantly affects the safety of human workers. This work presents an approach to recognizing hand gestures accurately during an assembly task while in collaboration with a robot co-worker. We have designed and developed a sensor system for measuring natural human-robot interactions. The position and rotation information of a human worker's hands and fingertips are tracked in 3D space while completing a task. A modified chain-code method is proposed to describe the motion trajectory of the measured hands and fingertips. The Hidden Markov Model (HMM method is adopted to recognize patterns via data streams and identify workers' gesture patterns and assembly intentions. The effectiveness of the proposed system is verified by experimental results. The outcome demonstrates that the proposed system is able to automatically segment the data streams and recognize the gesture patterns thus represented with a reasonable accuracy ratio.

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

Modular Algorithm Testbed Suite (MATS): A Software Framework for Automatic Target Recognition

Science.gov (United States)

2017-01-01

NAVAL SURFACE WARFARE CENTER PANAMA CITY DIVISION PANAMA CITY, FL 32407-7001 TECHNICAL REPORT NSWC PCD TR-2017-004 MODULAR ...31-01-2017 Technical Modular Algorithm Testbed Suite (MATS): A Software Framework for Automatic Target Recognition DR...flexible platform to facilitate the development and testing of ATR algorithms. To that end, NSWC PCD has created the Modular Algorithm Testbed Suite

Hidden Markov model analysis reveals the advantage of analytic eye movement patterns in face recognition across cultures.

Science.gov (United States)

Chuk, Tim; Crookes, Kate; Hayward, William G; Chan, Antoni B; Hsiao, Janet H

2017-12-01

It remains controversial whether culture modulates eye movement behavior in face recognition. Inconsistent results have been reported regarding whether cultural differences in eye movement patterns exist, whether these differences affect recognition performance, and whether participants use similar eye movement patterns when viewing faces from different ethnicities. These inconsistencies may be due to substantial individual differences in eye movement patterns within a cultural group. Here we addressed this issue by conducting individual-level eye movement data analysis using hidden Markov models (HMMs). Each individual's eye movements were modeled with an HMM. We clustered the individual HMMs according to their similarities and discovered three common patterns in both Asian and Caucasian participants: holistic (looking mostly at the face center), left-eye-biased analytic (looking mostly at the two individual eyes in addition to the face center with a slight bias to the left eye), and right-eye-based analytic (looking mostly at the right eye in addition to the face center). The frequency of participants adopting the three patterns did not differ significantly between Asians and Caucasians, suggesting little modulation from culture. Significantly more participants (75%) showed similar eye movement patterns when viewing own- and other-race faces than different patterns. Most importantly, participants with left-eye-biased analytic patterns performed significantly better than those using either holistic or right-eye-biased analytic patterns. These results suggest that active retrieval of facial feature information through an analytic eye movement pattern may be optimal for face recognition regardless of culture. Copyright © 2017 Elsevier B.V. All rights reserved.

Computerized literature reference system: use of an optical scanner and optical character recognition software.

Science.gov (United States)

Lossef, S V; Schwartz, L H

1990-09-01

A computerized reference system for radiology journal articles was developed by using an IBM-compatible personal computer with a hand-held optical scanner and optical character recognition software. This allows direct entry of scanned text from printed material into word processing or data-base files. Additionally, line diagrams and photographs of radiographs can be incorporated into these files. A text search and retrieval software program enables rapid searching for keywords in scanned documents. The hand scanner and software programs are commercially available, relatively inexpensive, and easily used. This permits construction of a personalized radiology literature file of readily accessible text and images requiring minimal typing or keystroke entry.

Hidden Neural Networks: A Framework for HMM/NN Hybrids

DEFF Research Database (Denmark)

Riis, Søren Kamaric; Krogh, Anders Stærmose

1997-01-01

This paper presents a general framework for hybrids of hidden Markov models (HMM) and neural networks (NN). In the new framework called hidden neural networks (HNN) the usual HMM probability parameters are replaced by neural network outputs. To ensure a probabilistic interpretation the HNN is nor...... HMMs on TIMIT continuous speech recognition benchmarks. On the task of recognizing five broad phoneme classes an accuracy of 84% is obtained compared to 76% for a standard HMM. Additionally, we report a preliminary result of 69% accuracy on the TIMIT 39 phoneme task...

Utterance independent bimodal emotion recognition in spontaneous communication

Science.gov (United States)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

The Consensus String Problem and the Complexity of Comparing Hidden Markov Models

DEFF Research Database (Denmark)

Lyngsø, Rune Bang; Pedersen, Christian Nørgaard Storm

2002-01-01

The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing......-norms. We discuss the applicability of the technique used for proving the hardness of comparing two hidden Markov models under the L1-norm to other measures of distance between probability distributions. In particular, we show that it cannot be used for proving NP-hardness of determining the Kullback...

The Consensus String Problem and the Complexity of Comparing Hidden Markov Models

DEFF Research Database (Denmark)

Lyngsø, Rune Bang; Pedersen, Christian Nørgaard Storm

2002-01-01

The basic theory of hidden Markov models was developed and applied to problems in speech recognition in the late 1960s, and has since then been applied to numerous problems, e.g. biological sequence analysis. Most applications of hidden Markov models are based on efficient algorithms for computing...... the probability of generating a given string, or computing the most likely path generating a given string. In this paper we consider the problem of computing the most likely string, or consensus string, generated by a given model, and its implications on the complexity of comparing hidden Markov models. We show...... that computing the consensus string, and approximating its probability within any constant factor, is NP-hard, and that the same holds for the closely related labeling problem for class hidden Markov models. Furthermore, we establish the NP-hardness of comparing two hidden Markov models under the L∞- and L1...

Discriminative training of self-structuring hidden control neural models

DEFF Research Database (Denmark)

Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben

1995-01-01

This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...... we developed a discriminative training algorithm for SHC models, where each SHC model for a specific speech pattern is trained with utterances of the pattern to be recognized and with other utterances. The discriminative training of SHC neural models has been tested on the TIDIGITS database...

Application of neural network and pattern recognition software to the automated analysis of continuous nuclear monitoring of on-load reactors

Energy Technology Data Exchange (ETDEWEB)

Howell, J.A.; Eccleston, G.W.; Halbig, J.K.; Klosterbuer, S.F. [Los Alamos National Lab., NM (United States); Larson, T.W. [California Polytechnic State Univ., San Luis Obispo, CA (US)

1993-08-01

Automated analysis using pattern recognition and neural network software can help interpret data, call attention to potential anomalies, and improve safeguards effectiveness. Automated software analysis, based on pattern recognition and neural networks, was applied to data collected from a radiation core discharge monitor system located adjacent to an on-load reactor core. Unattended radiation sensors continuously collect data to monitor on-line refueling operations in the reactor. The huge volume of data collected from a number of radiation channels makes it difficult for a safeguards inspector to review it all, check for consistency among the measurement channels, and find anomalies. Pattern recognition and neural network software can analyze large volumes of data from continuous, unattended measurements, thereby improving and automating the detection of anomalies. The authors developed a prototype pattern recognition program that determines the reactor power level and identifies the times when fuel bundles are pushed through the core during on-line refueling. Neural network models were also developed to predict fuel bundle burnup to calculate the region on the on-load reactor face from which fuel bundles were discharged based on the radiation signals. In the preliminary data set, which was limited and consisted of four distinct burnup regions, the neural network model correctly predicted the burnup region with an accuracy of 92%.

Extended abstract of a hidden agenda

Energy Technology Data Exchange (ETDEWEB)

Goguen, J.; Malcolm, G. [Oxford Univ. (United Kingdom)

1996-12-31

The initial goal of our hidden research programme was both straightforward and ambitious: give a semantics for software engineering, and in particular for the object paradigm, supporting correctness proofs that are as simple and mechanical as possible. This emphasizes proofs rather than models, and thus suggests an equational approach, rather than one based on higher order logic, denotational semantics, or any kind of model, because equational proofs achieve maximal simplicity and mechanization, and yet are fully expressive. We introduce powerful coinduction techniques for proving behavioral properties of complex systems. We make the no doubt outrageous claim that our hidden approach gives simpler proofs than other formalisms; this is because we exploit algebraic structure that most other approaches discard.

Hidden histories: challenges for pedagogy and participation

OpenAIRE

Morrice, Linda

2013-01-01

Higher Education has become and an increasingly diverse and globalised system in which the binaries between ‘traditional’ and ‘non-traditional’ students, exclusion and inclusion have less resonance and analytical purchase. Drawing on research with refugees Linda will suggest that higher education can be marked simultaneously by belonging and recognition, deficit and exclusion. Complex differences and inequalities remain hidden and unspoken, raising new questions and challenges for pedagogy an...

Facial recognition software success rates for the identification of 3D surface reconstructed facial images: implications for patient privacy and security.

Science.gov (United States)

Mazura, Jan C; Juluru, Krishna; Chen, Joseph J; Morgan, Tara A; John, Majnu; Siegel, Eliot L

2012-06-01

Image de-identification has focused on the removal of textual protected health information (PHI). Surface reconstructions of the face have the potential to reveal a subject's identity even when textual PHI is absent. This study assessed the ability of a computer application to match research subjects' 3D facial reconstructions with conventional photographs of their face. In a prospective study, 29 subjects underwent CT scans of the head and had frontal digital photographs of their face taken. Facial reconstructions of each CT dataset were generated on a 3D workstation. In phase 1, photographs of the 29 subjects undergoing CT scans were added to a digital directory and tested for recognition using facial recognition software. In phases 2-4, additional photographs were added in groups of 50 to increase the pool of possible matches and the test for recognition was repeated. As an internal control, photographs of all subjects were tested for recognition against an identical photograph. Of 3D reconstructions, 27.5% were matched correctly to corresponding photographs (95% upper CL, 40.1%). All study subject photographs were matched correctly to identical photographs (95% lower CL, 88.6%). Of 3D reconstructions, 96.6% were recognized simply as a face by the software (95% lower CL, 83.5%). Facial recognition software has the potential to recognize features on 3D CT surface reconstructions and match these with photographs, with implications for PHI.

Discriminative learning for speech recognition

CERN Document Server

He, Xiadong

2008-01-01

In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

Character Recognition Using Genetically Trained Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

1998-10-01

Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

Enhanced Map-Matching Algorithm with a Hidden Markov Model for Mobile Phone Positioning

Directory of Open Access Journals (Sweden)

An Luo

2017-10-01

Full Text Available Numerous map-matching techniques have been developed to improve positioning, using Global Positioning System (GPS data and other sensors. However, most existing map-matching algorithms process GPS data with high sampling rates, to achieve a higher correct rate and strong universality. This paper introduces a novel map-matching algorithm based on a hidden Markov model (HMM for GPS positioning and mobile phone positioning with a low sampling rate. The HMM is a statistical model well known for providing solutions to temporal recognition applications such as text and speech recognition. In this work, the hidden Markov chain model was built to establish a map-matching process, using the geometric data, the topologies matrix of road links in road network and refined quad-tree data structure. HMM-based map-matching exploits the Viterbi algorithm to find the optimized road link sequence. The sequence consists of hidden states in the HMM model. The HMM-based map-matching algorithm is validated on a vehicle trajectory using GPS and mobile phone data. The results show a significant improvement in mobile phone positioning and high and low sampling of GPS data.

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

Science.gov (United States)

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

2011-03-31

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

Fault Diagnosis of Car Engine by Using a Novel GA-Based Extension Recognition Method

Directory of Open Access Journals (Sweden)

Meng-Hui Wang

2014-01-01

Full Text Available Due to the passenger’s security, the recognized hidden faults in car engines are the most important work for a maintenance engineer, so they can regulate the engines to be safe and improve the reliability of automobile systems. In this paper, we will present a novel fault recognition method based on the genetic algorithm (GA and the extension theory and also apply this method to the fault recognition of a practical car engine. The proposed recognition method has been tested on the Nissan Cefiro 2.0 engine and has also been compared to other traditional classification methods. Experimental results are of great effect regarding the hidden fault recognition of car engines, and the proposed method can also be applied to other industrial apparatus.

Use of voice recognition software in an outpatient pediatric specialty practice.

Science.gov (United States)

Issenman, Robert M; Jaffer, Iqbal H

2004-09-01

Voice recognition software (VRS), with specialized medical vocabulary, is being promoted to enhance physician efficiency, decrease costs, and improve patient safety. This study reports the experience of a pediatric subspecialist (pediatric gastroenterology) physician with the use of Dragon Naturally Speaking (version 6; ScanSoft Inc, Peabody, MA), incorporated for use with a proprietary electronic medical record, in a large university medical center ambulatory care service. After 2 hours of group orientation and 2 hours of individual VRS instruction, the physician trained the software for 1 month (30 letters) during a hospital slowdown. Set-up, dictation, and correction times for the physician and medical transcriptionist were recorded for these training sessions, as well as for 42 subsequently dictated letters. Figures were extrapolated to the yearly clinic volume for the physician, to estimate costs (physician: 110 dollars per hour; transcriptionist: 11 dollars per hour, US dollars). The use of VRS required an additional 200% of physician dictation and correction time (9 minutes vs 3 minutes), compared with the use of electronic signatures for letters typed by an experienced transcriptionist and imported into the electronic medical record. When the cost of the license agreement and the costs of physician and transcriptionist time were included, the use of the software cost 100% more, for the amount of dictation performed annually by the physician. VRS is an intriguing technology. It holds the possibility of streamlining medical practice. However, the learning curve and accuracy of the tested version of the software limit broad physician acceptance at this time.

Epigenetic change detection and pattern recognition via Bayesian hierarchical hidden Markov models.

Science.gov (United States)

Wang, Xinlei; Zang, Miao; Xiao, Guanghua

2013-06-15

Epigenetics is the study of changes to the genome that can switch genes on or off and determine which proteins are transcribed without altering the DNA sequence. Recently, epigenetic changes have been linked to the development and progression of disease such as psychiatric disorders. High-throughput epigenetic experiments have enabled researchers to measure genome-wide epigenetic profiles and yield data consisting of intensity ratios of immunoprecipitation versus reference samples. The intensity ratios can provide a view of genomic regions where protein binding occur under one experimental condition and further allow us to detect epigenetic alterations through comparison between two different conditions. However, such experiments can be expensive, with only a few replicates available. Moreover, epigenetic data are often spatially correlated with high noise levels. In this paper, we develop a Bayesian hierarchical model, combined with hidden Markov processes with four states for modeling spatial dependence, to detect genomic sites with epigenetic changes from two-sample experiments with paired internal control. One attractive feature of the proposed method is that the four states of the hidden Markov process have well-defined biological meanings and allow us to directly call the change patterns based on the corresponding posterior probabilities. In contrast, none of existing methods can offer this advantage. In addition, the proposed method offers great power in statistical inference by spatial smoothing (via hidden Markov modeling) and information pooling (via hierarchical modeling). Both simulation studies and real data analysis in a cocaine addiction study illustrate the reliability and success of this method. Copyright © 2012 John Wiley & Sons, Ltd.

Learning to Automatically Detect Features for Mobile Robots Using Second-Order Hidden Markov Models

Directory of Open Access Journals (Sweden)

Olivier Aycard

2004-12-01

Full Text Available In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T-intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.

Hidden Markov Model Application to Transfer The Trader Online Forex Brokers

Directory of Open Access Journals (Sweden)

Farida Suharleni

2012-05-01

Full Text Available Hidden Markov Model is elaboration of Markov chain, which is applicable to cases that can’t directly observe. In this research, Hidden Markov Model is used to know trader’s transition to broker forex online. In Hidden Markov Model, observed state is observable part and hidden state is hidden part. Hidden Markov Model allows modeling system that contains interrelated observed state and hidden state. As observed state in trader’s transition to broker forex online is category 1, category 2, category 3, category 4, category 5 by condition of every broker forex online, whereas as hidden state is broker forex online Marketiva, Masterforex, Instaforex, FBS and Others. First step on application of Hidden Markov Model in this research is making construction model by making a probability of transition matrix (A from every broker forex online. Next step is making a probability of observation matrix (B by making conditional probability of five categories, that is category 1, category 2, category 3, category 4, category 5 by condition of every broker forex online and also need to determine an initial state probability (π from every broker forex online. The last step is using Viterbi algorithm to find hidden state sequences that is broker forex online sequences which is the most possible based on model and observed state that is the five categories. Application of Hidden Markov Model is done by making program with Viterbi algorithm using Delphi 7.0 software with observed state based on simulation data. Example: By the number of observation T = 5 and observed state sequences O = (2,4,3,5,1 is found hidden state sequences which the most possible with observed state O as following : where X1 = FBS, X2 = Masterforex, X3 = Marketiva, X4 = Others, and X5 = Instaforex.

Voice recognition software can be used for scientific articles.

Science.gov (United States)

Pommergaard, Hans-Christian; Huang, Chenxi; Burcharth, Jacob; Rosenberg, Jacob

2015-02-01

Dictation of scientific articles has been recognised as an efficient method for producing high-quality, first article drafts. However, standardised transcription service by a secretary may not be available for all researchers and voice recognition software (VRS) may therefore be an alternative. The purpose of this study was to evaluate the out-of-the-box accuracy of VRS. Eleven young researchers without dictation experience dictated the first draft of their own scientific article after thorough preparation according to a pre-defined schedule. The dictate transcribed by VRS was compared with the same dictate transcribed by an experienced research secretary, and the effect of adding words to the vocabulary of the VRS was investigated. The number of errors per hundred words was used as outcome. Furthermore, three experienced researchers assessed the subjective readability using a Likert scale (0-10). Dragon Nuance Premium version 12.5 was used as VRS. The median number of errors per hundred words was 18 (range: 8.5-24.3), which improved when 15,000 words were added to the vocabulary. Subjective readability assessment showed that the texts were understandable with a median score of five (range: 3-9), which was improved with the addition of 5,000 words. The out-of-the-box performance of VRS was acceptable and improved after additional words were added. Further studies are needed to investigate the effect of additional software accuracy training.

DISEÑO Y MANIPULACIÓN DE MODELOS OCULTOS DE MARKOV, UTILIZANDO HERRAMIENTAS HTK: UNA TUTORÍA DESIGN AND MANIPULATION OF HIDDEN MARKOV MODELS USING HTK TOOLS: A TUTORIAL

Directory of Open Access Journals (Sweden)

Roberto Carrillo Aguilar

2007-04-01

Full Text Available Este trabajo da a conocer el sistema de desarrollo de software para el diseño y manipulación de modelos ocultos de Markov, denominado HTK. Actualmente, la técnica de modelos ocultos de Markov es la herramienta más efectiva para implementar sistemas reconocedores del habla. HTK está orientado principalmente a ese aspecto. Su arquitectura es robusta y autosuficiente. Permite: la entrada lógica y natural desde un micrófono, dispone de módulos para la conversión A/D, preprocesado y parametrización de la información, posee herramientas para definir y manipular modelos ocultos de Markov, tiene librerías para entrenamiento y manipulación de los modelos ocultos de Markov ya definidos, considera funciones para definir la gramática, y además: Una serie de herramientas adicionales permiten lograr el objetivo final de obtener una hipotética transcripción del habla (conversión voz - texto.This paper presents HTK, a software development platform for the design and management of Hidden Markov Models. Nowadays, the Hidden Markov Models technique is the more effective one to implement voice recognition systems. HTK is mainly oriented to this application. Its architecture is robust and self-sufficient. It allows a natural input from a microphone, it has modules for A/D conversion, it allows pre-processing and parameterization of information, it possesses tools to define and manage the Hidden Markov Models, libraries for training and use the already defined Hidden Markov Models. It has functions to define the grammar and it has additional tools to reach the final objective, to obtain an hypothetical transcription of the talking (voice to text translation.

Hidden Liquidity

OpenAIRE

Cebiroglu, Gökhan; Horst, Ulrich

2012-01-01

We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stock’s hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that large hidden orders are associated with larger transaction costs, higher price impact and increased volatility. In particular, as large hidden orders fail to attract (latent) liquidity to the market, hi...

Parametric Hidden Markov Models for Recognition and Synthesis of Movements

DEFF Research Database (Denmark)

Herzog, Dennis; Krüger, Volker; Grest, Daniel

2008-01-01

In humanoid robotics, the recognition and synthesis of parametric movements plays an extraordinary role for robot human interaction. Such a parametric movement is a movement of a particular type (semantic), for example, similar pointing movements performed at different table-top positions....... For understanding the whole meaning of a movement of a human, the recognition of its type, likewise its parameterization are important. Only both together convey the whole meaning. Vice versa, for mimicry, the synthesis of movements for the motor control of a robot needs to be parameterized, e.g., by the relative...... the applicability for online recognition based on very noisy 3D tracking data. The use of a parametric representation of movements is shown in a robot demo, where a robot removes objects from a table as demonstrated by an advisor. The synthesis for motor control is performed for arbitrary table-top positions....

Speech to Text Software Evaluation Report

CERN Document Server

Martins Santo, Ana Luisa

2017-01-01

This document compares out-of-box performance of three commercially available speech recognition software: Vocapia VoxSigma TM , Google Cloud Speech, and Lime- craft Transcriber. It is defined a set of evaluation criteria and test methods for speech recognition softwares. The evaluation of these softwares in noisy environments are also included for the testing purposes. Recognition accuracy was compared using noisy environments and languages. Testing in ”ideal” non-noisy environment of a quiet room has been also performed for comparison.

Human ear recognition by computer

CERN Document Server

Bhanu, Bir; Chen, Hui

2010-01-01

Biometrics deals with recognition of individuals based on their physiological or behavioral characteristics. The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. Unlike the fingerprint and iris, it can be easily captured from a distance without a fully cooperative subject, although sometimes it may be hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively stable structure that does not change much with the age and facial expressions. ""Human Ear Recognition by Computer"" is the first book o

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.

Factors that motivate software developers in Nigerian's software ...

African Journals Online (AJOL)

It was also observed those courtesy, good reward systems, regular training, recognition, tolerance of mistakes and good leadership were high motivators of software developers. Keywords: Software developers, information technology, project managers, Nigeria International Journal of Natural and Applied Sciences, 6(4): ...

Sigma A recognition sites in the Bacillus subtilis genome

DEFF Research Database (Denmark)

Jarmer, Hanne Østergaard; Larsen, Thomas Schou; Krogh, Anders Stærmose

2001-01-01

A hidden Markov model of sigma (A) RNA polymerase cofactor recognition sites in Bacillus subtilis, containing either the common or the extended -10 motifs, has been constructed based on experimentally verified sigma (A) recognition sites. This work suggests that more information exists...... at the initiation site of transcription in both types of promoters than previously thought. When tested on the entire B. subtilis genome, the model predicts that approximately half of the sigma (A) recognition sites are of the extended type. Some of the response-regulator aspartate phosphatases were among...

Model-based recognition of 3-D objects by geometric hashing technique

International Nuclear Information System (INIS)

Severcan, M.; Uzunalioglu, H.

1992-09-01

A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs

Appropriate baseline values for HMM-based speech recognition

CSIR Research Space (South Africa)

Barnard, E

2004-11-01

Full Text Available A number of issues realted to the development of speech-recognition systems with Hidden Markov Models (HMM) are discussed. A set of systematic experiments using the HTK toolkit and the TMIT database are used to elucidate matters such as the number...

The Usefulness of Automatic Speech Recognition (ASR Eyespeak Software in Improving Iraqi EFL Students’ Pronunciation

Directory of Open Access Journals (Sweden)

Lina Fathi Sidig Sidgi

2017-02-01

Full Text Available The present study focuses on determining whether automatic speech recognition (ASR technology is reliable for improving English pronunciation to Iraqi EFL students. Non-native learners of English are generally concerned about improving their pronunciation skills, and Iraqi students face difficulties in pronouncing English sounds that are not found in their native language (Arabic. This study is concerned with ASR and its effectiveness in overcoming this difficulty. The data were obtained from twenty participants randomly selected from first-year college students at Al-Turath University College from the Department of English in Baghdad-Iraq. The students had participated in a two month pronunciation instruction course using ASR Eyespeak software. At the end of the pronunciation instruction course using ASR Eyespeak software, the students completed a questionnaire to get their opinions about the usefulness of the ASR Eyespeak in improving their pronunciation. The findings of the study revealed that the students found ASR Eyespeak software very useful in improving their pronunciation and helping them realise their pronunciation mistakes. They also reported that learning pronunciation with ASR Eyespeak enjoyable.

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-15

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

A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems

Directory of Open Access Journals (Sweden)

Ahmad Jalal

2017-08-01

Full Text Available Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR realizable for elderly healthcare applications. In this paper, a depth video-based novel method for HAR is presented using robust multi-features and embedded Hidden Markov Models (HMMs to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi-view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi-features are efficient and robust over the state of the art features for human action and activity recognition.

Kazakh Traditional Dance Gesture Recognition

Science.gov (United States)

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

2014-04-01

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

A model for abnormal activity recognition and alert generation system for elderly care by hidden conditional random fields using R-transform and generalized discriminant analysis features.

Science.gov (United States)

Khan, Zafar Ali; Sohn, Won

2012-10-01

The growing population of elderly people living alone increases the need for automatic healthcare monitoring systems for elderly care. Automatic vision sensor-based systems are increasingly used for human activity recognition (HAR) in recent years. This study presents an improved model, tested using actors, of a sensor-based HAR system to recognize daily life activities of elderly people at home and generate an alert in case of abnormal HAR. Datasets consisting of six abnormal activities (falling backward, falling forward, falling rightward, falling leftward, chest pain, and fainting) and four normal activities (walking, rushing, sitting down, and standing up) are generated from different view angles (90°, -90°, 45°, -45°). Feature extraction and dimensions reduction are performed by R-transform followed by generalized discriminant analysis (GDA) methods. R-transform extracts symmetric, scale, and translation-invariant features from the sequences of activities. GDA increases the discrimination between different classes of highly similar activities. Silhouette sequences are quantified by the Linde-Buzo-Gray algorithm and recognized by hidden conditional random fields. Experimental results provide an average recognition rate of 94.2% for abnormal activities and 92.7% for normal activities. The recognition rate for the highly similar activities from different view angles shows the flexibility and efficacy of the proposed abnormal HAR and alert generation system for elderly care.

A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

Directory of Open Access Journals (Sweden)

Ebenezer Out-Nyarko

2009-11-01

Full Text Available Using Hidden Markov Models (HMMs as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks.

A RECOGNITION METHOD FOR AIRPLANE TARGETS USING 3D POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

M. Zhou

2012-07-01

Full Text Available LiDAR is capable of obtaining three dimension coordinates of the terrain and targets directly and is widely applied in digital city, emergent disaster mitigation and environment monitoring. Especially because of its ability of penetrating the low density vegetation and canopy, LiDAR technique has superior advantages in hidden and camouflaged targets detection and recognition. Based on the multi-echo data of LiDAR, and combining the invariant moment theory, this paper presents a recognition method for classic airplanes (even hidden targets mainly under the cover of canopy using KD-Tree segmented point cloud data. The proposed algorithm firstly uses KD-tree to organize and manage point cloud data, and makes use of the clustering method to segment objects, and then the prior knowledge and invariant recognition moment are utilized to recognise airplanes. The outcomes of this test verified the practicality and feasibility of the method derived in this paper. And these could be applied in target measuring and modelling of subsequent data processing.

Sociology of Hidden Curriculum

Directory of Open Access Journals (Sweden)

Alireza Moradi

2017-06-01

Full Text Available This paper reviews the concept of hidden curriculum in the sociological theories and wants to explain sociological aspects of formation of hidden curriculum. The main question concentrates on the theoretical approaches in which hidden curriculum is explained sociologically.For this purpose it was applied qualitative research methodology. The relevant data include various sociological concepts and theories of hidden curriculum collected by the documentary method. The study showed a set of rules, procedures, relationships and social structure of education have decisive role in the formation of hidden curriculum. A hidden curriculum reinforces by existed inequalities among learners (based on their social classes or statues. There is, in fact, a balance between the learner's "knowledge receptions" with their "inequality proportion".The hidden curriculum studies from different major sociological theories such as Functionalism, Marxism and critical theory, Symbolic internationalism and Feminism. According to the functionalist perspective a hidden curriculum has a social function because it transmits social values. Marxists and critical thinkers correlate between hidden curriculum and the totality of social structure. They depicts that curriculum prepares learners for the exploitation in the work markets. Symbolic internationalism rejects absolute hegemony of hidden curriculum on education and looks to the socialization as a result of interaction between learner and instructor. Feminism theory also considers hidden curriculum as a vehicle which legitimates gender stereotypes.

Histogram equalization with Bayesian estimation for noise robust speech recognition.

Science.gov (United States)

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

Exemplar-based Parametric Hidden Markov Models for Recognition and Synthesis of Movements

DEFF Research Database (Denmark)

Herzog, Dennis; Krüger, Volker; Grest, Daniel

2007-01-01

A common problem in movement recognition is the recognition of movements of a particular type. E.g. pointing movements are of a particular type but differ in terms of the pointing direction. Arm movements with the goal of reaching out and grasping an object are of a particular type but differ...... are carried out through locally linear interpolation of the exemplar movements. Experiments are performed with pointing and grasping movements. Synthesis is done based on the object position as parameterization. In case of the recognition, the coordinates of the grasped or pointed at object are recovered. Our...

Page Recognition: Quantum Leap In Recognition Technology

Science.gov (United States)

Miller, Larry

1989-07-01

No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere

Caveats on Bayesian and hidden-Markov models (v2.8)

OpenAIRE

Schomaker, Lambert

2016-01-01

This paper describes a number of fundamental and practical problems in the application of hidden-Markov models and Bayes when applied to cursive-script recognition. Several problems, however, will have an effect in other application areas. The most fundamental problem is the propagation of error in the product of probabilities. This is a common and pervasive problem which deserves more attention. On the basis of Monte Carlo modeling, tables for the expected relative error are given. It seems ...

Hidden measurements, hidden variables and the volume representation of transition probabilities

OpenAIRE

Oliynyk, Todd A.

2005-01-01

We construct, for any finite dimension $n$, a new hidden measurement model for quantum mechanics based on representing quantum transition probabilities by the volume of regions in projective Hilbert space. For $n=2$ our model is equivalent to the Aerts sphere model and serves as a generalization of it for dimensions $n \\geq 3$. We also show how to construct a hidden variables scheme based on hidden measurements and we discuss how joint distributions arise in our hidden variables scheme and th...

Surveillance application using patten recognition software at the EBR-II Reactor Facility

International Nuclear Information System (INIS)

Olson, D.L.

1992-01-01

The System State Analyzer (SSA) is a software based pattern recognition system. For the past several year this system has been used at Argonne National Laboratory's Experimental Breeder Reactor 2 (EBR-2) reactor for detection of degradation and other abnormalities in plant systems. Currently there are two versions of the SSA being used at EBR-2. One version of SSA is used for daily surveillance and trending of the reactor delta-T and startups of the reactor. Another version of the SSA is the QSSA which is used to monitor individual systems of the reactor such as the Secondary Sodium System, Secondary Sodium Pumps, and Steam Generator. This system has been able to detect problems such as signals being affected by temperature variations due to a failing temperature controller

Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure

Directory of Open Access Journals (Sweden)

Shan Pang

2016-01-01

Full Text Available A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. Results show that, with optimized network structure, OM-ELM obtains better test accuracy in both applications and is more robust to sensor noise. Meanwhile it controls the model complexity and needs far less hidden nodes than multi-hidden-layer ELM, thus saving computer memory and making it more efficient to implement. All these advantages make our method an effective and reliable tool for engine component fault diagnosis tool.

Sensor-based Human Activity Recognition in a Multi-user Scenario

DEFF Research Database (Denmark)

Wang, Liang; Gu, Tao; Tao, Xianping

2009-01-01

Existing work on sensor-based activity recognition focuses mainly on single-user activities. However, in real life, activities are often performed by multiple users involving interactions between them. In this paper, we propose Coupled Hidden Markov Models (CHMMs) to recognize multi-user activiti...

A comparison study of support vector machines and hidden Markov models in machinery condition monitoring

International Nuclear Information System (INIS)

Miao, Qiang; Huang, Hong Zhong; Fan, Xianfeng

2007-01-01

Condition classification is an important step in machinery fault detection, which is a problem of pattern recognition. Currently, there are a lot of techniques in this area and the purpose of this paper is to investigate two popular recognition techniques, namely hidden Markov model and support vector machine. At the beginning, we briefly introduced the procedure of feature extraction and the theoretical background of this paper. The comparison experiment was conducted for gearbox fault detection and the analysis results from this work showed that support vector machine has better classification performance in this area

Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R

DEFF Research Database (Denmark)

O'Connell, Jarad Michael; Højsgaard, Søren

2011-01-01

models only allow a geometrically distributed sojourn time in a given state, while hidden semi-Markov models extend this by allowing an arbitrary sojourn distribution. We demonstrate the software with simulation examples and an application involving the modelling of the ovarian cycle of dairy cows...

Landsat TM band 431 combine on clustering analysis for pattern recognition land use using idrisi 4.2 software

International Nuclear Information System (INIS)

Wiweka, Arief H.; Izzawati, Tjahyaningsih A.

1997-01-01

The recognition of earth object's pattern which is recorded on remote sensing digital image can do by classification process based on the group of spectral pixel value. The spectral assessment on a spatial which represent the object characteristic can be helped through supervised or unsupervised. On certain case, there no media, such as maps, airborne, photo, the capability of field observation and the knowledge of object's location. Classification process can be done by clustering. The group of pixel based on the wide of the whole value interval of spectral image, then the class group base on the desired accuracy. The clustering method in Idris 4.2 software equipments are sequential method, statistic, iso data, and RGB. The clustering existence can help pre-process pattern recognition

Mobile Application Identification based on Hidden Markov Model

Directory of Open Access Journals (Sweden)

Yang Xinyan

2018-01-01

Full Text Available With the increasing number of mobile applications, there has more challenging network management tasks to resolve. Users also face security issues of the mobile Internet application when enjoying the mobile network resources. Identifying applications that correspond to network traffic can help network operators effectively perform network management. The existing mobile application recognition technology presents new challenges in extensibility and applications with encryption protocols. For the existing mobile application recognition technology, there are two problems, they can not recognize the application which using the encryption protocol and their scalability is poor. In this paper, a mobile application identification method based on Hidden Markov Model(HMM is proposed to extract the defined statistical characteristics from different network flows generated when each application starting. According to the time information of different network flows to get the corresponding time series, and then for each application to be identified separately to establish the corresponding HMM model. Then, we use 10 common applications to test the method proposed in this paper. The test results show that the mobile application recognition method proposed in this paper has a high accuracy and good generalization ability.

Auditory Modeling for Noisy Speech Recognition

National Research Council Canada - National Science Library

2000-01-01

... digital filtering for noise cancellation which interfaces to speech recognition software. It uses auditory features in speech recognition training, and provides applications to multilingual spoken language translation...

Hand gesture recognition in confined spaces with partial observability and occultation constraints

Science.gov (United States)

Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2016-05-01

Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.

Neuroevolution Mechanism for Hidden Markov Model

Directory of Open Access Journals (Sweden)

Nabil M. Hewahi

2011-12-01

Full Text Available Hidden Markov Model (HMM is a statistical model based on probabilities. HMM is becoming one of the major models involved in many applications such as natural language
processing, handwritten recognition, image processing, prediction systems and many more. In this research we are concerned with finding out the best HMM for a certain application domain. We propose a neuroevolution process that is based first on converting the HMM to a neural network, then generating many neural networks at random where each represents a HMM. We proceed by
applying genetic operators to obtain new set of neural networks where each represents HMMs, and updating the population. Finally select the best neural network based on a fitness function.

Psychodynamic experience enhances recognition of hidden childhood trauma.

Directory of Open Access Journals (Sweden)

David Cohen

Full Text Available BACKGROUND: Experimental psychology has only recently provided supporting evidence for Freud's and Janet's description of unconscious phenomena. Here, we aimed to assess whether specific abilities, such as personal psychodynamic experience, enhance the ability to recognize unconscious phenomena in peers - in other words, to better detect implicit knowledge related to individual self-experience. METHODOLOGY AND PRINCIPAL FINDINGS: First, we collected 14 videos from seven healthy adults who had experienced a sibling's cancer during childhood and seven matched controls. Subjects and controls were asked to give a 5-minute spontaneous free-associating speech following specific instructions created in order to activate a buffer zone between fantasy and reality. Then, 18 raters (three psychoanalysts, six medical students, three oncologists, three cognitive behavioral therapists and three individuals with the same experience of trauma were randomly shown the videos and asked to blindly classify them according to whether the speaker had a sibling with cancer using a Likert scale. Using a permutation test, we found a significant association between group and recognition score (ANOVA: p = .0006. Psychoanalysts were able to recognize, above chance levels, healthy adults who had experienced sibling cancer during childhood without explicit knowledge of this history (Power = 88%; p = .002. In contrast, medical students, oncologists, cognitive behavioral therapists and individuals who had the same history of a sibling's cancer were unable to do so. CONCLUSION: This experiment supports the view that implicit recognition of a subject's history depends on the rater's specific abilities. In the case of subjects who did have a sibling with cancer during childhood, psychoanalysts appear better able to recognize this particular history.

Recognition and Synthesis of Human Movements by Parametric HMMs

DEFF Research Database (Denmark)

Herzog, Dennis; Krüger, Volker

2009-01-01

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

Speech recognition technology: an outlook for human-to-machine interaction.

Science.gov (United States)

Erdel, T; Crooks, S

2000-01-01

Speech recognition, as an enabling technology in healthcare-systems computing, is a topic that has been discussed for quite some time, but is just now coming to fruition. Traditionally, speech-recognition software has been constrained by hardware, but improved processors and increased memory capacities are starting to remove some of these limitations. With these barriers removed, companies that create software for the healthcare setting have the opportunity to write more successful applications. Among the criticisms of speech-recognition applications are the high rates of error and steep training curves. However, even in the face of such negative perceptions, there remains significant opportunities for speech recognition to allow healthcare providers and, more specifically, physicians, to work more efficiently and ultimately spend more time with their patients and less time completing necessary documentation. This article will identify opportunities for inclusion of speech-recognition technology in the healthcare setting and examine major categories of speech-recognition software--continuous speech recognition, command and control, and text-to-speech. We will discuss the advantages and disadvantages of each area, the limitations of the software today, and how future trends might affect them.

Radar Target Recognition Based on Stacked Denoising Sparse Autoencoder

Directory of Open Access Journals (Sweden)

Zhao Feixiang

2017-04-01

Full Text Available Feature extraction is a key step in radar target recognition. The quality of the extracted features determines the performance of target recognition. However, obtaining the deep nature of the data is difficult using the traditional method. The autoencoder can learn features by making use of data and can obtain feature expressions at different levels of data. To eliminate the influence of noise, the method of radar target recognition based on stacked denoising sparse autoencoder is proposed in this paper. This method can extract features directly and efficiently by setting different hidden layers and numbers of iterations. Experimental results show that the proposed method is superior to the K-nearest neighbor method and the traditional stacked autoencoder.

Optimized hardware framework of MLP with random hidden layers for classification applications

Science.gov (United States)

Zyarah, Abdullah M.; Ramesh, Abhishek; Merkel, Cory; Kudithipudi, Dhireesha

2016-05-01

Multilayer Perceptron Networks with random hidden layers are very efficient at automatic feature extraction and offer significant performance improvements in the training process. They essentially employ large collection of fixed, random features, and are expedient for form-factor constrained embedded platforms. In this work, a reconfigurable and scalable architecture is proposed for the MLPs with random hidden layers with a customized building block based on CORDIC algorithm. The proposed architecture also exploits fixed point operations for area efficiency. The design is validated for classification on two different datasets. An accuracy of ~ 90% for MNIST dataset and 75% for gender classification on LFW dataset was observed. The hardware has 299 speed-up over the corresponding software realization.

A hidden Ising model for ChIP-chip data analysis

KAUST Repository

Mo, Q.

2010-01-28

Motivation: Chromatin immunoprecipitation (ChIP) coupled with tiling microarray (chip) experiments have been used in a wide range of biological studies such as identification of transcription factor binding sites and investigation of DNA methylation and histone modification. Hidden Markov models are widely used to model the spatial dependency of ChIP-chip data. However, parameter estimation for these models is typically either heuristic or suboptimal, leading to inconsistencies in their applications. To overcome this limitation and to develop an efficient software, we propose a hidden ferromagnetic Ising model for ChIP-chip data analysis. Results: We have developed a simple, but powerful Bayesian hierarchical model for ChIP-chip data via a hidden Ising model. Metropolis within Gibbs sampling algorithm is used to simulate from the posterior distribution of the model parameters. The proposed model naturally incorporates the spatial dependency of the data, and can be used to analyze data with various genomic resolutions and sample sizes. We illustrate the method using three publicly available datasets and various simulated datasets, and compare it with three closely related methods, namely TileMap HMM, tileHMM and BAC. We find that our method performs as well as TileMap HMM and BAC for the high-resolution data from Affymetrix platform, but significantly outperforms the other three methods for the low-resolution data from Agilent platform. Compared with the BAC method which also involves MCMC simulations, our method is computationally much more efficient. Availability: A software called iChip is freely available at http://www.bioconductor.org/. Contact: moq@mskcc.org. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org.

Bi-dimension decomposed hidden Markov models for multi-person activity recognition

Institute of Scientific and Technical Information of China (English)

Wei-dong ZHANG; Feng CHEN; Wen-li XU

2009-01-01

We present a novel model for recognizing long-term complex activities involving multiple persons. The proposed model, named 'decomposed hidden Markov model' (DHMM), combines spatial decomposition and hierarchical abstraction to capture multi-modal, long-term dependent and multi-scale characteristics of activities. Decomposition in space and time offers conceptual advantages of compaction and clarity, and greatly reduces the size of state space as well as the number of parameters.DHMMs are efficient even when the number of persons is variable. We also introduce an efficient approximation algorithm for inference and parameter estimation. Experiments on multi-person activities and multi-modal individual activities demonstrate that DHMMs are more efficient and reliable than familiar models, such as coupled HMMs, hierarchical HMMs, and multi-observation HMMs.

Uncovering Hidden Mathematics of the Multiplication Table Using Spreadsheets

Directory of Open Access Journals (Sweden)

Sergei Abramovich

2007-05-01

Full Text Available This paper reveals a number of learning activities emerging from a spreadsheetgenerated multiplication table. These activities are made possible by using such features of the software as conditional formatting, circular referencing, calculation through iteration, scroll bars, and graphing. The paper is a reflection on a mathematics content course designed for prospective elementary teachers using the hidden mathematics curriculum framework. It is written in support of standards for teaching and recommendations for teachers in North America.

The software for automatic creation of the formal grammars used by speech recognition, computer vision, editable text conversion systems, and some new functions

Science.gov (United States)

Kardava, Irakli; Tadyszak, Krzysztof; Gulua, Nana; Jurga, Stefan

2017-02-01

For more flexibility of environmental perception by artificial intelligence it is needed to exist the supporting software modules, which will be able to automate the creation of specific language syntax and to make a further analysis for relevant decisions based on semantic functions. According of our proposed approach, of which implementation it is possible to create the couples of formal rules of given sentences (in case of natural languages) or statements (in case of special languages) by helping of computer vision, speech recognition or editable text conversion system for further automatic improvement. In other words, we have developed an approach, by which it can be achieved to significantly improve the training process automation of artificial intelligence, which as a result will give us a higher level of self-developing skills independently from us (from users). At the base of our approach we have developed a software demo version, which includes the algorithm and software code for the entire above mentioned component's implementation (computer vision, speech recognition and editable text conversion system). The program has the ability to work in a multi - stream mode and simultaneously create a syntax based on receiving information from several sources.

A Study on Efficient Robust Speech Recognition with Stochastic Dynamic Time Warping

OpenAIRE

孫, 喜浩

2014-01-01

In recent years, great progress has been made in automatic speech recognition (ASR) system. The hidden Markov model (HMM) and dynamic time warping (DTW) are the two main algorithms which have been widely applied to ASR system. Although, HMM technique achieves higher recognition accuracy in clear speech environment and noisy environment. It needs large-set of words and realizes the algorithm more complexly.Thus, more and more researchers have focused on DTW-based ASR system.Dynamic time warpin...

Efficient Interaction Recognition through Positive Action Representation

Directory of Open Access Journals (Sweden)

Tao Hu

2013-01-01

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

RangerMaster trademark: Real-time pattern recognition software for in-field analysis of radiation sources

International Nuclear Information System (INIS)

Murray, W.S.; Ziemba, F.; Szluk, N.

1998-01-01

RangerMaster trademark is the embedded firmware for Quantrad Sensor's integrated nuclear instrument package, the Ranger trademark. The Ranger trademark, which is both a gamma-ray and neutron detection system, was originally developed at Los Alamos National Laboratory for in situ surveys at the Plutonium Facility to confirm the presence of nuclear materials. The new RangerMaster trademark software expands the library of isotopes and simplifies the operation of the instrument by providing an easy mode suitable for untrained operators. The expanded library of the Ranger trademark now includes medical isotopes 99 Tc, 201 Tl, 111 In, 67 Ga, 133 Xe, 103 Pa, and 131 I; industrial isotopes 241 Am, 57 Co, 133 Ba, 137 Cs, 40 K, 60 Co, 232 Th, 226 Ra, and 207 Bi; and nuclear materials 235 U, 238 U, 233 U, and 239 Pu. To accomplish isotopic identification, a simulated spectrum for each of the isotopes was generated using SYNTH. The SYNTH spectra formed the basis for the knowledge-based expert system and selection of the regions of interest that are used in the pattern recognition system. The knowledge-based pattern recognition system was tested against actual spectra under field conditions

RangerMasterTM: real-time pattern recognition software for in-field analysis of radiation sources

International Nuclear Information System (INIS)

Murray, W.S.; Ziemba, F.; Szluk, N.

1998-01-01

RangerMaster TM is the embedded firmware for Quantrad Sensor's integrated nuclear instrument package, the Ranger TM . The Ranger TM , which is both a gamma-ray and neutron detection system, was originally developed at Los Alamos National Laboratory for in situ surveys at the Plutonium Facility to confirm the presence of nuclear materials. The new RangerMaster TM software expands the library of isotopes and simplifies the operation of the instrument by providing an 'easy' mode suitable for untrained operators. The expanded library of the Ranger TM now includes medical isotopes 99 Tc, 201 Tl, 111 In, 67 Ga, 133 Xe, 103 Pa, and 131 I; industrial isotopes 241 Am, 57 Co, 133 Ba, 137 Cs, 40 K, 60 Co, 232 Th, 226 Ra, and 207 Bi; and nuclear materials 235 U, 238 U, 233 U, and 239 Pu. To accomplish isotopic identification, a simulated spectrum for each of the isotopes was generated using SYNTH 2 . The SYNTH spectra formed the basis for the knowledge-based expert system and selection of the regions of interest that are used in the pattern recognition system. The knowledge-based pattern recognition system was tested against actual spectra under field conditions. (author)

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

NARCIS (Netherlands)

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

2011-01-01

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

Hidden gauge symmetry

International Nuclear Information System (INIS)

O'Raifeartaigh, L.

1979-01-01

This review describes the principles of hidden gauge symmetry and of its application to the fundamental interactions. The emphasis is on the structure of the theory rather than on the technical details and, in order to emphasise the structure, gauge symmetry and hidden symmetry are first treated as independent phenomena before being combined into a single (hidden gauge symmetric) theory. The main application of the theory is to the weak and electromagnetic interactions of the elementary particles, and although models are used for comparison with experiment and for illustration, emphasis is placed on those features of the application which are model-independent. (author)

Variational Infinite Hidden Conditional Random Fields

NARCIS (Netherlands)

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin

2015-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of

Critical object recognition in millimeter-wave images with robustness to rotation and scale.

Science.gov (United States)

Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

2017-06-01

Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

HMMEditor: a visual editing tool for profile hidden Markov model

Directory of Open Access Journals (Sweden)

Cheng Jianlin

2008-03-01

Full Text Available Abstract Background Profile Hidden Markov Model (HMM is a powerful statistical model to represent a family of DNA, RNA, and protein sequences. Profile HMM has been widely used in bioinformatics research such as sequence alignment, gene structure prediction, motif identification, protein structure prediction, and biological database search. However, few comprehensive, visual editing tools for profile HMM are publicly available. Results We develop a visual editor for profile Hidden Markov Models (HMMEditor. HMMEditor can visualize the profile HMM architecture, transition probabilities, and emission probabilities. Moreover, it provides functions to edit and save HMM and parameters. Furthermore, HMMEditor allows users to align a sequence against the profile HMM and to visualize the corresponding Viterbi path. Conclusion HMMEditor provides a set of unique functions to visualize and edit a profile HMM. It is a useful tool for biological sequence analysis and modeling. Both HMMEditor software and web service are freely available.

Hidden charged dark matter

International Nuclear Information System (INIS)

Feng, Jonathan L.; Kaplinghat, Manoj; Tu, Huitzu; Yu, Hai-Bo

2009-01-01

Can dark matter be stabilized by charge conservation, just as the electron is in the standard model? We examine the possibility that dark matter is hidden, that is, neutral under all standard model gauge interactions, but charged under an exact (\\rm U)(1) gauge symmetry of the hidden sector. Such candidates are predicted in WIMPless models, supersymmetric models in which hidden dark matter has the desired thermal relic density for a wide range of masses. Hidden charged dark matter has many novel properties not shared by neutral dark matter: (1) bound state formation and Sommerfeld-enhanced annihilation after chemical freeze out may reduce its relic density, (2) similar effects greatly enhance dark matter annihilation in protohalos at redshifts of z ∼ 30, (3) Compton scattering off hidden photons delays kinetic decoupling, suppressing small scale structure, and (4) Rutherford scattering makes such dark matter self-interacting and collisional, potentially impacting properties of the Bullet Cluster and the observed morphology of galactic halos. We analyze all of these effects in a WIMPless model in which the hidden sector is a simplified version of the minimal supersymmetric standard model and the dark matter is a hidden sector stau. We find that charged hidden dark matter is viable and consistent with the correct relic density for reasonable model parameters and dark matter masses in the range 1 GeV ∼ X ∼< 10 TeV. At the same time, in the preferred range of parameters, this model predicts cores in the dark matter halos of small galaxies and other halo properties that may be within the reach of future observations. These models therefore provide a viable and well-motivated framework for collisional dark matter with Sommerfeld enhancement, with novel implications for astrophysics and dark matter searches

Localization of hidden Chua's attractors

International Nuclear Information System (INIS)

Leonov, G.A.; Kuznetsov, N.V.; Vagaitsev, V.I.

2011-01-01

The classical attractors of Lorenz, Rossler, Chua, Chen, and other widely-known attractors are those excited from unstable equilibria. From computational point of view this allows one to use numerical method, in which after transient process a trajectory, started from a point of unstable manifold in the neighborhood of equilibrium, reaches an attractor and identifies it. However there are attractors of another type: hidden attractors, a basin of attraction of which does not contain neighborhoods of equilibria. In the present Letter for localization of hidden attractors of Chua's circuit it is suggested to use a special analytical-numerical algorithm. -- Highlights: → There are hidden attractors: basin doesn't contain neighborhoods of equilibria. → Hidden attractors cannot be reached by trajectory from neighborhoods of equilibria. → We suggested special procedure for localization of hidden attractors. → We discovered hidden attractor in Chua's system, L. Chua in his work didn't expect this.

Research on Interaction-oriented Gesture Recognition

Directory of Open Access Journals (Sweden)

Lu Huang

2014-01-01

Full Text Available This thesis designs a series of gesture interaction with the features of the natural human-machine interaction; besides, it utilizes the 3D acceleration sensors as interactive input. Afterwards, it builds the Discrete Hidden Markov Model to make gesture recognition by introducing the collection proposal of gesture interaction based on the acceleration sensors and pre-handling the gesture acceleration signal obtained in the collection. In the end, the thesis proofs the design proposal workable and effective according to the experiments.

Pattern activation/recognition theory of mind.

Science.gov (United States)

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Speech recognition software and electronic psychiatric progress notes: physicians' ratings and preferences

Directory of Open Access Journals (Sweden)

Derman Yaron D

2010-08-01

Full Text Available Abstract Background The context of the current study was mandatory adoption of electronic clinical documentation within a large mental health care organization. Psychiatric electronic documentation has unique needs by the nature of dense narrative content. Our goal was to determine if speech recognition (SR would ease the creation of electronic progress note (ePN documents by physicians at our institution. Methods Subjects: Twelve physicians had access to SR software on their computers for a period of four weeks to create ePN. Measurements: We examined SR software in relation to its perceived usability, data entry time savings, impact on the quality of care and quality of documentation, and the impact on clinical and administrative workflow, as compared to existing methods for data entry. Data analysis: A series of Wilcoxon signed rank tests were used to compare pre- and post-SR measures. A qualitative study design was used. Results Six of twelve participants completing the study favoured the use of SR (five with SR alone plus one with SR via hand-held digital recorder for creating electronic progress notes over their existing mode of data entry. There was no clear perceived benefit from SR in terms of data entry time savings, quality of care, quality of documentation, or impact on clinical and administrative workflow. Conclusions Although our findings are mixed, SR may be a technology with some promise for mental health documentation. Future investigations of this nature should use more participants, a broader range of document types, and compare front- and back-end SR methods.

Detection of hidden explosives by fast neutron activation analysis

International Nuclear Information System (INIS)

Li Xinnian; Guo Junpeng; Luo Wenyun; Wang Chuanshan; Fang Xiaoming; Yu Tailiu

2008-01-01

The paper describes the method and principle for detection of hidden explosive by fast neutron activation analysis (FNAA). The method of detection of explosives by FNAA has the specific properties of simple determination equipments, high reliability, and low detecting cost, and would be beneficial to the applicability and popularization in the field of protecting and securing nation. The contents of nitrogen and oxygen in four explosives, more then ten common materials and TNT samples covered with soil, were measured by FNAA. 14 MeV fast neutrons were generated from (d, t) reaction with a 400 kV Cockcroft Walton type accelerator. The two-dimension distributions for nitro- gen and oxygen counting rates per unit mass of determined matters were obtained, and the characteristic area of explosives and non-explosives can be defined. By computer aided pattern recognition, the samples were identified with low false alarm or omission rates. The Monte-Carlo simulation indicates that there is no any radiation at 15 m apart from neutron source and is safe for irradiation after 1 h. It is suggested that FNAA may be potential in remote controlling for detection hidden explosive system with multi-probe large array. (authors)

Hidden Liquidity: Determinants and Impact

OpenAIRE

Gökhan Cebiroglu; Ulrich Horst

2012-01-01

We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stock’s hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that large hidden orders are associated with larger transaction costs, higher price impact and increased volatility. In particular, as large hidden orders fail to attract (latent) liquidity to the market, ...

Portability and the National Energy Software Center

International Nuclear Information System (INIS)

Butler, M.K.

1978-01-01

The software portability problem is examined from the viewpoint of experience gained in the operation of a software exchange and information center. First, the factors contributing to the program interchange to date are identified, then major problem areas remaining are noted. The import of the development of programing language and documentation standards is noted, and the program packaging procedures and dissemination practices employed by the Center to facilitate successful software transport are described. Organization, or installation, dependencies of the computing environment, often hidden from the program author, and data interchange complexities are seen as today's primary issues, with dedicated processors and network communications offering an alternative solution

Hidden Markov Model for Stock Selection

Directory of Open Access Journals (Sweden)

Nguyet Nguyen

2015-10-01

Full Text Available The hidden Markov model (HMM is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for stock selection. We first use HMM to make monthly regime predictions for the four macroeconomic variables: inflation (consumer price index (CPI, industrial production index (INDPRO, stock market index (S&P 500 and market volatility (VIX. At the end of each month, we calibrate HMM’s parameters for each of these economic variables and predict its regimes for the next month. We then look back into historical data to find the time periods for which the four variables had similar regimes with the forecasted regimes. Within those similar periods, we analyze all of the S&P 500 stocks to identify which stock characteristics have been well rewarded during the time periods and assign scores and corresponding weights for each of the stock characteristics. A composite score of each stock is calculated based on the scores and weights of its features. Based on this algorithm, we choose the 50 top ranking stocks to buy. We compare the performances of the portfolio with the benchmark index, S&P 500. With an initial investment of $100 in December 1999, over 15 years, in December 2014, our portfolio had an average gain per annum of 14.9% versus 2.3% for the S&P 500.

Static human face recognition using artificial neural networks

International Nuclear Information System (INIS)

Qamar, R.; Shah, S.H.; Javed-ur-Rehman

2003-01-01

This paper presents a novel method of human face recognition using digital computers. A digital PC camera is used to take the BMP images of the human faces. An artificial neural network using Back Propagation Algorithm is developed as a recognition engine. The BMP images of the faces serve as the input patterns for this engine. A software 'Face Recognition' has been developed to recognize the human faces for which it is trained. Once the neural network is trained for patterns of the faces, the software is able to detect and recognize them with success rate of about 97%. (author)

Using features of local densities, statistics and HMM toolkit (HTK for offline Arabic handwriting text recognition

Directory of Open Access Journals (Sweden)

El Moubtahij Hicham

2017-12-01

Full Text Available This paper presents an analytical approach of an offline handwritten Arabic text recognition system. It is based on the Hidden Markov Models (HMM Toolkit (HTK without explicit segmentation. The first phase is preprocessing, where the data is introduced in the system after quality enhancements. Then, a set of characteristics (features of local densities and features statistics are extracted by using the technique of sliding windows. Subsequently, the resulting feature vectors are injected to the Hidden Markov Model Toolkit (HTK. The simple database “Arabic-Numbers” and IFN/ENIT are used to evaluate the performance of this system. Keywords: Hidden Markov Models (HMM Toolkit (HTK, Sliding windows

Finger Vein Recognition Based on Local Directional Code

Science.gov (United States)

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger Vein Recognition Based on Local Directional Code

Directory of Open Access Journals (Sweden)

Rongyang Xiao

2012-11-01

Full Text Available Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP, Local Derivative Pattern (LDP and Local Line Binary Pattern (LLBP. However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD, this paper represents a new direction based local descriptor called Local Directional Code (LDC and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

Primitive Based Action Representation and recognition

DEFF Research Database (Denmark)

Baby, Sanmohan

The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human-machine i......The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human......-machine interface, entertainment, biomechanics etc. Recent developments in neuroscience suggest that all actions are a compositions of smaller units called primitives. Current works based on primitives for action recognition uses a supervised framework for specifying the primitives. We propose a method to extract...... primitives automatically. These primitives are to be used to generate actions based on certain rules for combining. These rules are expressed as a stochastic context free grammar. A model merging approach is adopted to learn a Hidden Markov Model to t the observed data sequences. The states of the HMM...

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

Science.gov (United States)

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Hidden Curriculum: An Analytical Definition

Directory of Open Access Journals (Sweden)

Mohammad Reza Andarvazh

2018-03-01

Full Text Available Background: The concept of hidden curriculum was first used by Philip Jackson in 1968, and Hafferty brought this concept to the medical education. Many of the subjects that medical students learn are attributed to this curriculum. So far several definitions have been presented for the hidden curriculum, which on the one hand made this concept richer, and on the other hand, led to confusion and ambiguity.This paper tries to provide a clear and comprehensive definition of it.Methods: In this study, concept analysis of McKenna method was used. Using keywords and searching in the databases, 561 English and 26 Persian references related to the concept was found, then by limitingthe research scope, 125 abstracts and by finding more relevant references, 55 articles were fully studied.Results: After analyzing the definitions by McKenna method, the hidden curriculum is defined as follows: The hidden curriculum is a hidden, powerful, intrinsic in organizational structure and culture and sometimes contradictory message, conveyed implicitly and tacitly in the learning environment by structural and human factors and its contents includes cultural habits and customs, norms, values, belief systems, attitudes, skills, desires and behavioral and social expectations can have a positive or negative effect, unplanned, neither planners nor teachers, nor learners are aware of it. The ultimate consequence of the hidden curriculum includes reproducing the existing class structure, socialization, and familiarizing learners for transmission and joining the professional world.Conclusion: Based on the concept analysis, we arrived at an analytical definition of the hidden curriculum that could be useful for further studies in this area.Keywords: CONCEPT ANALYSIS, HIDDEN CURRICULUM, MCKENNA’S METHOD

Hidden particle production at the ILC

International Nuclear Information System (INIS)

Fujii, Keisuke; Itoh, Hideo; Okada, Nobuchika; Hano, Hitoshi; Yoshioka, Tamaki

2008-01-01

In a class of new physics models, the new physics sector is completely or partly hidden, namely, a singlet under the standard model (SM) gauge group. Hidden fields included in such new physics models communicate with the standard model sector through higher-dimensional operators. If a cutoff lies in the TeV range, such hidden fields can be produced at future colliders. We consider a scalar field as an example of the hidden fields. Collider phenomenology on this hidden scalar is similar to that of the SM Higgs boson, but there are several features quite different from those of the Higgs boson. We investigate productions of the hidden scalar at the International Linear Collider (ILC) and study the feasibility of its measurements, in particular, how well the ILC distinguishes the scalar from the Higgs boson, through realistic Monte Carlo simulations.

Probing hidden sector photons through the Higgs window

International Nuclear Information System (INIS)

Ahlers, M.

2008-07-01

We investigate the possibility that a (light) hidden sector extra photon receives its mass via spontaneous symmetry breaking of a hidden sector Higgs boson, the so-called hidden-Higgs. The hidden-photon can mix with the ordinary photon via a gauge kinetic mixing term. The hidden-Higgs can couple to the Standard Model Higgs via a renormalizable quartic term - sometimes called the Higgs Portal. We discuss the implications of this light hidden-Higgs in the context of laser polarization and light-shining-through-the-wall experiments as well as cosmological, astrophysical, and non-Newtonian force measurements. For hidden-photons receiving their mass from a hidden-Higgs we find in the small mass regime significantly stronger bounds than the bounds on massive hidden sector photons alone. (orig.)

Probing hidden sector photons through the Higgs window

International Nuclear Information System (INIS)

Ahlers, Markus; Jaeckel, Joerg; Redondo, Javier; Ringwald, Andreas

2008-01-01

We investigate the possibility that a (light) hidden sector extra photon receives its mass via spontaneous symmetry breaking of a hidden sector Higgs boson, the so-called hidden-Higgs. The hidden-photon can mix with the ordinary photon via a gauge kinetic mixing term. The hidden-Higgs can couple to the standard model Higgs via a renormalizable quartic term - sometimes called the Higgs portal. We discuss the implications of this light hidden-Higgs in the context of laser polarization and light-shining-through-the-wall experiments as well as cosmological, astrophysical, and non-Newtonian force measurements. For hidden-photons receiving their mass from a hidden-Higgs, we find in the small mass regime significantly stronger bounds than the bounds on massive hidden sector photons alone.

Insight: Exploring Hidden Roles in Collaborative Play

Directory of Open Access Journals (Sweden)

Tricia Shi

2015-06-01

Full Text Available This paper looks into interaction modes between players in co-located, collaborative games. In particular, hidden traitor games, in which one or more players is secretly working against the group mission, has the effect of increasing paranoia and distrust between players, so this paper looks into the opposite of a hidden traitor – a hidden benefactor. Rather than sabotaging the group mission, the hidden benefactor would help the group achieve the end goal while still having a reason to stay hidden. The paper explores what games with such a role can look like and how the role changes player interactions. Finally, the paper addresses the divide between video game and board game interaction modes; hidden roles are not common within video games, but they are of growing prevalence in board games. This fact, combined with the exploration of hidden benefactors, reveals that hidden roles is a mechanic that video games should develop into in order to match board games’ complexity of player interaction modes.

Hidden attractors in dynamical systems

Science.gov (United States)

Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh

2016-06-01

Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.

Partially Hidden Markov Models

DEFF Research Database (Denmark)

Forchhammer, Søren Otto; Rissanen, Jorma

1996-01-01

Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where...

Device Control Using Gestures Sensed from EMG

Science.gov (United States)

Wheeler, Kevin R.

2003-01-01

In this paper we present neuro-electric interfaces for virtual device control. The examples presented rely upon sampling Electromyogram data from a participants forearm. This data is then fed into pattern recognition software that has been trained to distinguish gestures from a given gesture set. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard.

Hidden photons in connection to dark matter

Energy Technology Data Exchange (ETDEWEB)

Andreas, Sarah; Ringwald, Andreas [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Goodsell, Mark D. [CPhT, Ecole Polytechnique, Palaiseau (France)

2013-06-15

Light extra U(1) gauge bosons, so called hidden photons, which reside in a hidden sector have attracted much attention since they are a well motivated feature of many scenarios beyond the Standard Model and furthermore could mediate the interaction with hidden sector dark matter.We review limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay. In addition, we study the possibility of having dark matter in the hidden sector. A simple toy model and different supersymmetric realisations are shown to provide viable dark matter candidates in the hidden sector that are in agreement with recent direct detection limits.

Hidden photons in connection to dark matter

International Nuclear Information System (INIS)

Andreas, Sarah; Ringwald, Andreas; Goodsell, Mark D.

2013-06-01

Light extra U(1) gauge bosons, so called hidden photons, which reside in a hidden sector have attracted much attention since they are a well motivated feature of many scenarios beyond the Standard Model and furthermore could mediate the interaction with hidden sector dark matter.We review limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay. In addition, we study the possibility of having dark matter in the hidden sector. A simple toy model and different supersymmetric realisations are shown to provide viable dark matter candidates in the hidden sector that are in agreement with recent direct detection limits.

POVMs and hidden variables

International Nuclear Information System (INIS)

Stairs, Allen

2007-01-01

Recent results by Paul Busch and Adan Cabello claim to show that by appealing to POVMs, non-contextual hidden variables can be ruled out in two dimensions. While the results of Busch and Cabello are mathematically correct, interpretive problems render them problematic as no hidden variable proofs

Strengthening Software Authentication with the ROSE Software Suite

International Nuclear Information System (INIS)

White, G

2006-01-01

Many recent nonproliferation and arms control software projects include a software authentication regime. These include U.S. Government-sponsored projects both in the United States and in the Russian Federation (RF). This trend toward requiring software authentication is only accelerating. Demonstrating assurance that software performs as expected without hidden ''backdoors'' is crucial to a project's success. In this context, ''authentication'' is defined as determining that a software package performs only its intended purpose and performs said purpose correctly and reliably over the planned duration of an agreement. In addition to visual inspections by knowledgeable computer scientists, automated tools are needed to highlight suspicious code constructs, both to aid visual inspection and to guide program development. While many commercial tools are available for portions of the authentication task, they are proprietary and not extensible. An open-source, extensible tool can be customized to the unique needs of each project (projects can have both common and custom rules to detect flaws and security holes). Any such extensible tool has to be based on a complete language compiler. ROSE is precisely such a compiler infrastructure developed within the Department of Energy (DOE) and targeted at the optimization of scientific applications and user-defined libraries within large-scale applications (typically applications of a million lines of code). ROSE is a robust, source-to-source analysis and optimization infrastructure currently addressing large, million-line DOE applications in C and C++ (handling the full C, C99, C++ languages and with current collaborations to support Fortran90). We propose to extend ROSE to address a number of security-specific requirements, and apply it to software authentication for nonproliferation and arms control projects

Helioscope bounds on hidden sector photons

International Nuclear Information System (INIS)

Redondo, J.

2008-01-01

The flux of hypothetical ''hidden photons'' from the Sun is computed under the assumption that they interact with normal matter only through kinetic mixing with the ordinary standard model photon. Requiring that the exotic luminosity is smaller than the standard photon luminosity provides limits for the mixing parameter down to χ -14 , depending on the hidden photon mass. Furthermore, it is pointed point out that helioscopes looking for solar axions are also sensitive to hidden photons. The recent results of the CAST collaboration are used to further constrain the mixing parameter χ at low masses (m γ' <1 eV) where the luminosity bound is weaker. In this regime the solar hidden photon ux has a sizable contribution of longitudinally polarized hidden photons of low energy which are invisible for current helioscopes. (orig.)

Managing Hidden Costs of Offshoring

DEFF Research Database (Denmark)

Larsen, Marcus M.; Pedersen, Torben

2014-01-01

This chapter investigates the concept of the ‘hidden costs’ of offshoring, i.e. unexpected offshoring costs exceeding the initially expected costs. Due to the highly undefined nature of these costs, we position our analysis towards the strategic responses of firms’ realisation of hidden costs....... In this regard, we argue that a major response to the hidden costs of offshoring is the identification and utilisation of strategic mechanisms in the organisational design to eventually achieving system integration in a globally dispersed and disaggregated organisation. This is heavily moderated by a learning......-by-doing process, where hidden costs motivate firms and their employees to search for new and better knowledge on how to successfully manage the organisation. We illustrate this thesis based on the case of the LEGO Group....

The Hidden Costs of Offshoring

DEFF Research Database (Denmark)

Møller Larsen, Marcus; Manning, Stephan; Pedersen, Torben

2011-01-01

of offshoring. Specifically, we propose that hidden costs can be explained by the combination of increasing structural, operational and social complexity of offshoring activities. In addition, we suggest that firm orientation towards organizational design as part of an offshoring strategy and offshoring......This study seeks to explain hidden costs of offshoring, i.e. unexpected costs resulting from the relocation of business tasks and activities outside the home country. We develop a model that highlights the role of complexity, design orientation and experience in explaining hidden costs...... experience moderate the relationship between complexity and hidden costs negatively i.e. reduces the cost generating impact of complexity. We develop three hypotheses and test them on comprehensive data from the Offshoring Research Network (ORN). In general, we find support for our hypotheses. A key result...

An HMM-Like Dynamic Time Warping Scheme for Automatic Speech Recognition

Directory of Open Access Journals (Sweden)

Ing-Jr Ding

2014-01-01

Full Text Available In the past, the kernel of automatic speech recognition (ASR is dynamic time warping (DTW, which is feature-based template matching and belongs to the category technique of dynamic programming (DP. Although DTW is an early developed ASR technique, DTW has been popular in lots of applications. DTW is playing an important role for the known Kinect-based gesture recognition application now. This paper proposed an intelligent speech recognition system using an improved DTW approach for multimedia and home automation services. The improved DTW presented in this work, called HMM-like DTW, is essentially a hidden Markov model- (HMM- like method where the concept of the typical HMM statistical model is brought into the design of DTW. The developed HMM-like DTW method, transforming feature-based DTW recognition into model-based DTW recognition, will be able to behave as the HMM recognition technique and therefore proposed HMM-like DTW with the HMM-like recognition model will have the capability to further perform model adaptation (also known as speaker adaptation. A series of experimental results in home automation-based multimedia access service environments demonstrated the superiority and effectiveness of the developed smart speech recognition system by HMM-like DTW.

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.

Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

Directory of Open Access Journals (Sweden)

Araceli Sanchis

2013-04-01

Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

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.

Double-Blind Review in Software Engineering Venues : The Community’s Perspective

NARCIS (Netherlands)

Bacchelli, A.; Beller, M.M.

2017-01-01

The peer review process is central to the scientific method, the advancement and spread of research, as well as crucial for individual careers. However, the single-blind review mode currently used in most Software Engineering (SE) venues is susceptible to apparent and hidden biases, since reviewers

Hidden Risk Factors for Women

Science.gov (United States)

... A.S.T. Quiz Hidden Stroke Risk Factors for Women Updated:Nov 22,2016 Excerpted from "What Women Need To Know About The Hidden Risk Factors ... 2012) This year, more than 100,000 U.S. women under 65 will have a stroke. Stroke is ...

Hidden-Sector Dynamics and the Supersymmetric Seesaw

CERN Document Server

Campbell, Bruce A; Maybury, David W

2008-01-01

In light of recent analyses that have shown that nontrivial hidden-sector dynamics in models of supersymmetry breaking can lead to a significant impact on the predicted low-energy supersymmetric spectrum, we extend these studies to consider hidden-sector effects in extensions of the MSSM to include a seesaw model for neutrino masses. A dynamical hidden sector in an interval of mass scales below the seesaw scale would yield renormalization-group running involving both the anomalous dimension from the hidden sector and the seesaw-extended MSSM renormalization group equations (RGEs). These effects interfere in general, altering the generational mixing of the sleptons, and allowing for a substantial change to the expected level of charged-lepton flavour violation in seesaw-extended MSSM models. These results provide further support for recent theoretical observations that knowledge of the hidden sector is required in order to make concrete low-energy predictions, if the hidden sector is strongly coupled. In parti...

Post processing of optically recognized text via second order hidden Markov model

Science.gov (United States)

Poudel, Srijana

In this thesis, we describe a postprocessing system on Optical Character Recognition(OCR) generated text. Second Order Hidden Markov Model (HMM) approach is used to detect and correct the OCR related errors. The reason for choosing the 2nd order HMM is to keep track of the bigrams so that the model can represent the system more accurately. Based on experiments with training data of 159,733 characters and testing of 5,688 characters, the model was able to correct 43.38 % of the errors with a precision of 75.34 %. However, the precision value indicates that the model introduced some new errors, decreasing the correction percentage to 26.4%.

Parametric HMMs for Movement Recognition and Synthesis

DEFF Research Database (Denmark)

Herzog, Dennis; Krüger, Volker

2009-01-01

, we develop an exemplar-based parametric hidden Markov model (PHMM) that allows to represent movements of a particular type. Since we use model interpolation to reduce the necessary amount of training data, we had to develop a method to setup local models in a synchronized way. In our experiments we......A common problem in human movement recognition is the recognition of movements of a particular type (semantic). E.g., grasping movements have a particular semantic (grasping) but the actual movements usually have very different appearances due to, e.g., different grasping directions. In this paper...... to recover the movement type, and, e.g., the object position a human is pointing at. Our experiments show the flexibility of the PHMMs in terms of the amount of training data and its robustness in terms of noisy observation data. In addition, we compare our PHMM to an other kind of PHMM, which has been...

Vision-Based Recognition of Activities by a Humanoid Robot

Directory of Open Access Journals (Sweden)

Mounîm A. El-Yacoubi

2015-12-01

Full Text Available We present an autonomous assistive robotic system for human activity recognition from video sequences. Due to the large variability inherent to video capture from a non-fixed robot (as opposed to a fixed camera, as well as the robot's limited computing resources, implementation has been guided by robustness to this variability and by memory and computing speed efficiency. To accommodate motion speed variability across users, we encode motion using dense interest point trajectories. Our recognition model harnesses the dense interest point bag-of-words representation through an intersection kernel-based SVM that better accommodates the large intra-class variability stemming from a robot operating in different locations and conditions. To contextually assess the engine as implemented in the robot, we compare it with the most recent approaches of human action recognition performed on public datasets (non-robot-based, including a novel approach of our own that is based on a two-layer SVM-hidden conditional random field sequential recognition model. The latter's performance is among the best within the recent state of the art. We show that our robot-based recognition engine, while less accurate than the sequential model, nonetheless shows good performances, especially given the adverse test conditions of the robot, relative to those of a fixed camera.

Global Update and Trends of Hidden Hunger, 1995-2011: The Hidden Hunger Index.

Directory of Open Access Journals (Sweden)

Julie C Ruel-Bergeron

Full Text Available Deficiencies in essential vitamins and minerals-also termed hidden hunger-are pervasive and hold negative consequences for the cognitive and physical development of children.This analysis evaluates the change in hidden hunger over time in the form of one composite indicator-the Hidden Hunger Index (HHI-using an unweighted average of prevalence estimates from the Nutrition Impact Model Study for anemia due to iron deficiency, vitamin A deficiency, and stunting (used as a proxy indicator for zinc deficiency. Net changes from 1995-2011 and population weighted regional means for various time periods are measured.Globally, hidden hunger improved (-6.7 net change in HHI from 1995-2011. Africa was the only region to see a deterioration in hidden hunger (+1.9 over the studied time period; East Asia and the Pacific performed exceptionally well (-13.0, while other regions improved only slightly. Improvements in HHI were mostly due to reductions in zinc and vitamin A deficiencies, while anemia due to iron deficiency persisted and even increased.This analysis is critical for informing and tracking the impact of policy and programmatic efforts to reduce micronutrient deficiencies, to advance the global nutrition agenda, and to achieve the Millennium Development Goals (MDGs. However, there remains an unmet need to invest in gathering frequent, nationally representative, high-quality micronutrient data as we renew our efforts to scale up nutrition, and as we enter the post-2015 development agenda.Preparation of this manuscript was funded by Sight and Life. There was no funding involved in the study design, data collection, analysis, or decision to publish.

A Two-Channel Training Algorithm for Hidden Markov Model and Its Application to Lip Reading

Directory of Open Access Journals (Sweden)

Foo Say Wei

2005-01-01

Full Text Available Hidden Markov model (HMM has been a popular mathematical approach for sequence classification such as speech recognition since 1980s. In this paper, a novel two-channel training strategy is proposed for discriminative training of HMM. For the proposed training strategy, a novel separable-distance function that measures the difference between a pair of training samples is adopted as the criterion function. The symbol emission matrix of an HMM is split into two channels: a static channel to maintain the validity of the HMM and a dynamic channel that is modified to maximize the separable distance. The parameters of the two-channel HMM are estimated by iterative application of expectation-maximization (EM operations. As an example of the application of the novel approach, a hierarchical speaker-dependent visual speech recognition system is trained using the two-channel HMMs. Results of experiments on identifying a group of confusable visemes indicate that the proposed approach is able to increase the recognition accuracy by an average of 20% compared with the conventional HMMs that are trained with the Baum-Welch estimation.

ASERA: A Spectrum Eye Recognition Assistant

Science.gov (United States)

Yuan, Hailong; Zhang, Haotong; Zhang, Yanxia; Lei, Yajuan; Dong, Yiqiao; Zhao, Yongheng

2018-04-01

ASERA, ASpectrum Eye Recognition Assistant, aids in quasar spectral recognition and redshift measurement and can also be used to recognize various types of spectra of stars, galaxies and AGNs (Active Galactic Nucleus). This interactive software allows users to visualize observed spectra, superimpose template spectra from the Sloan Digital Sky Survey (SDSS), and interactively access related spectral line information. ASERA is an efficient and user-friendly semi-automated toolkit for the accurate classification of spectra observed by LAMOST (the Large Sky Area Multi-object Fiber Spectroscopic Telescope) and is available as a standalone Java application and as a Java applet. The software offers several functions, including wavelength and flux scale settings, zoom in and out, redshift estimation, and spectral line identification.

Hidden variables and locality in quantum theory

International Nuclear Information System (INIS)

Shiva, Vandana.

1978-12-01

The status of hidden variables in quantum theory has been debated since the 1920s. The author examines the no-hidden-variable theories of von Neumann, Kochen, Specker and Bell, and finds that they all share one basic assumption: averaging over the hidden variables should reproduce the quantum mechanical probabilities. Von Neumann also makes a linearity assumption, Kochen and Specker require the preservation of certain functional relations between magnitudes, and Bell proposes a locality condition. It has been assumed that the extrastatistical requirements are needed to serve as criteria of success for the introduction of hidden variables because the statistical condition is trivially satisfied, and that Bell's result is based on a locality condition that is physically motivated. The author shows that the requirement of weak locality, which is not physically motivated, is enough to give Bell's result. The proof of Bell's inequality works equally well for any pair of commuting magnitudes satisfying a condition called the degeneracy principle. None of the no-hidden-variable proofs apply to a class of hidden variable theories that are not phase-space reconstructions of quantum mechanics. The author discusses one of these theories, the Bohm-Bub theory, and finds that hidden variable theories that re all the quantum statistics, for single and sequential measurements, must introduce a randomization process for the hidden variables after each measurement. The philosophical significance of this theory lies in the role it can play in solving the conceptual puzzles posed by quantum theory

Affective State Level Recognition in Naturalistic Facial and Vocal Expressions.

Science.gov (United States)

Meng, Hongying; Bianchi-Berthouze, Nadia

2014-03-01

Naturalistic affective expressions change at a rate much slower than the typical rate at which video or audio is recorded. This increases the probability that consecutive recorded instants of expressions represent the same affective content. In this paper, we exploit such a relationship to improve the recognition performance of continuous naturalistic affective expressions. Using datasets of naturalistic affective expressions (AVEC 2011 audio and video dataset, PAINFUL video dataset) continuously labeled over time and over different dimensions, we analyze the transitions between levels of those dimensions (e.g., transitions in pain intensity level). We use an information theory approach to show that the transitions occur very slowly and hence suggest modeling them as first-order Markov models. The dimension levels are considered to be the hidden states in the Hidden Markov Model (HMM) framework. Their discrete transition and emission matrices are trained by using the labels provided with the training set. The recognition problem is converted into a best path-finding problem to obtain the best hidden states sequence in HMMs. This is a key difference from previous use of HMMs as classifiers. Modeling of the transitions between dimension levels is integrated in a multistage approach, where the first level performs a mapping between the affective expression features and a soft decision value (e.g., an affective dimension level), and further classification stages are modeled as HMMs that refine that mapping by taking into account the temporal relationships between the output decision labels. The experimental results for each of the unimodal datasets show overall performance to be significantly above that of a standard classification system that does not take into account temporal relationships. In particular, the results on the AVEC 2011 audio dataset outperform all other systems presented at the international competition.

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

Directory of Open Access Journals (Sweden)

Ran Wang

2016-10-01

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

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

Science.gov (United States)

Daniels, Paul; Iwago, Koji

2017-01-01

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

… To be hidden does not mean to be merely revealed – Part 1 Artistic research on hidden curriculum

Directory of Open Access Journals (Sweden)

Annette Krause

2015-09-01

Full Text Available This text revisits the long-term project Hidden Curriculum, initiated by Annette Krauss. The project addresses unquestioned routines, hierarchies of knowledge (part 1, and the role of the body in learning processes (part 2 from the perspective of secondary/high school education (in the research on a hidden curriculum. A deeper analysis of educational studies on the phenomenon of ‘hidden curriculum’ in relation to the feminist and critical pedagogies of bell hooks, Paulo Freire, and Jacques Rancière brings forward important insights generated through the artistic research within hidden curriculum. The aim of this text is to address academic canons, corporeality, and investigate everyday norms through revisiting the framework, results, and processes of the collaborative research into hidden curriculum with secondary high school students.

Features Speech Signature Image Recognition on Mobile Devices

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Alexander Mikhailovich Alyushin

2015-12-01

Full Text Available The algorithms fordynamic spectrograms images recognition, processing and soundspeech signature (SS weredeveloped. The software for mobile phones, thatcan recognize speech signatureswas prepared. The investigation of the SS recognition speed on its boundarytypes was conducted. Recommendations on the boundary types choice in the optimal ratio of recognitionspeed and required space were given.

Global Update and Trends of Hidden Hunger, 1995-2011: The Hidden Hunger Index

Science.gov (United States)

Stevens, Gretchen A.; Ezzati, Majid; Black, Robert E.; Kraemer, Klaus

2015-01-01

Background Deficiencies in essential vitamins and minerals–also termed hidden hunger–are pervasive and hold negative consequences for the cognitive and physical development of children. Methods This analysis evaluates the change in hidden hunger over time in the form of one composite indicator–the Hidden Hunger Index (HHI)–using an unweighted average of prevalence estimates from the Nutrition Impact Model Study for anemia due to iron deficiency, vitamin A deficiency, and stunting (used as a proxy indicator for zinc deficiency). Net changes from 1995–2011 and population weighted regional means for various time periods are measured. Findings Globally, hidden hunger improved (-6.7 net change in HHI) from 1995–2011. Africa was the only region to see a deterioration in hidden hunger (+1.9) over the studied time period; East Asia and the Pacific performed exceptionally well (-13.0), while other regions improved only slightly. Improvements in HHI were mostly due to reductions in zinc and vitamin A deficiencies, while anemia due to iron deficiency persisted and even increased. Interpretation This analysis is critical for informing and tracking the impact of policy and programmatic efforts to reduce micronutrient deficiencies, to advance the global nutrition agenda, and to achieve the Millennium Development Goals (MDGs). However, there remains an unmet need to invest in gathering frequent, nationally representative, high-quality micronutrient data as we renew our efforts to scale up nutrition, and as we enter the post-2015 development agenda. Funding Preparation of this manuscript was funded by Sight and Life. There was no funding involved in the study design, data collection, analysis, or decision to publish. PMID:26673631

Compressing the hidden variable space of a qubit

OpenAIRE

Montina, Alberto

2010-01-01

In previously exhibited hidden variable models of quantum state preparation and measurement, the number of continuous hidden variables describing the actual state of a single realization is never smaller than the quantum state manifold dimension. We introduce a simple model for a qubit whose hidden variable space is one-dimensional, i.e., smaller than the two-dimensional Bloch sphere. The hidden variable probability distributions associated with the quantum states satisfy reasonable criteria ...

Object and Facial Recognition in Augmented and Virtual Reality: Investigation into Software, Hardware and Potential Uses

Science.gov (United States)

Schulte, Erin

2017-01-01

As augmented and virtual reality grows in popularity, and more researchers focus on its development, other fields of technology have grown in the hopes of integrating with the up-and-coming hardware currently on the market. Namely, there has been a focus on how to make an intuitive, hands-free human-computer interaction (HCI) utilizing AR and VR that allows users to control their technology with little to no physical interaction with hardware. Computer vision, which is utilized in devices such as the Microsoft Kinect, webcams and other similar hardware has shown potential in assisting with the development of a HCI system that requires next to no human interaction with computing hardware and software. Object and facial recognition are two subsets of computer vision, both of which can be applied to HCI systems in the fields of medicine, security, industrial development and other similar areas.

Search for Hidden Particles

CERN Multimedia

Solovev, V

The SHiP Experiment is a new general-purpose fixed target facility at the SPS to search for hidden particles as predicted by a very large number of recently elaborated models of Hidden Sectors which are capable of accommodating dark matter, neutrino oscillations, and the origin of the full baryon asymmetry in the Universe. Specifically, the experiment is aimed at searching for very weakly interacting long lived particles including Heavy Neutral Leptons - right-handed partners of the active neutrinos; light supersymmetric particles - sgoldstinos, etc.; scalar, axion and vector portals to the hidden sector. The high intensity of the SPS and in particular the large production of charm mesons with the 400 GeV beam allow accessing a wide variety of light long-lived exotic particles of such models and of SUSY. Moreover, the facility is ideally suited to study the interactions of tau neutrinos.

Software tool for data mining and its applications

Science.gov (United States)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Higgs Portal into Hidden Sectors

CERN Multimedia

CERN. Geneva

2007-01-01

Several attractive theoretical ideas suggest the existence of one or more 'hidden sectors' consisting of standard model singlet fields, some of which may not be too heavy. There is a profound reason to think that the Higgs sector might provide the first access to these hidden sectors. This scenario could affect Higgs phenomenology in drastic ways.

Hidden in plain sight: the formal, informal, and hidden curricula of a psychiatry clerkship.

Science.gov (United States)

Wear, Delese; Skillicorn, Jodie

2009-04-01

To examine perceptions of the formal, informal, and hidden curricula in psychiatry as they are observed and experienced by (1) attending physicians who have teaching responsibilities for residents and medical students, (2) residents who are taught by those same physicians and who have teaching responsibilities for medical students, and (3) medical students who are taught by attendings and residents during their psychiatry rotation. From June to November 2007, the authors conducted focus groups with attendings, residents, and students in one midwestern academic setting. The sessions were audiotaped, transcribed, and analyzed for themes surrounding the formal, informal, and hidden curricula. All three groups offered a similar belief that the knowledge, skills, and values of the formal curriculum focused on building relationships. Similarly, all three suggested that elements of the informal and hidden curricula were expressed primarily as the values arising from attendings' role modeling, as the nature and amount of time attendings spend with patients, and as attendings' advice arising from experience and intuition versus "textbook learning." Whereas students and residents offered negative values arising from the informal and hidden curricula, attendings did not, offering instead the more positive values they intended to encourage through the informal and hidden curricula. The process described here has great potential in local settings across all disciplines. Asking teachers and learners in any setting to think about how they experience the educational environment and what sense they make of all curricular efforts can provide a reality check for educators and a values check for learners as they critically reflect on the meanings of what they are learning.

A Novel Method for Decoding Any High-Order Hidden Markov Model

Directory of Open Access Journals (Sweden)

Fei Ye

2014-01-01

Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.

Audio-Visual Speech Recognition Using MPEG-4 Compliant Visual Features

Directory of Open Access Journals (Sweden)

Petar S. Aleksic

2002-11-01

Full Text Available We describe an audio-visual automatic continuous speech recognition system, which significantly improves speech recognition performance over a wide range of acoustic noise levels, as well as under clean audio conditions. The system utilizes facial animation parameters (FAPs supported by the MPEG-4 standard for the visual representation of speech. We also describe a robust and automatic algorithm we have developed to extract FAPs from visual data, which does not require hand labeling or extensive training procedures. The principal component analysis (PCA was performed on the FAPs in order to decrease the dimensionality of the visual feature vectors, and the derived projection weights were used as visual features in the audio-visual automatic speech recognition (ASR experiments. Both single-stream and multistream hidden Markov models (HMMs were used to model the ASR system, integrate audio and visual information, and perform a relatively large vocabulary (approximately 1000 words speech recognition experiments. The experiments performed use clean audio data and audio data corrupted by stationary white Gaussian noise at various SNRs. The proposed system reduces the word error rate (WER by 20% to 23% relatively to audio-only speech recognition WERs, at various SNRs (0–30 dB with additive white Gaussian noise, and by 19% relatively to audio-only speech recognition WER under clean audio conditions.

Abelian hidden sectors at a GeV

International Nuclear Information System (INIS)

Morrissey, David E.; Poland, David; Zurek, Kathryn M.

2009-01-01

We discuss mechanisms for naturally generating GeV-scale hidden sectors in the context of weak-scale supersymmetry. Such low mass scales can arise when hidden sectors are more weakly coupled to supersymmetry breaking than the visible sector, as happens when supersymmetry breaking is communicated to the visible sector by gauge interactions under which the hidden sector is uncharged, or if the hidden sector is sequestered from gravity-mediated supersymmetry breaking. We study these mechanisms in detail in the context of gauge and gaugino mediation, and present specific models of Abelian GeV-scale hidden sectors. In particular, we discuss kinetic mixing of a U(1) x gauge force with hypercharge, singlets or bi-fundamentals which couple to both sectors, and additional loop effects. Finally, we investigate the possible relevance of such sectors for dark matter phenomenology, as well as for low- and high-energy collider searches.

Stargate of the Hidden Multiverse

Directory of Open Access Journals (Sweden)

Alexander Antonov

2016-02-01

Full Text Available Concept of Monoverse, which corresponds to the existing broad interpretation of the second postulate of the special theory of relativity, is not consistent with the modern astrophysical reality — existence of the dark matter and the dark energy, the total mass-energy of which is ten times greater than the mass-energy of the visible universe (which has been considered as the entire universe until very recent . This concept does not allow to explain their rather unusual properties — invisibility and lack of baryon content — which would seem to even destroy the very modern understanding of the term ‘matter’. However, all numerous alternative concepts of Multiverses, which have been proposed until today, are unable to explain these properties of the dark matter and dark energy. This article describes a new concept: the concept of the hidden Multiverse and hidden Supermultiverse, which mutual invisibility of parallel universes is explained by the physical reality of imaginary numbers. This concept completely explains the phenomenon of the dark matter and the dark energy. Moreover, it is shown that the dark matter and the dark energy are the experimental evidence for the existence of the hidden Multiverse. Described structure of the hidden Multiverse is fully consistent with the data obtained by the space stations WMAP and Planck. An extremely important property of the hidden Multiverse is an actual possibility of its permeation through stargate located on the Earth.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments.

Science.gov (United States)

Roy, Nirmalya; Misra, Archan; Cook, Diane

2016-02-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional 'hidden' context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions.

A Self-Adaptive Hidden Markov Model for Emotion Classification in Chinese Microblogs

Directory of Open Access Journals (Sweden)

Li Liu

2015-01-01

we propose a modified version of hidden Markov model (HMM classifier, called self-adaptive HMM, whose parameters are optimized by Particle Swarm Optimization algorithms. Since manually labeling large-scale dataset is difficult, we also employ the entropy to decide whether a new unlabeled tweet shall be contained in the training dataset after being assigned an emotion using our HMM-based approach. In the experiment, we collected about 200,000 Chinese tweets from Sina Weibo. The results show that the F-score of our approach gets 76% on happiness and fear and 65% on anger, surprise, and sadness. In addition, the self-adaptive HMM classifier outperforms Naive Bayes and Support Vector Machine on recognition of happiness, anger, and sadness.

Activity Recognition for Personal Time Management

Science.gov (United States)

Prekopcsák, Zoltán; Soha, Sugárka; Henk, Tamás; Gáspár-Papanek, Csaba

We describe an accelerometer based activity recognition system for mobile phones with a special focus on personal time management. We compare several data mining algorithms for the automatic recognition task in the case of single user and multiuser scenario, and improve accuracy with heuristics and advanced data mining methods. The results show that daily activities can be recognized with high accuracy and the integration with the RescueTime software can give good insights for personal time management.

Connected word recognition using a cascaded neuro-computational model

Science.gov (United States)

Hoya, Tetsuya; van Leeuwen, Cees

2016-10-01

We propose a novel framework for processing a continuous speech stream that contains a varying number of words, as well as non-speech periods. Speech samples are segmented into word-tokens and non-speech periods. An augmented version of an earlier-proposed, cascaded neuro-computational model is used for recognising individual words within the stream. Simulation studies using both a multi-speaker-dependent and speaker-independent digit string database show that the proposed method yields a recognition performance comparable to that obtained by a benchmark approach using hidden Markov models with embedded training.

Feature and score fusion based multiple classifier selection for iris recognition.

Science.gov (United States)

Islam, Md Rabiul

2014-01-01

The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Feature and Score Fusion Based Multiple Classifier Selection for Iris Recognition

Directory of Open Access Journals (Sweden)

Md. Rabiul Islam

2014-01-01

Full Text Available The aim of this work is to propose a new feature and score fusion based iris recognition approach where voting method on Multiple Classifier Selection technique has been applied. Four Discrete Hidden Markov Model classifiers output, that is, left iris based unimodal system, right iris based unimodal system, left-right iris feature fusion based multimodal system, and left-right iris likelihood ratio score fusion based multimodal system, is combined using voting method to achieve the final recognition result. CASIA-IrisV4 database has been used to measure the performance of the proposed system with various dimensions. Experimental results show the versatility of the proposed system of four different classifiers with various dimensions. Finally, recognition accuracy of the proposed system has been compared with existing N hamming distance score fusion approach proposed by Ma et al., log-likelihood ratio score fusion approach proposed by Schmid et al., and single level feature fusion approach proposed by Hollingsworth et al.

Experiments on Automatic Recognition of Nonnative Arabic Speech

Directory of Open Access Journals (Sweden)

Douglas O'Shaughnessy

2008-05-01

Full Text Available The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of nonnative speech in a speaker independent, large-vocabulary speech recognition system for modern standard Arabic (MSA. We analyze some major differences at the phonetic level in order to determine which phonemes have a significant part in the recognition performance for both native and nonnative speakers. Special attention is given to specific Arabic phonemes. The performance of an HMM-based Arabic speech recognition system is analyzed with respect to speaker gender and its native origin. The WestPoint modern standard Arabic database from the language data consortium (LDC and the hidden Markov Model Toolkit (HTK are used throughout all experiments. Our study shows that the best performance in the overall phoneme recognition is obtained when nonnative speakers are involved in both training and testing phases. This is not the case when a language model and phonetic lattice networks are incorporated in the system. At the phonetic level, the results show that female nonnative speakers perform better than nonnative male speakers, and that emphatic phonemes yield a significant decrease in performance when they are uttered by both male and female nonnative speakers.

Experiments on Automatic Recognition of Nonnative Arabic Speech

Directory of Open Access Journals (Sweden)

Selouani Sid-Ahmed

2008-01-01

Full Text Available The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of nonnative speech in a speaker independent, large-vocabulary speech recognition system for modern standard Arabic (MSA. We analyze some major differences at the phonetic level in order to determine which phonemes have a significant part in the recognition performance for both native and nonnative speakers. Special attention is given to specific Arabic phonemes. The performance of an HMM-based Arabic speech recognition system is analyzed with respect to speaker gender and its native origin. The WestPoint modern standard Arabic database from the language data consortium (LDC and the hidden Markov Model Toolkit (HTK are used throughout all experiments. Our study shows that the best performance in the overall phoneme recognition is obtained when nonnative speakers are involved in both training and testing phases. This is not the case when a language model and phonetic lattice networks are incorporated in the system. At the phonetic level, the results show that female nonnative speakers perform better than nonnative male speakers, and that emphatic phonemes yield a significant decrease in performance when they are uttered by both male and female nonnative speakers.

Coding with partially hidden Markov models

DEFF Research Database (Denmark)

Forchhammer, Søren; Rissanen, J.

1995-01-01

Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...

Compressing the hidden variable space of a qubit

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

In previously exhibited hidden variable models of quantum state preparation and measurement, the number of continuous hidden variables describing the actual state of single realizations is never smaller than the quantum state manifold dimension. We introduce a simple model for a qubit whose hidden variable space is one-dimensional, i.e., smaller than the two-dimensional Bloch sphere. The hidden variable probability distributions associated with quantum states satisfy reasonable criteria of regularity. Possible generalizations of this shrinking to an N-dimensional Hilbert space are discussed.

Incorporating Speech Recognition into a Natural User Interface

Science.gov (United States)

Chapa, Nicholas

2017-01-01

The Augmented/ Virtual Reality (AVR) Lab has been working to study the applicability of recent virtual and augmented reality hardware and software to KSC operations. This includes the Oculus Rift, HTC Vive, Microsoft HoloLens, and Unity game engine. My project in this lab is to integrate voice recognition and voice commands into an easy to modify system that can be added to an existing portion of a Natural User Interface (NUI). A NUI is an intuitive and simple to use interface incorporating visual, touch, and speech recognition. The inclusion of speech recognition capability will allow users to perform actions or make inquiries using only their voice. The simplicity of needing only to speak to control an on-screen object or enact some digital action means that any user can quickly become accustomed to using this system. Multiple programs were tested for use in a speech command and recognition system. Sphinx4 translates speech to text using a Hidden Markov Model (HMM) based Language Model, an Acoustic Model, and a word Dictionary running on Java. PocketSphinx had similar functionality to Sphinx4 but instead ran on C. However, neither of these programs were ideal as building a Java or C wrapper slowed performance. The most ideal speech recognition system tested was the Unity Engine Grammar Recognizer. A Context Free Grammar (CFG) structure is written in an XML file to specify the structure of phrases and words that will be recognized by Unity Grammar Recognizer. Using Speech Recognition Grammar Specification (SRGS) 1.0 makes modifying the recognized combinations of words and phrases very simple and quick to do. With SRGS 1.0, semantic information can also be added to the XML file, which allows for even more control over how spoken words and phrases are interpreted by Unity. Additionally, using a CFG with SRGS 1.0 produces a Finite State Machine (FSM) functionality limiting the potential for incorrectly heard words or phrases. The purpose of my project was to

Sign language recognition and translation: a multidisciplined approach from the field of artificial intelligence.

Science.gov (United States)

Parton, Becky Sue

2006-01-01

In recent years, research has progressed steadily in regard to the use of computers to recognize and render sign language. This paper reviews significant projects in the field beginning with finger-spelling hands such as "Ralph" (robotics), CyberGloves (virtual reality sensors to capture isolated and continuous signs), camera-based projects such as the CopyCat interactive American Sign Language game (computer vision), and sign recognition software (Hidden Markov Modeling and neural network systems). Avatars such as "Tessa" (Text and Sign Support Assistant; three-dimensional imaging) and spoken language to sign language translation systems such as Poland's project entitled "THETOS" (Text into Sign Language Automatic Translator, which operates in Polish; natural language processing) are addressed. The application of this research to education is also explored. The "ICICLE" (Interactive Computer Identification and Correction of Language Errors) project, for example, uses intelligent computer-aided instruction to build a tutorial system for deaf or hard-of-hearing children that analyzes their English writing and makes tailored lessons and recommendations. Finally, the article considers synthesized sign, which is being added to educational material and has the potential to be developed by students themselves.

A survey of hidden-variables theories

CERN Document Server

Belinfante, F J

1973-01-01

A Survey of Hidden-Variables Theories is a three-part book on the hidden-variable theories, referred in this book as """"theories of the first kind"""". Part I reviews the motives in developing different types of hidden-variables theories. The quest for determinism led to theories of the first kind; the quest for theories that look like causal theories when applied to spatially separated systems that interacted in the past led to theories of the second kind. Parts II and III further describe the theories of the first kind and second kind, respectively. This book is written to make the literat

A classification of hidden-variable properties

International Nuclear Information System (INIS)

Brandenburger, Adam; Yanofsky, Noson

2008-01-01

Hidden variables are extra components added to try to banish counterintuitive features of quantum mechanics. We start with a quantum-mechanical model and describe various properties that can be asked of a hidden-variable model. We present six such properties and a Venn diagram of how they are related. With two existence theorems and three no-go theorems (EPR, Bell and Kochen-Specker), we show which properties of empirically equivalent hidden-variable models are possible and which are not. Formally, our treatment relies only on classical probability models, and physical phenomena are used only to motivate which models to choose

Evolutionary neural network modeling for software cumulative failure time prediction

International Nuclear Information System (INIS)

Tian Liang; Noore, Afzel

2005-01-01

An evolutionary neural network modeling approach for software cumulative failure time prediction based on multiple-delayed-input single-output architecture is proposed. Genetic algorithm is used to globally optimize the number of the delayed input neurons and the number of neurons in the hidden layer of the neural network architecture. Modification of Levenberg-Marquardt algorithm with Bayesian regularization is used to improve the ability to predict software cumulative failure time. The performance of our proposed approach has been compared using real-time control and flight dynamic application data sets. Numerical results show that both the goodness-of-fit and the next-step-predictability of our proposed approach have greater accuracy in predicting software cumulative failure time compared to existing approaches

Perspective: Disclosing hidden sources of funding.

Science.gov (United States)

Resnik, David B

2009-09-01

In this article, the author discusses ethical and policy issues related to the disclosure of hidden sources of funding in research. The author argues that authors have an ethical obligation to disclose hidden sources of funding and that journals should adopt policies to enforce this obligation. Journal policies should require disclosure of hidden sources of funding that authors know about and that have a direct relation to their research. To stimulate this discussion, the author describes a recent case: investigators who conducted a lung cancer screening study had received funding from a private foundation that was supported by a tobacco company, but they did not disclose this relationship to the journal. Investigators and journal editors must be prepared to deal with these issues in a manner that promotes honesty, transparency, fairness, and accountability in research. The development of well-defined, reasonable policies pertaining to hidden sources of funding can be a step in this direction.

Profile hidden Markov models for the detection of viruses within metagenomic sequence data.

Directory of Open Access Journals (Sweden)

Peter Skewes-Cox

Full Text Available Rapid, sensitive, and specific virus detection is an important component of clinical diagnostics. Massively parallel sequencing enables new diagnostic opportunities that complement traditional serological and PCR based techniques. While massively parallel sequencing promises the benefits of being more comprehensive and less biased than traditional approaches, it presents new analytical challenges, especially with respect to detection of pathogen sequences in metagenomic contexts. To a first approximation, the initial detection of viruses can be achieved simply through alignment of sequence reads or assembled contigs to a reference database of pathogen genomes with tools such as BLAST. However, recognition of highly divergent viral sequences is problematic, and may be further complicated by the inherently high mutation rates of some viral types, especially RNA viruses. In these cases, increased sensitivity may be achieved by leveraging position-specific information during the alignment process. Here, we constructed HMMER3-compatible profile hidden Markov models (profile HMMs from all the virally annotated proteins in RefSeq in an automated fashion using a custom-built bioinformatic pipeline. We then tested the ability of these viral profile HMMs ("vFams" to accurately classify sequences as viral or non-viral. Cross-validation experiments with full-length gene sequences showed that the vFams were able to recall 91% of left-out viral test sequences without erroneously classifying any non-viral sequences into viral protein clusters. Thorough reanalysis of previously published metagenomic datasets with a set of the best-performing vFams showed that they were more sensitive than BLAST for detecting sequences originating from more distant relatives of known viruses. To facilitate the use of the vFams for rapid detection of remote viral homologs in metagenomic data, we provide two sets of vFams, comprising more than 4,000 vFams each, in the HMMER3

Use of Splines in Handwritten Character Recognition

OpenAIRE

Sunil Kumar; Gopinath S,; Satish Kumar; Rajesh Chhikara

2010-01-01

Handwritten Character Recognition is software used to identify the handwritten characters and receive and interpret intelligible andwritten input from sources such as manuscript documents. The recent past several years has seen the development of many systems which are able to simulate the human brain actions. Among the many, the neural networks and the artificial intelligence are the most two important paradigms used. In this paper we propose a new algorithm for recognition of handwritten t...

Human body contour data based activity recognition.

Science.gov (United States)

Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

2013-01-01

This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

Post-editing through Speech Recognition

DEFF Research Database (Denmark)

Mesa-Lao, Bartolomé

(i.e. typing, handwriting and speaking) to improve the efficiency and accuracy of the translation process. However, further studies need to be conducted to build up new knowledge about the way in which state-of-the-art speech recognition software can be applied to the post-editing process...

Hidden Statistics of Schroedinger Equation

Science.gov (United States)

Zak, Michail

2011-01-01

Work was carried out in determination of the mathematical origin of randomness in quantum mechanics and creating a hidden statistics of Schr dinger equation; i.e., to expose the transitional stochastic process as a "bridge" to the quantum world. The governing equations of hidden statistics would preserve such properties of quantum physics as superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods.

Segmenting Continuous Motions with Hidden Semi-markov Models and Gaussian Processes

Directory of Open Access Journals (Sweden)

Tomoaki Nakamura

2017-12-01

Full Text Available Humans divide perceived continuous information into segments to facilitate recognition. For example, humans can segment speech waves into recognizable morphemes. Analogously, continuous motions are segmented into recognizable unit actions. People can divide continuous information into segments without using explicit segment points. This capacity for unsupervised segmentation is also useful for robots, because it enables them to flexibly learn languages, gestures, and actions. In this paper, we propose a Gaussian process-hidden semi-Markov model (GP-HSMM that can divide continuous time series data into segments in an unsupervised manner. Our proposed method consists of a generative model based on the hidden semi-Markov model (HSMM, the emission distributions of which are Gaussian processes (GPs. Continuous time series data is generated by connecting segments generated by the GP. Segmentation can be achieved by using forward filtering-backward sampling to estimate the model's parameters, including the lengths and classes of the segments. In an experiment using the CMU motion capture dataset, we tested GP-HSMM with motion capture data containing simple exercise motions; the results of this experiment showed that the proposed GP-HSMM was comparable with other methods. We also conducted an experiment using karate motion capture data, which is more complex than exercise motion capture data; in this experiment, the segmentation accuracy of GP-HSMM was 0.92, which outperformed other methods.

Software Project Management and Measurement on the World-Wide-Web (WWW)

Science.gov (United States)

Callahan, John; Ramakrishnan, Sudhaka

1996-01-01

We briefly describe a system for forms-based, work-flow management that helps members of a software development team overcome geographical barriers to collaboration. Our system, called the Web Integrated Software Environment (WISE), is implemented as a World-Wide-Web service that allows for management and measurement of software development projects based on dynamic analysis of change activity in the workflow. WISE tracks issues in a software development process, provides informal communication between the users with different roles, supports to-do lists, and helps in software process improvement. WISE minimizes the time devoted to metrics collection and analysis by providing implicit delivery of messages between users based on the content of project documents. The use of a database in WISE is hidden from the users who view WISE as maintaining a personal 'to-do list' of tasks related to the many projects on which they may play different roles.

Comparison of HMM and DTW methods in automatic recognition of pathological phoneme pronunciation

OpenAIRE

Wielgat, Robert; Zielinski, Tomasz P.; Swietojanski, Pawel; Zoladz, Piotr; Król, Daniel; Wozniak, Tomasz; Grabias, Stanislaw

2007-01-01

In the paper recently proposed Human Factor Cepstral Coefficients (HFCC) are used to automatic recognition of pathological phoneme pronunciation in speech of impaired children and efficiency of this approach is compared to application of the standard Mel-Frequency Cepstral Coefficients (MFCC) as a feature vector. Both dynamic time warping (DTW), working on whole words or embedded phoneme patterns, and hidden Markov models (HMM) are used as classifiers in the presented research. Obtained resul...

Hidden supersymmetry and Fermion number fractionalization

International Nuclear Information System (INIS)

Akhoury, R.

1985-01-01

This paper discusses how a hidden supersymmetry of the underlying field theories can be used to interpret and to calculate fermion number fractionalization in different dimensions. This is made possible by relating it to a corresponding Witten index of the hidden supersymmetry. The closely related anomalies in odd dimensions are also discussed

The Hidden Reason Behind Children's Misbehavior.

Science.gov (United States)

Nystul, Michael S.

1986-01-01

Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…

Software engineers and nuclear engineers: teaming up to do testing

International Nuclear Information System (INIS)

Kelly, D.; Cote, N.; Shepard, T.

2007-01-01

The software engineering community has traditionally paid little attention to the specific needs of engineers and scientists who develop their own software. Recently there has been increased recognition that specific software engineering techniques need to be found for this group of developers. In this case study, a software engineering group teamed with a nuclear engineering group to develop a software testing strategy. This work examines the types of testing that proved to be useful and examines what each discipline brings to the table to improve the quality of the software product. (author)

Hidden worlds in quantum physics

CERN Document Server

Gouesbet, Gérard

2014-01-01

The past decade has witnessed a resurgence in research and interest in the areas of quantum computation and entanglement. This new book addresses the hidden worlds or variables of quantum physics. Author Gérard Gouesbet studied and worked with a former student of Louis de Broglie, a pioneer of quantum physics. His presentation emphasizes the history and philosophical foundations of physics, areas that will interest lay readers as well as professionals and advanced undergraduate and graduate students of quantum physics. The introduction is succeeded by chapters offering background on relevant concepts in classical and quantum mechanics, a brief history of causal theories, and examinations of the double solution, pilot wave, and other hidden-variables theories. Additional topics include proofs of possibility and impossibility, contextuality, non-locality, classification of hidden-variables theories, and stochastic quantum mechanics. The final section discusses how to gain a genuine understanding of quantum mec...

Speech pattern recognition for forensic acoustic purposes

OpenAIRE

Herrera Martínez, Marcelo; Aldana Blanco, Andrea Lorena; Guzmán Palacios, Ana María

2014-01-01

The present paper describes the development of a software for analysis of acoustic voice parameters (APAVOIX), which can be used for forensic acoustic purposes, based on the speaker recognition and identification. This software enables to observe in a clear manner, the parameters which are sufficient and necessary when performing a comparison between two voice signals, the suspicious and the original one. These parameters are used according to the classic method, generally used by state entit...

Hidden charged dark matter and chiral dark radiation

Science.gov (United States)

Ko, P.; Nagata, Natsumi; Tang, Yong

2017-10-01

In the light of recent possible tensions in the Hubble constant H0 and the structure growth rate σ8 between the Planck and other measurements, we investigate a hidden-charged dark matter (DM) model where DM interacts with hidden chiral fermions, which are charged under the hidden SU(N) and U(1) gauge interactions. The symmetries in this model assure these fermions to be massless. The DM in this model, which is a Dirac fermion and singlet under the hidden SU(N), is also assumed to be charged under the U(1) gauge symmetry, through which it can interact with the chiral fermions. Below the confinement scale of SU(N), the hidden quark condensate spontaneously breaks the U(1) gauge symmetry such that there remains a discrete symmetry, which accounts for the stability of DM. This condensate also breaks a flavor symmetry in this model and Nambu-Goldstone bosons associated with this flavor symmetry appear below the confinement scale. The hidden U(1) gauge boson and hidden quarks/Nambu-Goldstone bosons are components of dark radiation (DR) above/below the confinement scale. These light fields increase the effective number of neutrinos by δNeff ≃ 0.59 above the confinement scale for N = 2, resolving the tension in the measurements of the Hubble constant by Planck and Hubble Space Telescope if the confinement scale is ≲1 eV. DM and DR continuously scatter with each other via the hidden U(1) gauge interaction, which suppresses the matter power spectrum and results in a smaller structure growth rate. The DM sector couples to the Standard Model sector through the exchange of a real singlet scalar mixing with the Higgs boson, which makes it possible to probe our model in DM direct detection experiments. Variants of this model are also discussed, which may offer alternative ways to investigate this scenario.

Adaptive filtering for hidden node detection and tracking in networks.

Science.gov (United States)

Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L

2017-07-01

The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.

The hidden universe

International Nuclear Information System (INIS)

Disney, M.

1985-01-01

Astronomer Disney has followed a somewhat different tack than that of most popular books on cosmology by concentrating on the notion of hidden (as in not directly observable by its own radiation) matter in the universe

Incremental discovery of hidden structure: Applications in theory of elementary particles

International Nuclear Information System (INIS)

Zytkow, J.M.; Fischer, P.J.

1996-01-01

Discovering hidden structure is a challenging, universal research task in Physics, Chemistry, Biology, and other disciplines. Not only must the elements of hidden structure be postulated by the discoverer, but they can only be verified by indirect evidence, at the level of observable objects. In this paper we describe a framework for hidden structure discovery, built on a constructive definition of hidden structure. This definition leads to operators that build models of hidden structure step by step, postulating hidden objects, their combinations and properties, reactions described in terms of hidden objects, and mapping between the hidden and the observed structure. We introduce the operator dependency diagram, which shows the order of operator application and model evaluation. Different observational knowledge supports different evaluation criteria, which lead to different search systems with verifiable sequences of operator applications. Isomorph-free structure generation is another issue critical for efficiency of search. We apply our framework in the system GELL-MANN, that hypothesizes hidden structure for elementary particles and we present the results of a large scale search for quark models

Detecting hidden sources-STUK/HUT team

Energy Technology Data Exchange (ETDEWEB)

Nikkinen, M.; Aarnio, P. [Helsinki Univ. of Technology, Espoo (Finland); Honkamaa, T.; Tiilikainen, H. [Finnish Centre for Radiation and Nuclear Safety, Helsinki (Finland)

1997-12-31

The task of the team was to locate and to identify hidden sources in a specified area in Padasjoki Auttoinen village. The team used AB-420 helicopter of the Finnish Frontier Guard. The team had two measuring systems: HPGe system (relative efficiency 18%) and 5`x5` NaI system. The team found two sources in real-time and additional two sources after 24 h analysis time. After the locations and characteristics of the sources were announced it was found out that altogether six sources would have been possible to find using the measured data. The total number of sources was ten. The NaI detector was good at detecting and locating the sources and HPGe was most useful in identification and calculation of the activity estimates. The following development should be made: 1) larger detectors are needed, 2) the software has to be improved. (This has been performed after the exercise) and 3) the navigation must be based on DGPS. visual navigation causes easily gaps between the flight lines and some sources may not be detected. (au).

Detecting hidden sources-STUK/HUT team

Energy Technology Data Exchange (ETDEWEB)

Nikkinen, M; Aarnio, P [Helsinki Univ. of Technology, Espoo (Finland); Honkamaa, T; Tiilikainen, H [Finnish Centre for Radiation and Nuclear Safety, Helsinki (Finland)

1998-12-31

The task of the team was to locate and to identify hidden sources in a specified area in Padasjoki Auttoinen village. The team used AB-420 helicopter of the Finnish Frontier Guard. The team had two measuring systems: HPGe system (relative efficiency 18%) and 5`x5` NaI system. The team found two sources in real-time and additional two sources after 24 h analysis time. After the locations and characteristics of the sources were announced it was found out that altogether six sources would have been possible to find using the measured data. The total number of sources was ten. The NaI detector was good at detecting and locating the sources and HPGe was most useful in identification and calculation of the activity estimates. The following development should be made: 1) larger detectors are needed, 2) the software has to be improved. (This has been performed after the exercise) and 3) the navigation must be based on DGPS. visual navigation causes easily gaps between the flight lines and some sources may not be detected. (au).

Religious Tolerance in the Hidden Curriculum

Directory of Open Access Journals (Sweden)

Kevin Nobel Kurniawan

2018-03-01

Full Text Available Religious intolerance is spreading within the Indonesian institution of education. Previous studies have shown that the growth of intolerance is due to the state’s regulation and pedagogical apparatus. In contrast to the previous studies, I argue that the intolerance is related to hidden curriculum applied by the institution of education.  Normatively, the hidden curriculum contains the value of religious tolerance. However, factually, the author found that there are practices of intolerance, through the formal and informal spheres in the school’s structure, within the hidden curriculum. This article applies a qualitative approach with a mixed method research strategy to analyze data collected from students, teachers, and alumnis through field observation, in-depth interview, and survey.

Hidden gauge structure of supersymmetric free differential algebras

Energy Technology Data Exchange (ETDEWEB)

Andrianopoli, Laura [DISAT, Politecnico di Torino,Corso Duca degli Abruzzi 24, I-10129 Turin (Italy); INFN - Sezione di Torino,Torino (Italy); D’Auria, Riccardo [DISAT, Politecnico di Torino,Corso Duca degli Abruzzi 24, I-10129 Turin (Italy); Ravera, Lucrezia [DISAT, Politecnico di Torino,Corso Duca degli Abruzzi 24, I-10129 Turin (Italy); INFN - Sezione di Torino,Torino (Italy)

2016-08-16

The aim of this paper is to clarify the role of the nilpotent fermionic generator Q{sup ′} introduced in http://dx.doi.org/10.1016/0550-3213(82)90376-5 and appearing in the hidden supergroup underlying the free differential algebra (FDA) of D=11 supergravity. We give a physical explanation of its role by looking at the gauge properties of the theory. We find that its presence is necessary, in order that the extra 1-forms of the hidden supergroup give rise to the correct gauge transformations of the p-forms of the FDA. This interpretation is actually valid for any supergravity containing antisymmetric tensor fields, and any supersymmetric FDA can always be traded for a hidden Lie superalgebra containing extra fermionic nilpotent generators. As an interesting example we construct the hidden superalgebra associated with the FDA of N=2, D=7 supergravity. In this case we are able to parametrize the mutually non local 2- and 3-form B{sup (2)} and B{sup (3)} in terms of hidden 1-forms and find that supersymmetry and gauge invariance require in general the presence of two nilpotent fermionic generators in the hidden algebra. We propose that our approach, where all the invariances of the FDA are expressed as Lie derivatives of the p-forms in the hidden supergroup manifold, could be an appropriate framework to discuss theories defined in enlarged versions of superspace recently considered in the literature, such us double field theory and its generalizations.

Software for radiation protection

International Nuclear Information System (INIS)

Graffunder, H.

2002-01-01

The software products presented are universally usable programs for radiation protection. The systems were designed in order to establish a comprehensive database specific to radiation protection and, on this basis, model in programs subjects of radiation protection. Development initially focused on the creation of the database. Each software product was to access the same nuclide-specific data; input errors and differences in spelling were to be excluded from the outset. This makes the products more compatible with each other and able to exchange data among each other. The software products are modular in design. Functions recurring in radiation protection are always treated the same way in different programs, and also represented the same way on the program surface. The recognition effect makes it easy for users to familiarize with the products quickly. All software products are written in German and are tailored to the administrative needs and codes and regulations in Germany and in Switzerland. (orig.) [de

Fitting Hidden Markov Models to Psychological Data

Directory of Open Access Journals (Sweden)

Ingmar Visser

2002-01-01

Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.

Geometric phases and hidden local gauge symmetry

International Nuclear Information System (INIS)

Fujikawa, Kazuo

2005-01-01

The analysis of geometric phases associated with level crossing is reduced to the familiar diagonalization of the Hamiltonian in the second quantized formulation. A hidden local gauge symmetry, which is associated with the arbitrariness of the phase choice of a complete orthonormal basis set, becomes explicit in this formulation (in particular, in the adiabatic approximation) and specifies physical observables. The choice of a basis set which specifies the coordinate in the functional space is arbitrary in the second quantization, and a subclass of coordinate transformations, which keeps the form of the action invariant, is recognized as the gauge symmetry. We discuss the implications of this hidden local gauge symmetry in detail by analyzing geometric phases for cyclic and noncyclic evolutions. It is shown that the hidden local symmetry provides a basic concept alternative to the notion of holonomy to analyze geometric phases and that the analysis based on the hidden local gauge symmetry leads to results consistent with the general prescription of Pancharatnam. We however note an important difference between the geometric phases for cyclic and noncyclic evolutions. We also explain a basic difference between our hidden local gauge symmetry and a gauge symmetry (or equivalence class) used by Aharonov and Anandan in their definition of generalized geometric phases

Locating Hidden Servers

National Research Council Canada - National Science Library

Oeverlier, Lasse; Syverson, Paul F

2006-01-01

.... Announced properties include server resistance to distributed DoS. Both the EFF and Reporters Without Borders have issued guides that describe using hidden services via Tor to protect the safety of dissidents as well as to resist censorship...

Recognition of Equations Using a Two-Dimensional Stochastic Context-Free Grammar

Science.gov (United States)

Chou, Philip A.

1989-11-01

We propose using two-dimensional stochastic context-free grammars for image recognition, in a manner analogous to using hidden Markov models for speech recognition. The value of the approach is demonstrated in a system that recognizes printed, noisy equations. The system uses a two-dimensional probabilistic version of the Cocke-Younger-Kasami parsing algorithm to find the most likely parse of the observed image, and then traverses the corresponding parse tree in accordance with translation formats associated with each production rule, to produce eqn I troff commands for the imaged equation. In addition, it uses two-dimensional versions of the Inside/Outside and Baum re-estimation algorithms for learning the parameters of the grammar from a training set of examples. Parsing the image of a simple noisy equation currently takes about one second of cpu time on an Alliant FX/80.

Hidden neural networks

DEFF Research Database (Denmark)

Krogh, Anders Stærmose; Riis, Søren Kamaric

1999-01-01

A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

Recognition of Emotions in Mexican Spanish Speech: An Approach Based on Acoustic Modelling of Emotion-Specific Vowels

Directory of Open Access Journals (Sweden)

Santiago-Omar Caballero-Morales

2013-01-01

Full Text Available An approach for the recognition of emotions in speech is presented. The target language is Mexican Spanish, and for this purpose a speech database was created. The approach consists in the phoneme acoustic modelling of emotion-specific vowels. For this, a standard phoneme-based Automatic Speech Recognition (ASR system was built with Hidden Markov Models (HMMs, where different phoneme HMMs were built for the consonants and emotion-specific vowels associated with four emotional states (anger, happiness, neutral, sadness. Then, estimation of the emotional state from a spoken sentence is performed by counting the number of emotion-specific vowels found in the ASR’s output for the sentence. With this approach, accuracy of 87–100% was achieved for the recognition of emotional state of Mexican Spanish speech.

Low-Budget, Cost-Effective OCR: Optical Character Recognition for MS-DOS Micros.

Science.gov (United States)

Perez, Ernest

1990-01-01

Discusses optical character recognition (OCR) for use with MS-DOS microcomputers. Cost effectiveness is considered, three types of software approaches to character recognition are explained, hardware and operation requirements are described, possible library applications are discussed, future OCR developments are suggested, and a list of OCR…

Microwave background constraints on mixing of photons with hidden photons

International Nuclear Information System (INIS)

Mirizzi, Alessandro; Redondo, Javier; Sigl, Guenter

2008-12-01

Various extensions of the Standard Model predict the existence of hidden photons kinetically mixing with the ordinary photon. This mixing leads to oscillations between photons and hidden photons, analogous to the observed oscillations between different neutrino flavors. In this context, we derive new bounds on the photon-hidden photon mixing parameters using the high precision cosmic microwave background spectral data collected by the Far Infrared Absolute Spectrophotometer instrument on board of the Cosmic Background Explorer. Requiring the distortions of the CMB induced by the photon-hidden photon mixing to be smaller than experimental upper limits, this leads to a bound on the mixing angle χ 0 -7 - 10 -5 for hidden photon masses between 10 -14 eV and 10 -7 eV. This low-mass and low-mixing region of the hidden photon parameter space was previously unconstrained. (orig.)

arXiv HEP Software Foundation Community White Paper Working Group - Software Development, Deployment and Validation

CERN Document Server

Couturier, Benjamin; Grasland, Hadrien; Hegner, Benedikt; Jouvin, Michel; Kane, Meghan; Katz, Daniel S.; Kuhr, Thomas; Lange, David; Mendez Lorenzo, Patricia; Ritter, Martin; Stewart, Graeme Andrew; Valassi, Andrea

The High Energy Phyiscs community has developed and needs to maintain many tens of millions of lines of code and to integrate effectively the work of thousands of developers across large collaborations. Software needs to be built, validated, and deployed across hundreds of sites. Software also has a lifetime of many years, frequently beyond that of the original developer, it must be developed with sustainability in mind. Adequate recognition of software development as a critical task in the HEP community needs to be fostered and an appropriate publication and citation strategy needs to be developed. As part of the HEP Softare Foundation's Community White Paper process a working group on Software Development, Deployment and Validation was formed to examine all of these issues, identify best practice and to formulare recommendations for the next decade. Its report is presented here.

Hidden Crises and Communication: An Interactional Analysis of Hidden Crises

NARCIS (Netherlands)

dr. Annette Klarenbeek

2011-01-01

In this paper I describe the ways in which the communication discipline can make a hidden crisis transparent. For this purpose I examine the concept of crisis entrepreneurship from a communication point of view. Using discourse analysis, I analyse the discursive practices of crisis entrepreneurs in

Hidden Crises and Communication : An Interactional Analysis of Hidden Crises

NARCIS (Netherlands)

dr. Annette Klarenbeek

2011-01-01

In this paper I describe the ways in which the communication discipline can make a hidden crisis transparent. For this purpose I examine the concept of crisis entrepreneurship from a communication point of view. Using discourse analysis, I analyse the discursive practices of crisis entrepreneurs in

Hidden treasures - 50 km points of interests

Science.gov (United States)

Lommi, Matias; Kortelainen, Jaana

2015-04-01

Tampere is third largest city in Finland and a regional centre. During 70's there occurred several communal mergers. Nowadays this local area has both strong and diversed identity - from wilderness and agricultural fields to high density city living. Outside the city center there are interesting geological points unknown for modern city settlers. There is even a local proverb, "Go abroad to Teisko!". That is the area the Hidden Treasures -student project is focused on. Our school Tammerkoski Upper Secondary School (or Gymnasium) has emphasis on visual arts. We are going to offer our art students scientific and artistic experiences and knowledge about the hidden treasures of Teisko area and involve the Teisko inhabitants into this project. Hidden treasures - Precambrian subduction zone and a volcanism belt with dense bed of gold (Au) and arsenic (As), operating goldmines and quarries of minerals and metamorphic slates. - North of subduction zone a homogenic precambrian magmastone area with quarries, products known as Kuru Grey. - Former ashores of post-glasial Lake Näsijärvi and it's sediments enabled the developing agriculture and sustained settlement. Nowadays these ashores have both scenery and biodiversity values. - Old cattle sheds and dairy buildings made of local granite stones related to cultural stonebuilding inheritance. - Local active community of Kapee, about 100 inhabitants. Students will discover information of these "hidden" phenomena, and rendering this information trough Enviromental Art Method. Final form of this project will be published in several artistic and informative geocaches. These caches are achieved by a GPS-based special Hidden Treasures Cycling Route and by a website guiding people to find these hidden points of interests.

Image processing and analysis software development

International Nuclear Information System (INIS)

Shahnaz, R.

1999-01-01

The work presented in this project is aimed at developing a software 'IMAGE GALLERY' to investigate various image processing and analysis techniques. The work was divided into two parts namely the image processing techniques and pattern recognition, which further comprised of character and face recognition. Various image enhancement techniques including negative imaging, contrast stretching, compression of dynamic, neon, diffuse, emboss etc. have been studied. Segmentation techniques including point detection, line detection, edge detection have been studied. Also some of the smoothing and sharpening filters have been investigated. All these imaging techniques have been implemented in a window based computer program written in Visual Basic Neural network techniques based on Perception model have been applied for face and character recognition. (author)

Prediction of Cascading Collapse Occurrence due to the Effect of Hidden Failure of a Protection System using Artificial Neural Network

Directory of Open Access Journals (Sweden)

Nor Hazwani Idris

2017-06-01

Full Text Available Transmission line act as a medium of transportation for electrical energy from a power station to the consumer. There are many factors that could cause the cascading collapse such as instability of voltage and frequency, the change of environment and weather, the software and operator error and also the failure in protection system. Protection system plays an important function in maintaining the stability and reliability of the power grid. Hidden failures in relay protection systems are the primary factors for triggering the cascading collapse. This paper presents an Artificial Neural Network (ANN model for prediction of cascading collapse occurrence due to the effect of hidden failure of protection system. The ANN model has been developed through the normalized training and testing data process with optimum number of hidden layer, the momentum rate and the learning rate. The ANN model employs probability of hidden failure, random number of line limit power flow and exposed line as its input while trip index of cascading collapse occurrence as its output. IEEE 14 bus system is used in this study to illustrate the proposed approach. The performance of the results is analysed in terms of its Mean Square Error (MSE and Correlation Coefficient (R. The results show the ANN model produce reliable prediction of cascading collapse occurrence.

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.

Microwave background constraints on mixing of photons with hidden photons

Energy Technology Data Exchange (ETDEWEB)

Mirizzi, Alessandro [Max-Planck-Institut fuer Physik, Muenchen (Germany); Redondo, Javier [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Sigl, Guenter [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2008-12-15

Various extensions of the Standard Model predict the existence of hidden photons kinetically mixing with the ordinary photon. This mixing leads to oscillations between photons and hidden photons, analogous to the observed oscillations between different neutrino flavors. In this context, we derive new bounds on the photon-hidden photon mixing parameters using the high precision cosmic microwave background spectral data collected by the Far Infrared Absolute Spectrophotometer instrument on board of the Cosmic Background Explorer. Requiring the distortions of the CMB induced by the photon-hidden photon mixing to be smaller than experimental upper limits, this leads to a bound on the mixing angle {chi}{sub 0} hidden photon masses between 10{sup -14} eV and 10{sup -7} eV. This low-mass and low-mixing region of the hidden photon parameter space was previously unconstrained. (orig.)

Hidden symmetries in minimal five-dimensional supergravity

International Nuclear Information System (INIS)

Poessel, Markus; Silva, Sebastian

2004-01-01

We study the hidden symmetries arising in the dimensional reduction of d=5, N=2 supergravity to three dimensions. Extending previous partial results for the bosonic part, we give a derivation that includes fermionic terms, shedding light on the appearance of the local hidden symmetry SO(4) in the reduction

Sensor-Based Human Activity Recognition in a Multi-user Scenario

Science.gov (United States)

Wang, Liang; Gu, Tao; Tao, Xianping; Lu, Jian

Existing work on sensor-based activity recognition focuses mainly on single-user activities. However, in real life, activities are often performed by multiple users involving interactions between them. In this paper, we propose Coupled Hidden Markov Models (CHMMs) to recognize multi-user activities from sensor readings in a smart home environment. We develop a multimodal sensing platform and present a theoretical framework to recognize both single-user and multi-user activities. We conduct our trace collection done in a smart home, and evaluate our framework through experimental studies. Our experimental result shows that we achieve an average accuracy of 85.46% with CHMMs.

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.

Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction

Directory of Open Access Journals (Sweden)

MORARIU, N.

2007-04-01

Full Text Available The paper presents some aspects regarding the joint use of classification and recognition techniques for the activity evolution diagnostication and prediction by means of a set of indexes. Starting from the indexes set there is defined a measure on the patterns set, measure representing a scalar value that characterizes the activity analyzed at each time moment. A pattern is defined by the values of the indexes set at a given time. Over the classes set obtained by means of the classification and recognition techniques is defined a relation that allows the representation of the evolution from negative evolution towards positive evolution. For the diagnostication and prediction the following tools are used: pattern recognition and multilayer perceptron. The data set used in experiments describes the pollution due to CO2 emission from the consumption of fuels in Europe. The paper also presents the REFORME software written by the authors and the results of the experiment obtained with this software.

Local models and hidden nonlocality in Quantum Theory

OpenAIRE

Guerini, Leonardo

2014-01-01

This Master's thesis has two central subjects: the simulation of correlations generated by local measurements on entangled quantum states by local hidden-variables models and the revelation of hidden nonlocality. We present and detail the Werner's local model and the hidden nonlocality of some Werner states of dimension $d\\geq5$, the Gisin-Degorre's local model for a Werner state of dimension $d=2$ and the local model of Hirsch et al. for mixtures of the singlet state and noise, all of them f...

Searching for hidden-charm baryonium signals in QCD sum rules

Energy Technology Data Exchange (ETDEWEB)

Chen, Hua-Xing; Zhou, Dan [Beihang University, School of Physics, Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beijing (China); Chen, Wei [University of Saskatchewan, Department of Physics and Engineering Physics, Saskatoon, SK (Canada); Liu, Xiang [Lanzhou University, School of Physical Science and Technology, Lanzhou (China); Lanzhou University, Research Center for Hadron and CSR Physics, Institute of Modern Physics of CAS, Lanzhou (China); Zhu, Shi-Lin [Peking University, School of Physics, State Key Laboratory of Nuclear Physics and Technology, Beijing (China); Collaborative Innovation Center of Quantum Matter, Beijing (China); Peking University, Center of High Energy Physics, Beijing (China)

2016-11-15

We give an explicit QCD sum rule investigation for hidden-charm baryonium states with the quark content u anti ud anti dc anti c, spin J = 0/1/2/3, and of both positive and negative parities. We systematically construct the relevant local hidden-charm baryonium interpolating currents, which can actually couple to various structures, including hidden-charm baryonium states, charmonium states plus two pions, and hidden-charm tetraquark states plus one pion, etc. We do not know which structure these currents couple to at the beginning, but after sum rule analyses we can obtain some information. We find some of them can couple to hidden-charm baryonium states, using which we evaluate the masses of the lowest-lying hidden-charm baryonium states with quantum numbers J{sup P} = 2{sup -}/3{sup -}/0{sup +}/1{sup +}/2{sup +} to be around 5.0 GeV. We suggest to search for hidden-charm baryonium states, especially the one of J = 3{sup -}, in the D-wave J/ψππ and P-wave J/ψρ and J/ψω channels in this energy region. (orig.)

Hidden symmetries in five-dimensional supergravity

International Nuclear Information System (INIS)

Poessel, M.

2003-05-01

This thesis is concerned with the study of hidden symmetries in supergravity, which play an important role in the present picture of supergravity and string theory. Concretely, the appearance of a hidden G 2(+2) /SO(4) symmetry is studied in the dimensional reduction of d=5, N=2 supergravity to three dimensions - a parallel model to the more famous E 8(+8) /SO(16) case in eleven-dimensional supergravity. Extending previous partial results for the bosonic part, I give a derivation that includes fermionic terms. This sheds new light on the appearance of the local hidden symmetry SO(4) in the reduction, and shows up an unusual feature which follows from an analysis of the R-symmetry associated with N=4 supergravity and of the supersymmetry variations, and which has no parallel in the eleven-dimensional case: The emergence of an additional SO(3) as part of the enhanced local symmetry, invisible in the dimensional reduction of the gravitino, and corresponding to the fact that, of the SO(4) used in the coset model, only the diagonal SO(3) is visible immediately upon dimensional reduction. The uncovering of the hidden symmetries proceeds via the construction of the proper coset gravity in three dimensions, and matching it with the Lagrangian obtained from the reduction. (orig.)

Voice Recognition Interface in the Rehabilitation of Combat Amputees

National Research Council Canada - National Science Library

Lenhart, Martha; Yancosek, Kathleen E

2004-01-01

The goal of this pilot study is to assess the impact of training on voice recognition software as part of the rehabilitation process that Military patients with amputation, or peripheral nerve loss...

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

An Online Full-Body Motion Recognition Method Using Sparse and Deficient Signal Sequences

Directory of Open Access Journals (Sweden)

Chengyu Guo

2014-01-01

Full Text Available This paper presents a method to recognize continuous full-body human motion online by using sparse, low-cost sensors. The only input signals needed are linear accelerations without any rotation information, which are provided by four Wiimote sensors attached to the four human limbs. Based on the fused hidden Markov model (FHMM and autoregressive process, a predictive fusion model (PFM is put forward, which considers the different influences of the upper and lower limbs, establishes HMM for each part, and fuses them using a probabilistic fusion model. Then an autoregressive process is introduced in HMM to predict the gesture, which enables the model to deal with incomplete signal data. In order to reduce the number of alternatives in the online recognition process, a graph model is built that rejects parts of motion types based on the graph structure and previous recognition results. Finally, an online signal segmentation method based on semantics information and PFM is presented to finish the efficient recognition task. The results indicate that the method is robust with a high recognition rate of sparse and deficient signals and can be used in various interactive applications.

QCD sum rule study of hidden-charm pentaquarks

Energy Technology Data Exchange (ETDEWEB)

Chen, Hua-Xing; Cui, Er-Liang [Beihang University, School of Physics and Beijing Key Laboratory of Advanced Nuclear Materials and Physics, Beijing (China); Chen, Wei; Steele, T.G. [University of Saskatchewan, Department of Physics and Engineering Physics, Saskatoon, Saskatchewan (Canada); Liu, Xiang [Lanzhou University, School of Physical Science and Technology, Lanzhou (China); Lanzhou University and Institute of Modern Physics of CAS, Research Center for Hadron and CSR Physics, Lanzhou (China); Zhu, Shi-Lin [Peking University, School of Physics and State Key Laboratory of Nuclear Physics and Technology, Beijing (China); Collaborative Innovation Center of Quantum Matter, Beijing (China); Peking University, Center of High Energy Physics, Beijing (China)

2016-10-15

We study the mass spectra of hidden-charm pentaquarks having spin J = (1)/(2)/(3)/(2)/(5)/(2) and quark contents uudc anti c. We systematically construct all the relevant local hidden-charm pentaquark currents, and we select some of them to perform QCD sum rule analyses. We find that the P{sub c}(4380) and P{sub c}(4450) can be identified as hidden-charm pentaquark states composed of an anti-charmed meson and a charmed baryon. Besides them, we also find (a) the lowest-lying hidden-charm pentaquark state of J{sup P} = 1/2{sup -} has the mass 4.33{sup +0.17}{sub -0.13} GeV, while the one of J{sup P} = 1/2{sup +} is significantly higher, that is, around 4.7-4.9 GeV; (b) the lowest-lying hidden-charm pentaquark state of J{sup P} = 3/2{sup -} has the mass 4.37{sup +0.18}{sub -0.13} GeV, consistent with the P{sub c}(4380) of J{sup P} = 3/2{sup -}, while the one of J{sup P} = 3/2{sup +} is also significantly higher, that is, above 4.6 GeV; (c) the hidden-charm pentaquark state of J{sup P} = 5/2{sup -} has a mass around 4.5-4.6 GeV, slightly larger than the P{sub c}(4450) of J{sup P} = 5/2{sup +}. (orig.)

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.

RECOGNITION DESIGN OF LICENSE PLATE AND CAR TYPE USING TESSERACT OCR AND EmguCV

Directory of Open Access Journals (Sweden)

Antonius Herusutopo

2012-10-01

Full Text Available The goal of the research is to design and implement software that can recognize license plates and car types from images. The method used for the research is soft computing using library of EmguCV. There are four phases in creating the software, i.e., input image process, pre-processing, training processing and recognition. Firstly, user enters the car image. Then, the program reads and does pre-processing the image from bitmap form into vector. The next process is training process, which is learning phase in order the system to be able recognize an object (in this case license plate and car type, and in the end is the recognition process itself. The result is data about the car types and the license plates that have been entered. Using simulation, this software successfully recognized license plate by 80.223% accurate and car type 75% accurate.Keywords: Image; Pre-Processing; License plate and Car Type Recognition, Training

Sociocultural Dimension of Hidden Content in a Professional Language Curriculum

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Ekaterina E. Shishlova

2017-12-01

Full Text Available Introduction: studying curriculum as a pedagogical problem has traditionally been reduced to the analysis of its explicit content, set in official educational documents. However, a much less studied hidden content plays a significant role in education. So, what is the role of the hidden curriculum during professional language training? The purpose of the article is to determine the potential impact of hidden curriculum on students’ conceptual worldview. Comparing the worldview presented in textbooks with students’ one has allowed us to estimate the rate of influence of hidden curr iculum. Materials and Methods: the methodological basis of the work is the cultural concept of personalityoriented education. The methodology for studying the role of hidden curriculum includes four stages: at the first stage, the authors set the criteria for selecting textbooks for analysis and do the selection; at the second stage, the authors select sociocultural concepts for analysis; at the third stage, the scheme of analysis is designed and the analysis of textbooks is done; at the fourth stage, the authors identify the potential influence of hidden curriculum on students’ conceptual worldview. Results: the structure of hidden curriculum has been determined and the scheme for analysing its subject component has been developed. The authors have identified a significant influence of hidden curriculum on students’ worldview, which represents the scientific novelty of the article. Discussion and Conclusions: the article gives the definition of a hidden curriculum which is new for Russian pedagogy and presents a methodology for its analysis in EFL textbooks. That analysis is recommended to be conducted when selecting teaching materials both i n languages and other humanities.

Infinite hidden conditional random fields for human behavior analysis.

Science.gov (United States)

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

2013-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.

Science and Software

Science.gov (United States)

Zelt, C. A.

2017-12-01

Earth science attempts to understand how the earth works. This research often depends on software for modeling, processing, inverting or imaging. Freely sharing open-source software is essential to prevent reinventing the wheel and allows software to be improved and applied in ways the original author may never have envisioned. For young scientists, releasing software can increase their name ID when applying for jobs and funding, and create opportunities for collaborations when scientists who collect data want the software's creator to be involved in their project. However, we frequently hear scientists say software is a tool, it's not science. Creating software that implements a new or better way of earth modeling or geophysical processing, inverting or imaging should be viewed as earth science. Creating software for things like data visualization, format conversion, storage, or transmission, or programming to enhance computational performance, may be viewed as computer science. The former, ideally with an application to real data, can be published in earth science journals, the latter possibly in computer science journals. Citations in either case should accurately reflect the impact of the software on the community. Funding agencies need to support more software development and open-source releasing, and the community should give more high-profile awards for developing impactful open-source software. Funding support and community recognition for software development can have far reaching benefits when the software is used in foreseen and unforeseen ways, potentially for years after the original investment in the software development. For funding, an open-source release that is well documented should be required, with example input and output files. Appropriate funding will provide the incentive and time to release user-friendly software, and minimize the need for others to duplicate the effort. All funded software should be available through a single web site

Detecting hidden particles with MATHUSLA

Science.gov (United States)

Evans, Jared A.

2018-03-01

A hidden sector containing light long-lived particles provides a well-motivated place to find new physics. The recently proposed MATHUSLA experiment has the potential to be extremely sensitive to light particles originating from rare meson decays in the very long lifetime region. In this work, we illustrate this strength with the specific example of a light scalar mixed with the standard model-like Higgs boson, a model where MATHUSLA can further probe unexplored parameter space from exotic Higgs decays. Design augmentations should be considered in order to maximize the ability of MATHUSLA to discover very light hidden sector particles.

Zipf exponent of trajectory distribution in the hidden Markov model

Science.gov (United States)

Bochkarev, V. V.; Lerner, E. Yu

2014-03-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.

Zipf exponent of trajectory distribution in the hidden Markov model

International Nuclear Information System (INIS)

Bochkarev, V V; Lerner, E Yu

2014-01-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different

Deep Belief Networks Based Toponym Recognition for Chinese Text

Directory of Open Access Journals (Sweden)

Shu Wang

2018-06-01

Full Text Available In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo

SHIFT: server for hidden stops analysis in frame-shifted translation.

Science.gov (United States)

Gupta, Arun; Singh, Tiratha Raj

2013-02-23

Frameshift is one of the three classes of recoding. Frame-shifts lead to waste of energy, resources and activity of the biosynthetic machinery. In addition, some peptides synthesized after frame-shifts are probably cytotoxic which serve as plausible cause for innumerable number of diseases and disorders such as muscular dystrophies, lysosomal storage disorders, and cancer. Hidden stop codons occur naturally in coding sequences among all organisms. These codons are associated with the early termination of translation for incorrect reading frame selection and help to reduce the metabolic cost related to the frameshift events. Researchers have identified several consequences of hidden stop codons and their association with myriad disorders. However the wealth of information available is speckled and not effortlessly acquiescent to data-mining. To reduce this gap, this work describes an algorithmic web based tool to study hidden stops in frameshifted translation for all the lineages through respective genetic code systems. This paper describes SHIFT, an algorithmic web application tool that provides a user-friendly interface for identifying and analyzing hidden stops in frameshifted translation of genomic sequences for all available genetic code systems. We have calculated the correlation between codon usage frequencies and the plausible contribution of codons towards hidden stops in an off-frame context. Markovian chains of various order have been used to model hidden stops in frameshifted peptides and their evolutionary association with naturally occurring hidden stops. In order to obtain reliable and persuasive estimates for the naturally occurring and predicted hidden stops statistical measures have been implemented. This paper presented SHIFT, an algorithmic tool that allows user-friendly exploration, analysis, and visualization of hidden stop codons in frameshifted translations. It is expected that this web based tool would serve as a useful complement for

Asymptotics for Estimating Equations in Hidden Markov Models

DEFF Research Database (Denmark)

Hansen, Jørgen Vinsløv; Jensen, Jens Ledet

Results on asymptotic normality for the maximum likelihood estimate in hidden Markov models are extended in two directions. The stationarity assumption is relaxed, which allows for a covariate process influencing the hidden Markov process. Furthermore a class of estimating equations is considered...

A hidden service model based on HS-HS anonymous network

Science.gov (United States)

Meng, Yitong; Zhao, Xing; Fei, Jinlong; Zhu, Yuefei

2017-10-01

The Hidden Service provided by Tor anonymous network can effectively protect the anonymity and security of the Hidden server, this article through the analysis of the data packet structure of Tor, three jump transmission mechanism and link establishment protocol and Hidden Service communication process, in view of the Hidden node number too much, link building Service for too long and too redundant link problem. An improved hidden service model HS-HS is proposed that incorporating multiple transmission link and reuse, and at the same time will be important transit point for reuse protection link anonymity, through the ExperimenTor simulation environment test, verify the improved model of HS-HS can be more effective in guarantee anonymity and security, improve the overall efficiency of data transmission, to meet the needs of today's anonymous service.

VISIBLE COSTS AND HIDDEN COSTS IN THE BAKING INDUSTRY

Directory of Open Access Journals (Sweden)

Criveanu Maria

2013-04-01

Full Text Available Hidden costs are present in the activity of any company, hardly identified in the traditional administrative accounting. The high levels of the hidden costs and their unknown presence have serious consequences on the decisions made by the managers. This paper aims at presenting some aspects related to the hidden costs that occur in the activity of the companies in the baking industry and the possibilities to reduce their level.

The hidden values

DEFF Research Database (Denmark)

Rasmussen, Birgitte; Jensen, Karsten Klint

“The Hidden Values - Transparency in Decision-Making Processes Dealing with Hazardous Activities”. The report seeks to shed light on what is needed to create a transparent framework for political and administrative decisions on the use of GMOs and chemical products. It is our hope that the report...

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.

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

Science.gov (United States)

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

Suppressing the QCD axion abundance by hidden monopoles

International Nuclear Information System (INIS)

Kawasaki, Masahiro

2015-11-01

We study the Witten effect of hidden monopoles on the QCD axion dynamics, and show that its abundance as well as isocurvature perturbations can be significantly suppressed if there is a sufficient amount of hidden monopoles. When the hidden monopoles make up a significant fraction of dark matter, the Witten effect suppresses the abundance of axion with the decay constant smaller than 10 12 GeV. The cosmological domain wall problem of the QCD axion can also be avoided, relaxing the upper bound on the decay constant when the Peccei-Quinn symmetry is spontaneously broken after inflation.

Human gait recognition by pyramid of HOG feature on silhouette images

Science.gov (United States)

Yang, Guang; Yin, Yafeng; Park, Jeanrok; Man, Hong

2013-03-01

As a uncommon biometric modality, human gait recognition has a great advantage of identify people at a distance without high resolution images. It has attracted much attention in recent years, especially in the fields of computer vision and remote sensing. In this paper, we propose a human gait recognition framework that consists of a reliable background subtraction method followed by the pyramid of Histogram of Gradient (pHOG) feature extraction on the silhouette image, and a Hidden Markov Model (HMM) based classifier. Through background subtraction, the silhouette of human gait in each frame is extracted and normalized from the raw video sequence. After removing the shadow and noise in each region of interest (ROI), pHOG feature is computed on the silhouettes images. Then the pHOG features of each gait class will be used to train a corresponding HMM. In the test stage, pHOG feature will be extracted from each test sequence and used to calculate the posterior probability toward each trained HMM model. Experimental results on the CASIA Gait Dataset B1 demonstrate that with our proposed method can achieve very competitive recognition rate.

Robotic Software Integration Using MARIE

Directory of Open Access Journals (Sweden)

Carle Côté

2006-03-01

Full Text Available This paper presents MARIE, a middleware framework oriented towards developing and integrating new and existing software for robotic systems. By using a generic communication framework, MARIE aims to create a flexible distributed component system that allows robotics developers to share software programs and algorithms, and design prototypes rapidly based on their own integration needs. The use of MARIE is illustrated with the design of a socially interactive autonomous mobile robot platform capable of map building, localization, navigation, tasks scheduling, sound source localization, tracking and separation, speech recognition and generation, visual tracking, message reading and graphical interaction using a touch screen interface.

Deep generative learning of location-invariant visual word recognition

Science.gov (United States)

Di Bono, Maria Grazia; Zorzi, Marco

2013-01-01

It is widely believed that orthographic processing implies an approximate, flexible coding of letter position, as shown by relative-position and transposition priming effects in visual word recognition. These findings have inspired alternative proposals about the representation of letter position, ranging from noisy coding across the ordinal positions to relative position coding based on open bigrams. This debate can be cast within the broader problem of learning location-invariant representations of written words, that is, a coding scheme abstracting the identity and position of letters (and combinations of letters) from their eye-centered (i.e., retinal) locations. We asked whether location-invariance would emerge from deep unsupervised learning on letter strings and what type of intermediate coding would emerge in the resulting hierarchical generative model. We trained a deep network with three hidden layers on an artificial dataset of letter strings presented at five possible retinal locations. Though word-level information (i.e., word identity) was never provided to the network during training, linear decoding from the activity of the deepest hidden layer yielded near-perfect accuracy in location-invariant word recognition. Conversely, decoding from lower layers yielded a large number of transposition errors. Analyses of emergent internal representations showed that word selectivity and location invariance increased as a function of layer depth. Word-tuning and location-invariance were found at the level of single neurons, but there was no evidence for bigram coding. Finally, the distributed internal representation of words at the deepest layer showed higher similarity to the representation elicited by the two exterior letters than by other combinations of two contiguous letters, in agreement with the hypothesis that word edges have special status. These results reveal that the efficient coding of written words—which was the model's learning objective�

Deep generative learning of location-invariant visual word recognition.

Science.gov (United States)

Di Bono, Maria Grazia; Zorzi, Marco

2013-01-01

It is widely believed that orthographic processing implies an approximate, flexible coding of letter position, as shown by relative-position and transposition priming effects in visual word recognition. These findings have inspired alternative proposals about the representation of letter position, ranging from noisy coding across the ordinal positions to relative position coding based on open bigrams. This debate can be cast within the broader problem of learning location-invariant representations of written words, that is, a coding scheme abstracting the identity and position of letters (and combinations of letters) from their eye-centered (i.e., retinal) locations. We asked whether location-invariance would emerge from deep unsupervised learning on letter strings and what type of intermediate coding would emerge in the resulting hierarchical generative model. We trained a deep network with three hidden layers on an artificial dataset of letter strings presented at five possible retinal locations. Though word-level information (i.e., word identity) was never provided to the network during training, linear decoding from the activity of the deepest hidden layer yielded near-perfect accuracy in location-invariant word recognition. Conversely, decoding from lower layers yielded a large number of transposition errors. Analyses of emergent internal representations showed that word selectivity and location invariance increased as a function of layer depth. Word-tuning and location-invariance were found at the level of single neurons, but there was no evidence for bigram coding. Finally, the distributed internal representation of words at the deepest layer showed higher similarity to the representation elicited by the two exterior letters than by other combinations of two contiguous letters, in agreement with the hypothesis that word edges have special status. These results reveal that the efficient coding of written words-which was the model's learning objective

Deep generative learning of location-invariant visual word recognition

Directory of Open Access Journals (Sweden)

Maria Grazia eDi Bono

2013-09-01

Full Text Available It is widely believed that orthographic processing implies an approximate, flexible coding of letter position, as shown by relative-position and transposition priming effects in visual word recognition. These findings have inspired alternative proposals about the representation of letter position, ranging from noisy coding across the ordinal positions to relative position coding based on open bigrams. This debate can be cast within the broader problem of learning location-invariant representations of written words, that is, a coding scheme abstracting the identity and position of letters (and combinations of letters from their eye-centred (i.e., retinal locations. We asked whether location-invariance would emerge from deep unsupervised learning on letter strings and what type of intermediate coding would emerge in the resulting hierarchical generative model. We trained a deep network with three hidden layers on an artificial dataset of letter strings presented at five possible retinal locations. Though word-level information (i.e., word identity was never provided to the network during training, linear decoding from the activity of the deepest hidden layer yielded near-perfect accuracy in location-invariant word recognition. Conversely, decoding from lower layers yielded a large number of transposition errors. Analyses of emergent internal representations showed that word selectivity and location invariance increased as a function of layer depth. Conversely, there was no evidence for bigram coding. Finally, the distributed internal representation of words at the deepest layer showed higher similarity to the representation elicited by the two exterior letters than by other combinations of two contiguous letters, in agreement with the hypothesis that word edges have special status. These results reveal that the efficient coding of written words – which was the model’s learning objective – is largely based on letter-level information.

Context Tree Estimation in Variable Length Hidden Markov Models

OpenAIRE

Dumont, Thierry

2011-01-01

We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...

Extracting hidden-photon dark matter from an LC-circuit

International Nuclear Information System (INIS)

Arias, Paola; Arza, Ariel; Gamboa, Jorge; Mendez, Fernando

2014-11-01

We point out that a cold dark matter condensate made of gauge bosons from an extra hidden U(1) sector - dubbed hidden-photons - can create a small, oscillating electric density current. Thus, they could also be searched for in the recently proposed LC-circuit setup conceived for axion cold dark matter search by Sikivie, Sullivan and Tanner. We estimate the sensitivity of this setup for hidden-photon cold dark matter and we find it could cover a sizable, so far unexplored parameter space.

Extracting Hidden-Photon Dark Matter From an LC-Circuit

CERN Document Server

Arias, Paola; Döbrich, Babette; Gamboa, Jorge; Méndez, Fernando

2015-01-01

We point out that a cold dark matter condensate made of gauge bosons from an extra hidden U(1) sector - dubbed hidden- photons - can create a small, oscillating electric density current. Thus, they could also be searched for in the recently proposed LC-circuit setup conceived for axion cold dark matter search by Sikivie, Sullivan and Tanner. We estimate the sensitivity of this setup for hidden-photon cold dark matter and we find it could cover a sizable, so far unexplored parameter space.

Hidden photons in beam dump experiments and in connection with dark matter

Energy Technology Data Exchange (ETDEWEB)

Andreas, Sarah

2012-12-15

Hidden sectors with light extra U(1) gauge bosons, so-called hidden photons, recently received much interest as natural feature of beyond standard model scenarios like string theory and SUSY and because of their possible connection to dark matter. This paper presents limits on hidden photons from past electron beam dump experiments including two new limits from experiments at KEK and Orsay. Additionally, various hidden sector models containing both a hidden photon and a dark matter candidate are discussed with respect to their viability and potential signatures in direct detection.

Hidden photons in beam dump experiments and in connection with dark matter

International Nuclear Information System (INIS)

Andreas, Sarah

2012-12-01

Hidden sectors with light extra U(1) gauge bosons, so-called hidden photons, recently received much interest as natural feature of beyond standard model scenarios like string theory and SUSY and because of their possible connection to dark matter. This paper presents limits on hidden photons from past electron beam dump experiments including two new limits from experiments at KEK and Orsay. Additionally, various hidden sector models containing both a hidden photon and a dark matter candidate are discussed with respect to their viability and potential signatures in direct detection.

Search for hidden particles with the SHiP experiment

Energy Technology Data Exchange (ETDEWEB)

Hagner, Caren; Bick, Daniel; Bieschke, Stefan; Ebert, Joachim; Schmidt-Parzefall, Walter [Universitaet Hamburg, Institut fuer Experimentalphysik, Luruper Chaussee 149, 22761 Hamburg (Germany)

2016-07-01

Many theories beyond the standard model predict long lived neutral (hidden) particles. There might be a whole Hidden Sector (HS) of weakly interacting particles, which cannot be detected in existing high energy experiments. The SHiP experiment (Search for Hidden Particles) requires a high intensity beam dump, which could be realized by a new facility at the CERN SPS accelerator. New superweakly interacting particles with masses below O(10) GeV could be produced in the beam dump and detected in a general purpose Hidden Sector (HS) detector. In addition there will be a dedicated tau neutrino subdetector. I present the major requirements and technical challenges for the HS detector and discuss how the HS can be accessed through several portals: neutrino portal, scalar portal, vector portal and many more.

Simple and efficient method for region of interest value extraction from picture archiving and communication system viewer with optical character recognition software and macro program.

Science.gov (United States)

Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck

2015-01-01

The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

Multilayer Neural Networks with Extensively Many Hidden Units

International Nuclear Information System (INIS)

Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido

2001-01-01

The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones

Hidden Area and Mechanical Nonlinearities in Freestanding Graphene

Science.gov (United States)

Nicholl, Ryan J. T.; Lavrik, Nickolay V.; Vlassiouk, Ivan; Srijanto, Bernadeta R.; Bolotin, Kirill I.

2017-06-01

We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By comparing the data obtained through these two techniques, we determined the geometric hidden area which quantifies the crumpling strength. While the devices with hidden area ˜0 % obeyed linear mechanics with biaxial stiffness 428 ±10 N /m , specimens with hidden area in the range 0.5%-1.0% were found to obey an anomalous nonlinear Hooke's law with an exponent ˜0.1 .

Trends in computer hardware and software.

Science.gov (United States)

Frankenfeld, F M

1993-04-01

Previously identified and current trends in the development of computer systems and in the use of computers for health care applications are reviewed. Trends identified in a 1982 article were increasing miniaturization and archival ability, increasing software costs, increasing software independence, user empowerment through new software technologies, shorter computer-system life cycles, and more rapid development and support of pharmaceutical services. Most of these trends continue today. Current trends in hardware and software include the increasing use of reduced instruction-set computing, migration to the UNIX operating system, the development of large software libraries, microprocessor-based smart terminals that allow remote validation of data, speech synthesis and recognition, application generators, fourth-generation languages, computer-aided software engineering, object-oriented technologies, and artificial intelligence. Current trends specific to pharmacy and hospitals are the withdrawal of vendors of hospital information systems from the pharmacy market, improved linkage of information systems within hospitals, and increased regulation by government. The computer industry and its products continue to undergo dynamic change. Software development continues to lag behind hardware, and its high cost is offsetting the savings provided by hardware.

A methodology of error detection: Improving speech recognition in radiology

OpenAIRE

Voll, Kimberly Dawn

2006-01-01

Automated speech recognition (ASR) in radiology report dictation demands highly accurate and robust recognition software. Despite vendor claims, current implementations are suboptimal, leading to poor accuracy, and time and money wasted on proofreading. Thus, other methods must be considered for increasing the reliability and performance of ASR before it is a viable alternative to human transcription. One such method is post-ASR error detection, used to recover from the inaccuracy of speech r...

Extracting hidden-photon dark matter from an LC-circuit

International Nuclear Information System (INIS)

Arias, Paola; Arza, Ariel; Gamboa, Jorge; Mendez, Fernando; Doebrich, Babette

2015-01-01

We point out that a cold dark matter condensate made of gauge bosons from an extra hidden U(1) sector - dubbed hidden photons - can create a small, oscillating electric density current. Thus, they could also be searched for in the recently proposed LC-circuit setup conceived for axion cold dark matter search by Sikivie, Sullivan and Tanner. We estimate the sensitivity of this setup for hidden-photon cold dark matter and we find it could cover a sizable, so far unexplored parameter space. (orig.)

Communication Skills Training Exploiting Multimodal Emotion Recognition

Science.gov (United States)

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2017-01-01

The teaching of communication skills is a labour-intensive task because of the detailed feedback that should be given to learners during their prolonged practice. This study investigates to what extent our FILTWAM facial and vocal emotion recognition software can be used for improving a serious game (the Communication Advisor) that delivers a…

Petro Rents, Political Institutions, and Hidden Wealth

DEFF Research Database (Denmark)

Andersen, Jørgen Juel; Johannesen, Niels; Lassen, David Dreyer

2017-01-01

Do political institutions limit rent seeking by politicians? We study the transformation of petroleum rents, almost universally under direct government control, into hidden wealth using unique data on bank deposits in offshore financial centers that specialize in secrecy and asset protection. Our...... rulers is diverted to secret accounts. We find very limited evidence that shocks to other types of income not directly controlled by governments affect hidden wealth....

Hidden charm molecules in a finite volume

International Nuclear Information System (INIS)

Albaladejo, M.; Hidalgo-Duque, C.; Nieves, J.; Oset, E.

2014-01-01

In the present paper we address the interaction of charmed mesons in hidden charm channels in a finite box. We use the interaction from a recent model based on heavy quark spin symmetry that predicts molecules of hidden charm in the infinite volume. The energy levels in the box are generated within this model, and several methods for the analysis of these levels ("inverse problem") are investigated. (author)

B-graph sampling to estimate the size of a hidden population

NARCIS (Netherlands)

Spreen, M.; Bogaerts, S.

2015-01-01

Link-tracing designs are often used to estimate the size of hidden populations by utilizing the relational links between their members. A major problem in studies of hidden populations is the lack of a convenient sampling frame. The most frequently applied design in studies of hidden populations is

GenRGenS: Software for Generating Random Genomic Sequences and Structures

OpenAIRE

Ponty , Yann; Termier , Michel; Denise , Alain

2006-01-01

International audience; GenRGenS is a software tool dedicated to randomly generating genomic sequences and structures. It handles several classes of models useful for sequence analysis, such as Markov chains, hidden Markov models, weighted context-free grammars, regular expressions and PROSITE expressions. GenRGenS is the only program that can handle weighted context-free grammars, thus allowing the user to model and to generate structured objects (such as RNA secondary structures) of any giv...

Desarrollo de un software de reconocimiento de imagen para ensayos EMC de inmunidad

OpenAIRE

Cerro Gálvez, Ibán

2012-01-01

Desenvolupar un software de reconeixement d'imatge per a detectar mal funcionaments durant els assaigs d'immunitat d'EMC. [ANGLÈS] Develop an image recognition software to detect errors during EMC immunity test. [CASTELLÀ] Desarrollar un software de reconocimiento de imagen para detectar el mal funcionamiento durante los ensayos de inmunidad del EMC. [CATALÀ] Desenvolupar un software de reconeixement d'imatge per a detectar mal funcionaments durant els assaigs d'immunitat d'EMC.

Hidden Agendas in Marriage: Affective and Longitudinal Dimensions.

Science.gov (United States)

Krokoff, Lowell J.

1990-01-01

Examines how couples' discussions of troublesome problems reveal hidden agendas (issues not directly discussed or explored). Finds disgust and contempt are at the core of both love and respect agendas for husbands and wives. Finds that wives' more than husbands' hidden agendas are directly predictive of how negatively they argue at home. (SR)

A classification of marked hijaiyah letters' pronunciation using hidden Markov model

Science.gov (United States)

Wisesty, Untari N.; Mubarok, M. Syahrul; Adiwijaya

2017-08-01

Hijaiyah letters are the letters that arrange the words in Al Qur'an consisting of 28 letters. They symbolize the consonant sounds. On the other hand, the vowel sounds are symbolized by harokat/marks. Speech recognition system is a system used to process the sound signal to be data so that it can be recognized by computer. To build the system, some stages are needed i.e characteristics/feature extraction and classification. In this research, LPC and MFCC extraction method, K-Means Quantization vector and Hidden Markov Model classification are used. The data used are the 28 letters and 6 harakat with the total class of 168. After several are testing done, it can be concluded that the system can recognize the pronunciation pattern of marked hijaiyah letter very well in the training data with its highest accuracy of 96.1% using the feature of LPC extraction and 94% using the MFCC. Meanwhile, when testing system is used, the accuracy decreases up to 41%.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

Science.gov (United States)

Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

Towards Multimodal Emotion Recognition in E-Learning Environments

Science.gov (United States)

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2016-01-01

This paper presents a framework (FILTWAM (Framework for Improving Learning Through Webcams And Microphones)) for real-time emotion recognition in e-learning by using webcams. FILTWAM offers timely and relevant feedback based upon learner's facial expressions and verbalizations. FILTWAM's facial expression software module has been developed and…

ESO's Hidden Treasures Brought to Light

Science.gov (United States)

2011-01-01

Adam Kiil. 19. NGC 2467 - number 2 by Josh Barrington. 20. Haffner 18 and 19 by Javier Fuentes. Igor Chekalin, winner of the trip to Paranal, says: "It was a great experience and pleasure to work with such amazing data. As an amateur astrophotographer, this was the most difficult processing and post-processing job I have ever done. My participation in the Hidden Treasures competition gave me a range of challenges, from installing new software to studying techniques and even operating systems that I did not know before." The success of the ESO's Hidden Treasures 2010 competition and the enthusiasm of the skilled participants made it easy to decide to run a follow-up to the competition. Stay tuned and check www.eso.org for news about ESO's Hidden Treasures 2011. More information ESO, the European Southern Observatory, is the foremost intergovernmental astronomy organisation in Europe and the world's most productive astronomical observatory. It is supported by 15 countries: Austria, Belgium, Brazil, the Czech Republic, Denmark, France, Finland, Germany, Italy, the Netherlands, Portugal, Spain, Sweden, Switzerland and the United Kingdom. ESO carries out an ambitious programme focused on the design, construction and operation of powerful ground-based observing facilities enabling astronomers to make important scientific discoveries. ESO also plays a leading role in promoting and organising cooperation in astronomical research. ESO operates three unique world-class observing sites in Chile: La Silla, Paranal and Chajnantor. At Paranal, ESO operates the Very Large Telescope, the world's most advanced visible-light astronomical observatory and VISTA, the world's largest survey telescope. ESO is the European partner of a revolutionary astronomical telescope ALMA, the largest astronomical project in existence. ESO is currently planning a 42-metre European Extremely Large optical/near-infrared Telescope, the E-ELT, which will become "the world's biggest eye on the sky".

On the LHC sensitivity for non-thermalised hidden sectors

Science.gov (United States)

Kahlhoefer, Felix

2018-04-01

We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.

Massive hidden photons as lukewarm dark matter

International Nuclear Information System (INIS)

Redondo, Javier; Postma, Marieke

2008-11-01

We study the possibility that a keV-MeV mass hidden photon (HP), i.e. a hidden sector U(1) gauge boson, accounts for the observed amount of dark matter. We focus on the case where the HP interacts with the standard model sector only through kinetic mixing with the photon. The relic abundance is computed including all relevant plasma effects into the photon's self-energy, which leads to a resonant yield almost independent of the HP mass. The HP can decay into three photons. Moreover, if light enough it can be copiously produced in stars. Including bounds from cosmic photon backgrounds and stellar evolution, we find that the hidden photon can only give a subdominant contribution to the dark matter. This negative conclusion may be avoided if another production mechanism besides kinetic mixing is operative. (orig.)

Massive hidden photons as lukewarm dark matter

Energy Technology Data Exchange (ETDEWEB)

Redondo, Javier [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Postma, Marieke [Nationaal Inst. voor Kernfysica en Hoge-Energiefysica (NIKHEF), Amsterdam (Netherlands)

2008-11-15

We study the possibility that a keV-MeV mass hidden photon (HP), i.e. a hidden sector U(1) gauge boson, accounts for the observed amount of dark matter. We focus on the case where the HP interacts with the standard model sector only through kinetic mixing with the photon. The relic abundance is computed including all relevant plasma effects into the photon's self-energy, which leads to a resonant yield almost independent of the HP mass. The HP can decay into three photons. Moreover, if light enough it can be copiously produced in stars. Including bounds from cosmic photon backgrounds and stellar evolution, we find that the hidden photon can only give a subdominant contribution to the dark matter. This negative conclusion may be avoided if another production mechanism besides kinetic mixing is operative. (orig.)

New limits on hidden photons from past electron beam dumps

International Nuclear Information System (INIS)

Andreas, Sarah; Niebuhr, Carsten; Ringwald, Andreas

2012-09-01

Hidden sectors with light extra U(1) gauge bosons, so called hidden photons, have recently attracted some attention because they are a common feature of physics beyond the Standard Model like string theory and SUSY and additionally are phenomenologically of great interest regarding recent astrophysical observations. The hidden photon is already constrained by various laboratory experiments and presently searched for in running as well as upcoming experiments. We summarize the current status of limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay that have so far not been considered. All our limits take into account the experimental acceptances obtained from Monte Carlo simulations.

New limits on hidden photons from past electron beam dumps

Energy Technology Data Exchange (ETDEWEB)

Andreas, Sarah; Niebuhr, Carsten; Ringwald, Andreas

2012-09-15

Hidden sectors with light extra U(1) gauge bosons, so called hidden photons, have recently attracted some attention because they are a common feature of physics beyond the Standard Model like string theory and SUSY and additionally are phenomenologically of great interest regarding recent astrophysical observations. The hidden photon is already constrained by various laboratory experiments and presently searched for in running as well as upcoming experiments. We summarize the current status of limits on hidden photons from past electron beam dump experiments including two new limits from such experiments at KEK and Orsay that have so far not been considered. All our limits take into account the experimental acceptances obtained from Monte Carlo simulations.

Artificial Intelligence Software for Assessing Postural Stability

Science.gov (United States)

Lieberman, Erez; Forth, Katharine; Paloski, William

2013-01-01

A software package reads and analyzes pressure distributions from sensors mounted under a person's feet. Pressure data from sensors mounted in shoes, or in a platform, can be used to provide a description of postural stability (assessing competence to deficiency) and enables the determination of the person's present activity (running, walking, squatting, falling). This package has three parts: a preprocessing algorithm for reading input from pressure sensors; a Hidden Markov Model (HMM), which is used to determine the person's present activity and level of sensing-motor competence; and a suite of graphical algorithms, which allows visual representation of the person's activity and vestibular function over time.

Invisible axion in the hidden sector of no-scale supergravity

International Nuclear Information System (INIS)

Sato, Hikaru

1987-01-01

We propose a new axion model which incorporates the U(1) PQ symmetry into a hidden sector, as well as an observable sector, of no-scale supergravity models. The axion is a spin-zero field in the hidden sector. The U(1) PQ symmetry is naturally embedded in the family symmetry of the no-scale models. Invisible axions live in the gravity hidden sector without conflict with the cosmological and astrophysical constraints. (orig.)

EBR-II [Experimental Breeder Reactor-II] system surveillance using pattern recognition software

International Nuclear Information System (INIS)

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

1986-02-01

The problem of most accurately determining the Experimental Breeder Reactor-II (EBR-II) reactor outlet temperature from currently available plant signals is investigated. Historically, the reactor outlet pipe was originally instrumented with 8 temperature sensors but, during 22 years of operation, all these instruments have failed except for one remaining thermocouple, and its output had recently become suspect. Using pattern recognition methods to compare values of 129 plant signals for similarities over a 7 month period spanning reconfiguration of the core and recalibration of many plant signals, it was determined that the remaining reactor outlet pipe thermocouple is still useful as an indicator of true mixed mean reactor outlet temperature. Application of this methodology to investigate one specific signal has automatically validated the vast majority of the 129 signals used for pattern recognition and also highlighted a few inconsistent signals for further investigation

Increased taxon sampling reveals thousands of hidden orthologs in flatworms

Science.gov (United States)

2017-01-01

Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424

Searching for hidden sector in multiparticle production at LHC

Directory of Open Access Journals (Sweden)

Miguel-Angel Sanchis-Lozano

2016-03-01

Full Text Available We study the impact of a hidden sector beyond the Standard Model, e.g. a Hidden Valley model, on factorial moments and cumulants of multiplicity distributions in multiparticle production with a special emphasis on the prospects for LHC results.

An introduction to hidden Markov models for biological sequences

DEFF Research Database (Denmark)

Krogh, Anders Stærmose

1998-01-01

A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding.......A non-matematical tutorial on hidden Markov models (HMMs) plus a description of one of the applications of HMMs: gene finding....

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.

The origin of the hidden supersymmetry

International Nuclear Information System (INIS)

Jakubsky, Vit; Nieto, Luis-Miguel; Plyushchay, Mikhail S.

2010-01-01

The hidden supersymmetry and related tri-supersymmetric structure of the free particle system, the Dirac delta potential problem and the Aharonov-Bohm effect (planar, bound state, and tubule models) are explained by a special nonlocal unitary transformation, which for the usual N=2 supercharges has a nature of Foldy-Wouthuysen transformation. We show that in general case, the bosonized supersymmetry of nonlocal, parity even systems emerges in the same construction, and explain the origin of the unusual N=2 supersymmetry of electron in three-dimensional parity even magnetic field. The observation extends to include the hidden superconformal symmetry.

A transition-constrained discrete hidden Markov model for automatic sleep staging

Directory of Open Access Journals (Sweden)

Pan Shing-Tai

2012-08-01

Full Text Available Abstract Background Approximately one-third of the human lifespan is spent sleeping. To diagnose sleep problems, all-night polysomnographic (PSG recordings including electroencephalograms (EEGs, electrooculograms (EOGs and electromyograms (EMGs, are usually acquired from the patient and scored by a well-trained expert according to Rechtschaffen & Kales (R&K rules. Visual sleep scoring is a time-consuming and subjective process. Therefore, the development of an automatic sleep scoring method is desirable. Method The EEG, EOG and EMG signals from twenty subjects were measured. In addition to selecting sleep characteristics based on the 1968 R&K rules, features utilized in other research were collected. Thirteen features were utilized including temporal and spectrum analyses of the EEG, EOG and EMG signals, and a total of 158 hours of sleep data were recorded. Ten subjects were used to train the Discrete Hidden Markov Model (DHMM, and the remaining ten were tested by the trained DHMM for recognition. Furthermore, the 2-fold cross validation was performed during this experiment. Results Overall agreement between the expert and the results presented is 85.29%. With the exception of S1, the sensitivities of each stage were more than 81%. The most accurate stage was SWS (94.9%, and the least-accurately classified stage was S1 ( Conclusion The results of the experiments demonstrate that the proposed method significantly enhances the recognition rate when compared with prior studies.

Naturally light hidden photons in LARGE volume string compactifications

International Nuclear Information System (INIS)

Goodsell, M.; Jaeckel, J.; Redondo, J.; Ringwald, A.

2009-09-01

Extra ''hidden'' U(1) gauge factors are a generic feature of string theory that is of particular phenomenological interest. They can kinetically mix with the Standard Model photon and are thereby accessible to a wide variety of astrophysical and cosmological observations and laboratory experiments. In this paper we investigate the masses and the kinetic mixing of hidden U(1)s in LARGE volume compactifications of string theory. We find that in these scenarios the hidden photons can be naturally light and that their kinetic mixing with the ordinary electromagnetic photon can be of a size interesting for near future experiments and observations. (orig.)

Hidden photon dark matter search with large metallic mirror

International Nuclear Information System (INIS)

Doebrich, Babette; Lindner, Axel; Daumiller, Kai; Engel, Ralph; Roth, Markus; Kowalski, Marek

2014-10-01

If Dark Matter is composed of hidden-sector photons that kinetically mix with photons of the visible sector, then Dark Matter has a tiny oscillating electric field component. Its presence would lead to a small amount of visible radiation being emitted from a conducting surface, with the photon frequency given approximately by the mass of the hidden photon. Here, we report on experimental efforts that have started recently to search for such hidden photon Dark Matter in the (sub-)eV regime with a prototype mirror for the Auger fluorescence detector at the Karlsruhe Institute for Technology.

Modeling Strategic Use of Human Computer Interfaces with Novel Hidden Markov Models

Directory of Open Access Journals (Sweden)

Laura Jane Mariano

2015-07-01

Full Text Available Immersive software tools are virtual environments designed to give their users an augmented view of real-world data and ways of manipulating that data. As virtual environments, every action users make while interacting with these tools can be carefully logged, as can the state of the software and the information it presents to the user, giving these actions context. This data provides a high-resolution lens through which dynamic cognitive and behavioral processes can be viewed. In this report, we describe new methods for the analysis and interpretation of such data, utilizing a novel implementation of the Beta Process Hidden Markov Model (BP-HMM for analysis of software activity logs. We further report the results of a preliminary study designed to establish the validity of our modeling approach. A group of 20 participants were asked to play a simple computer game, instrumented to log every interaction with the interface. Participants had no previous experience with the game’s functionality or rules, so the activity logs collected during their naïve interactions capture patterns of exploratory behavior and skill acquisition as they attempted to learn the rules of the game. Pre- and post-task questionnaires probed for self-reported styles of problem solving, as well as task engagement, difficulty, and workload. We jointly modeled the activity log sequences collected from all participants using the BP-HMM approach, identifying a global library of activity patterns representative of the collective behavior of all the participants. Analyses show systematic relationships between both pre- and post-task questionnaires, self-reported approaches to analytic problem solving, and metrics extracted from the BP-HMM decomposition. Overall, we find that this novel approach to decomposing unstructured behavioral data within software environments provides a sensible means for understanding how users learn to integrate software functionality for strategic

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

Directory of Open Access Journals (Sweden)

Neng-Sheng Pai

2014-01-01

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

A coverage and slicing dependencies analysis for seeking software security defects.

Science.gov (United States)

He, Hui; Zhang, Dongyan; Liu, Min; Zhang, Weizhe; Gao, Dongmin

2014-01-01

Software security defects have a serious impact on the software quality and reliability. It is a major hidden danger for the operation of a system that a software system has some security flaws. When the scale of the software increases, its vulnerability has becoming much more difficult to find out. Once these vulnerabilities are exploited, it may lead to great loss. In this situation, the concept of Software Assurance is carried out by some experts. And the automated fault localization technique is a part of the research of Software Assurance. Currently, automated fault localization method includes coverage based fault localization (CBFL) and program slicing. Both of the methods have their own location advantages and defects. In this paper, we have put forward a new method, named Reverse Data Dependence Analysis Model, which integrates the two methods by analyzing the program structure. On this basis, we finally proposed a new automated fault localization method. This method not only is automation lossless but also changes the basic location unit into single sentence, which makes the location effect more accurate. Through several experiments, we proved that our method is more effective. Furthermore, we analyzed the effectiveness among these existing methods and different faults.

Supersymmetry, p-brane duality, and hidden spacetime dimensions

International Nuclear Information System (INIS)

Bars, I.

1996-01-01

A global superalgebra with 32 supercharges and all possible central extensions is studied in order to extract some general properties of duality and hidden dimensions in a theory that treats p-branes democratically. The maximal number of dimensions is 12, with signature (10,2), containing one space and one time dimension that are hidden from the point of view of perturbative ten-dimensional string theory or its compactifications. When the theory is compactified on R d-1,1 circle-times T c+1,1 with d+c+2=12, there are isometry groups that relate to the hidden dimensions as well as to duality. Their combined intersecting classification schemes provide some properties of nonperturbative states and their couplings. copyright 1996 The American Physical Society

Software refactoring at the package level using clustering techniques

KAUST Repository

Alkhalid, A.

2011-01-01

Enhancing, modifying or adapting the software to new requirements increases the internal software complexity. Software with high level of internal complexity is difficult to maintain. Software refactoring reduces software complexity and hence decreases the maintenance effort. However, software refactoring becomes quite challenging task as the software evolves. The authors use clustering as a pattern recognition technique to assist in software refactoring activities at the package level. The approach presents a computer aided support for identifying ill-structured packages and provides suggestions for software designer to balance between intra-package cohesion and inter-package coupling. A comparative study is conducted applying three different clustering techniques on different software systems. In addition, the application of refactoring at the package level using an adaptive k-nearest neighbour (A-KNN) algorithm is introduced. The authors compared A-KNN technique with the other clustering techniques (viz. single linkage algorithm, complete linkage algorithm and weighted pair-group method using arithmetic averages). The new technique shows competitive performance with lower computational complexity. © 2011 The Institution of Engineering and Technology.

A single hidden layer feedforward network with only one neuron in the hidden layer can approximate any univariate function

OpenAIRE

Guliyev , Namig; Ismailov , Vugar

2016-01-01

The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted. In this paper, we consider constructive approximation on any finite interval of $\\mathbb{R}$ by neural networks with only one neuron in the hid...

Discovering hidden sectors with monophoton Z' searches

International Nuclear Information System (INIS)

Gershtein, Yuri; Petriello, Frank; Quackenbush, Seth; Zurek, Kathryn M.

2008-01-01

In many theories of physics beyond the standard model, from extra dimensions to Hidden Valleys and models of dark matter, Z ' bosons mediate between standard model particles and hidden sector states. We study the feasibility of observing such hidden states through an invisibly decaying Z ' at the LHC. We focus on the process pp→γZ ' →γXX † , where X is any neutral, (quasi-) stable particle, whether a standard model neutrino or a new state. This complements a previous study using pp→ZZ ' →l + l - XX † . Only the Z ' mass and two effective charges are needed to describe this process. If the Z ' decays invisibly only to standard model neutrinos, then these charges are predicted by observation of the Z ' through the Drell-Yan process, allowing discrimination between Z ' decays to standard model ν's and invisible decays to new states. We carefully discuss all backgrounds and systematic errors that affect this search. We find that hidden sector decays of a 1 TeV Z ' can be observed at 5σ significance with 50 fb -1 at the LHC. Observation of a 1.5 TeV state requires super-LHC statistics of 1 ab -1 . Control of the systematic errors, in particular, the parton distribution function uncertainty of the dominant Zγ background, is crucial to maximize the LHC search reach.

Child Abuse: The Hidden Bruises

Science.gov (United States)

... for Families - Vietnamese Spanish Facts for Families Guide Child Abuse - The Hidden Bruises No. 5; Updated November 2014 The statistics on physical child abuse are alarming. It is estimated hundreds of thousands ...

Learning and inference in a nonequilibrium Ising model with hidden nodes.

Science.gov (United States)

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

Morphing Images: A Potential Tool for Teaching Word Recognition to Children with Severe Learning Difficulties

Science.gov (United States)

Sheehy, Kieron

2005-01-01

Children with severe learning difficulties who fail to begin word recognition can learn to recognise pictures and symbols relatively easily. However, finding an effective means of using pictures to teach word recognition has proved problematic. This research explores the use of morphing software to support the transition from picture to word…

Analysing the hidden curriculum: use of a cultural web.

Science.gov (United States)

Mossop, Liz; Dennick, Reg; Hammond, Richard; Robbé, Iain

2013-02-01

Major influences on learning about medical professionalism come from the hidden curriculum. These influences can contribute positively or negatively towards the professional enculturation of clinical students. The fact that there is no validated method for identifying the components of the hidden curriculum poses problems for educators considering professionalism. The aim of this study was to analyse whether a cultural web, adapted from a business context, might assist in the identification of elements of the hidden curriculum at a UK veterinary school. A qualitative approach was used. Seven focus groups consisting of three staff groups and four student groups were organised. Questioning was framed using the cultural web, which is a model used by business owners to assess their environment and consider how it affects their employees and customers. The focus group discussions were recorded, transcribed and analysed thematically using a combination of a priori and emergent themes. The cultural web identified elements of the hidden curriculum for both students and staff. These included: core assumptions; routines; rituals; control systems; organisational factors; power structures, and symbols. Discussions occurred about how and where these issues may affect students' professional identity development. The cultural web framework functioned well to help participants identify elements of the hidden curriculum. These aspects aligned broadly with previously described factors such as role models and institutional slang. The influence of these issues on a student's development of a professional identity requires discussion amongst faculty staff, and could be used to develop learning opportunities for students. The framework is promising for the analysis of the hidden curriculum and could be developed as an instrument for implementation in other clinical teaching environments. © Blackwell Publishing Ltd 2013.

Compression of a Deep Competitive Network Based on Mutual Information for Underwater Acoustic Targets Recognition

Directory of Open Access Journals (Sweden)

Sheng Shen

2018-04-01

Full Text Available The accuracy of underwater acoustic targets recognition via limited ship radiated noise can be improved by a deep neural network trained with a large number of unlabeled samples. However, redundant features learned by deep neural network have negative effects on recognition accuracy and efficiency. A compressed deep competitive network is proposed to learn and extract features from ship radiated noise. The core idea of the algorithm includes: (1 Competitive learning: By integrating competitive learning into the restricted Boltzmann machine learning algorithm, the hidden units could share the weights in each predefined group; (2 Network pruning: The pruning based on mutual information is deployed to remove the redundant parameters and further compress the network. Experiments based on real ship radiated noise show that the network can increase recognition accuracy with fewer informative features. The compressed deep competitive network can achieve a classification accuracy of 89.1 % , which is 5.3 % higher than deep competitive network and 13.1 % higher than the state-of-the-art signal processing feature extraction methods.

Automatic Human Facial Expression Recognition Based on Integrated Classifier From Monocular Video with Uncalibrated Camera

Directory of Open Access Journals (Sweden)

Yu Tao

2017-01-01

Full Text Available An automatic recognition framework for human facial expressions from a monocular video with an uncalibrated camera is proposed. The expression characteristics are first acquired from a kind of deformable template, similar to a facial muscle distribution. After associated regularization, the time sequences from the trait changes in space-time under complete expressional production are then arranged line by line in a matrix. Next, the matrix dimensionality is reduced by a method of manifold learning of neighborhood-preserving embedding. Finally, the refined matrix containing the expression trait information is recognized by a classifier that integrates the hidden conditional random field (HCRF and support vector machine (SVM. In an experiment using the Cohn–Kanade database, the proposed method showed a comparatively higher recognition rate than the individual HCRF or SVM methods in direct recognition from two-dimensional human face traits. Moreover, the proposed method was shown to be more robust than the typical Kotsia method because the former contains more structural characteristics of the data to be classified in space-time

Anticipating hidden text salting in emails (extended abstract)

OpenAIRE

Lioma, Christina; Moens, Marie-Francine; Gomez, Juan Carlos; De Beer, Jan; Bergholz, Andre; Paass, Gerhard; Horkan, Patrick

2008-01-01

Salting is the intentional addition or distortion of content, aimed to evade automatic filtering. Salting is usually found in spam emails. Salting can also be hidden in phishing emails, which aim to steal personal information from users. We present a novel method that detects hidden salting tricks as visual anomalies in text. We solely use these salting tricks to successfully classify emails as phishing (F-measure >90%).

Complicated basins and the phenomenon of amplitude death in coupled hidden attractors

Energy Technology Data Exchange (ETDEWEB)

Chaudhuri, Ushnish [Department of Physics, Sri Venkateswara College, University of Delhi, New Delhi 110021 (India); Department of Physics, National University of Singapore, Singapore 117551 (Singapore); Prasad, Awadhesh, E-mail: awadhesh@physics.du.ac.in [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India)

2014-02-07

Understanding hidden attractors, whose basins of attraction do not contain the neighborhood of equilibrium of the system, are important in many physical applications. We observe riddled-like complicated basins of coexisting hidden attractors both in coupled and uncoupled systems. Amplitude death is observed in coupled hidden attractors with no fixed point using nonlinear interaction. A new route to amplitude death is observed in time-delay coupled hidden attractors. Numerical results are presented for systems with no or one stable fixed point. The applications are highlighted.

Automated Facial Coding Software Outperforms People in Recognizing Neutral Faces as Neutral from Standardized Datasets

Directory of Open Access Journals (Sweden)

Peter eLewinski

2015-09-01

Full Text Available Little is known about people’s accuracy of recognizing neutral faces as neutral. In this paper, I demonstrate the importance of knowing how well people recognize neutral faces. I contrasted human recognition scores of 100 typical, neutral front-up facial images with scores of an arguably objective judge – automated facial coding (AFC software. I hypothesized that the software would outperform humans in recognizing neutral faces because of the inherently objective nature of computer algorithms. Results confirmed this hypothesis. I provided the first-ever evidence that computer software (90% was more accurate in recognizing neutral faces than people were (59%. I posited two theoretical mechanisms, i.e. smile-as-a-baseline and false recognition of emotion, as possible explanations for my findings.

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.

Flight Software Math Library

Science.gov (United States)

McComas, David

2013-01-01

The flight software (FSW) math library is a collection of reusable math components that provides typical math utilities required by spacecraft flight software. These utilities are intended to increase flight software quality reusability and maintainability by providing a set of consistent, well-documented, and tested math utilities. This library only has dependencies on ANSI C, so it is easily ported. Prior to this library, each mission typically created its own math utilities using ideas/code from previous missions. Part of the reason for this is that math libraries can be written with different strategies in areas like error handling, parameters orders, naming conventions, etc. Changing the utilities for each mission introduces risks and costs. The obvious risks and costs are that the utilities must be coded and revalidated. The hidden risks and costs arise in miscommunication between engineers. These utilities must be understood by both the flight software engineers and other subsystem engineers (primarily guidance navigation and control). The FSW math library is part of a larger goal to produce a library of reusable Guidance Navigation and Control (GN&C) FSW components. A GN&C FSW library cannot be created unless a standardized math basis is created. This library solves the standardization problem by defining a common feature set and establishing policies for the library s design. This allows the libraries to be maintained with the same strategy used in its initial development, which supports a library of reusable GN&C FSW components. The FSW math library is written for an embedded software environment in C. This places restrictions on the language features that can be used by the library. Another advantage of the FSW math library is that it can be used in the FSW as well as other environments like the GN&C analyst s simulators. This helps communication between the teams because they can use the same utilities with the same feature set and syntax.

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.

Gauge mediation scenario with hidden sector renormalization in MSSM

International Nuclear Information System (INIS)

Arai, Masato; Kawai, Shinsuke; Okada, Nobuchika

2010-01-01

We study the hidden sector effects on the mass renormalization of a simplest gauge-mediated supersymmetry breaking scenario. We point out that possible hidden sector contributions render the soft scalar masses smaller, resulting in drastically different sparticle mass spectrum at low energy. In particular, in the 5+5 minimal gauge-mediated supersymmetry breaking with high messenger scale (that is favored by the gravitino cold dark matter scenario), we show that a stau can be the next lightest superparticle for moderate values of hidden sector self-coupling. This provides a very simple theoretical model of long-lived charged next lightest superparticles, which imply distinctive signals in ongoing and upcoming collider experiments.

Gauge mediation scenario with hidden sector renormalization in MSSM

Science.gov (United States)

Arai, Masato; Kawai, Shinsuke; Okada, Nobuchika

2010-02-01

We study the hidden sector effects on the mass renormalization of a simplest gauge-mediated supersymmetry breaking scenario. We point out that possible hidden sector contributions render the soft scalar masses smaller, resulting in drastically different sparticle mass spectrum at low energy. In particular, in the 5+5¯ minimal gauge-mediated supersymmetry breaking with high messenger scale (that is favored by the gravitino cold dark matter scenario), we show that a stau can be the next lightest superparticle for moderate values of hidden sector self-coupling. This provides a very simple theoretical model of long-lived charged next lightest superparticles, which imply distinctive signals in ongoing and upcoming collider experiments.

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.

Software compensation in Particle Flow reconstruction

CERN Document Server

Lan Tran, Huong; Sefkow, Felix; Green, Steven; Marshall, John; Thomson, Mark; Simon, Frank

2017-01-01

The Particle Flow approach to calorimetry requires highly granular calorimeters and sophisticated software algorithms in order to reconstruct and identify individual particles in complex event topologies. The high spatial granularity, together with analog energy information, can be further exploited in software compensation. In this approach, the local energy density is used to discriminate electromagnetic and purely hadronic sub-showers within hadron showers in the detector to improve the energy resolution for single particles by correcting for the intrinsic non-compensation of the calorimeter system. This improvement in the single particle energy resolution also results in a better overall jet energy resolution by improving the energy measurement of identified neutral hadrons and improvements in the pattern recognition stage by a more accurate matching of calorimeter energies to tracker measurements. This paper describes the software compensation technique and its implementation in Particle Flow reconstruct...

Quantum mechanics and hidden superconformal symmetry

Science.gov (United States)

Bonezzi, R.; Corradini, O.; Latini, E.; Waldron, A.

2017-12-01

Solvability of the ubiquitous quantum harmonic oscillator relies on a spectrum generating osp (1 |2 ) superconformal symmetry. We study the problem of constructing all quantum mechanical models with a hidden osp (1 |2 ) symmetry on a given space of states. This problem stems from interacting higher spin models coupled to gravity. In one dimension, we show that the solution to this problem is the Vasiliev-Plyushchay family of quantum mechanical models with hidden superconformal symmetry obtained by viewing the harmonic oscillator as a one dimensional Dirac system, so that Grassmann parity equals wave function parity. These models—both oscillator and particlelike—realize all possible unitary irreducible representations of osp (1 |2 ).

Hidden simplicity of gauge theory amplitudes

Energy Technology Data Exchange (ETDEWEB)

Drummond, J M, E-mail: drummond@lapp.in2p3.f [LAPTH, Universite de Savoie, CNRS, B.P. 110, F-74941 Annecy-le-Vieux, Cedex (France)

2010-11-07

These notes were given as lectures at the CERN Winter School on Supergravity, Strings and Gauge Theory 2010. We describe the structure of scattering amplitudes in gauge theories, focussing on the maximally supersymmetric theory to highlight the hidden symmetries which appear. Using the Britto, Cachzo, Feng and Witten (BCFW) recursion relations we solve the tree-level S-matrix in N=4 super Yang-Mills theory and describe how it produces a sum of invariants of a large symmetry algebra. We review amplitudes in the planar theory beyond tree level, describing the connection between amplitudes and Wilson loops, and discuss the implications of the hidden symmetries.

Automated recognition system for power quality disturbances

Science.gov (United States)

Abdelgalil, Tarek

The application of deregulation policies in electric power systems has resulted in the necessity to quantify the quality of electric power. This fact highlights the need for a new monitoring strategy which is capable of tracking, detecting, classifying power quality disturbances, and then identifying the source of the disturbance. The objective of this work is to design an efficient and reliable power quality monitoring strategy that uses the advances in signal processing and pattern recognition to overcome the deficiencies that exist in power quality monitoring devices. The purposed monitoring strategy has two stages. The first stage is to detect, track, and classify any power quality violation by the use of on-line measurements. In the second stage, the source of the classified power quality disturbance must be identified. In the first stage, an adaptive linear combiner is used to detect power quality disturbances. Then, the Teager Energy Operator and Hilbert Transform are utilized for power quality event tracking. After the Fourier, Wavelet, and Walsh Transforms are employed for the feature extraction, two approaches are then exploited to classify the different power quality disturbances. The first approach depends on comparing the disturbance to be classified with a stored set of signatures for different power quality disturbances. The comparison is developed by using Hidden Markov Models and Dynamic Time Warping. The second approach depends on employing an inductive inference to generate the classification rules directly from the data. In the second stage of the new monitoring strategy, only the problem of identifying the location of the switched capacitor which initiates the transients is investigated. The Total Least Square-Estimation of Signal Parameters via Rotational Invariance Technique is adopted to estimate the amplitudes and frequencies of the various modes contained in the voltage signal measured at the facility entrance. After extracting the

Update on hidden sectors with dark forces and dark matter

Energy Technology Data Exchange (ETDEWEB)

Andreas, Sarah

2012-11-15

Recently there has been much interest in hidden sectors, especially in the context of dark matter and ''dark forces'', since they are a common feature of beyond standard model scenarios like string theory and SUSY and additionally exhibit interesting phenomenological aspects. Various laboratory experiments place limits on the so-called hidden photon and continuously further probe and constrain the parameter space; an updated overview is presented here. Furthermore, for several hidden sector models with light dark matter we study the viability with respect to the relic abundance and direct detection experiments.

Dietary phytate, zinc and hidden zinc deficiency.

Science.gov (United States)

Sandstead, Harold H; Freeland-Graves, Jeanne H

2014-10-01

Epidemiological data suggest at least one in five humans are at risk of zinc deficiency. This is in large part because the phytate in cereals and legumes has not been removed during food preparation. Phytate, a potent indigestible ligand for zinc prevents it's absorption. Without knowledge of the frequency of consumption of foods rich in phytate, and foods rich in bioavailable zinc, the recognition of zinc deficiency early in the illness may be difficult. Plasma zinc is insensitive to early zinc deficiency. Serum ferritin concentration≤20μg/L is a potential indirect biomarker. Early effects of zinc deficiency are chemical, functional and may be "hidden". The clinical problem is illustrated by 2 studies that involved US Mexican-American children, and US premenopausal women. The children were consuming home diets that included traditional foods high in phytate. The premenopausal women were not eating red meat on a regular basis, and their consumption of phytate was mainly from bran breakfast cereals. In both studies the presence of zinc deficiency was proven by functional responses to controlled zinc treatment. In the children lean-mass, reasoning, and immunity were significantly affected. In the women memory, reasoning, and eye-hand coordination were significantly affected. A screening self-administered food frequency questionnaire for office might help caregiver's identify patients at risk of zinc deficiency. Copyright © 2014 Elsevier GmbH. All rights reserved.

Searching for hidden sectors in multiparticle production at the LHC

CERN Document Server

Sanchis-Lozano, Miguel-Angel; Moreno-Picot, Salvador

2016-01-01

We study the impact of a hidden sector beyond the Standard Model, e.g. a Hidden Valley model, on factorial moments and cumulants of multiplicity distributions in multiparticle production with a special emphasis on the prospects for LHC results.

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

Science.gov (United States)

Marsden, Jim

1993-01-01

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

Carotta: Revealing Hidden Confounder Markers in Metabolic Breath Profiles

Directory of Open Access Journals (Sweden)

Anne-Christin Hauschild

2015-06-01

Full Text Available Computational breath analysis is a growing research area aiming at identifying volatile organic compounds (VOCs in human breath to assist medical diagnostics of the next generation. While inexpensive and non-invasive bioanalytical technologies for metabolite detection in exhaled air and bacterial/fungal vapor exist and the first studies on the power of supervised machine learning methods for profiling of the resulting data were conducted, we lack methods to extract hidden data features emerging from confounding factors. Here, we present Carotta, a new cluster analysis framework dedicated to uncovering such hidden substructures by sophisticated unsupervised statistical learning methods. We study the power of transitivity clustering and hierarchical clustering to identify groups of VOCs with similar expression behavior over most patient breath samples and/or groups of patients with a similar VOC intensity pattern. This enables the discovery of dependencies between metabolites. On the one hand, this allows us to eliminate the effect of potential confounding factors hindering disease classification, such as smoking. On the other hand, we may also identify VOCs associated with disease subtypes or concomitant diseases. Carotta is an open source software with an intuitive graphical user interface promoting data handling, analysis and visualization. The back-end is designed to be modular, allowing for easy extensions with plugins in the future, such as new clustering methods and statistics. It does not require much prior knowledge or technical skills to operate. We demonstrate its power and applicability by means of one artificial dataset. We also apply Carotta exemplarily to a real-world example dataset on chronic obstructive pulmonary disease (COPD. While the artificial data are utilized as a proof of concept, we will demonstrate how Carotta finds candidate markers in our real dataset associated with confounders rather than the primary disease (COPD

Detection, information fusion, and temporal processing for intelligence in recognition

Energy Technology Data Exchange (ETDEWEB)

Casasent, D. [Carnegie Mellon Univ., Pittsburgh, PA (United States)

1996-12-31

The use of intelligence in vision recognition uses many different techniques or tools. This presentation discusses several of these techniques for recognition. The recognition process is generally separated into several steps or stages when implemented in hardware, e.g. detection, segmentation and enhancement, and recognition. Several new distortion-invariant filters, biologically-inspired Gabor wavelet filter techniques, and morphological operations that have been found very useful for detection and clutter rejection are discussed. These are all shift-invariant operations that allow multiple object regions of interest in a scene to be located in parallel. We also discuss new algorithm fusion concepts by which the results from different detection algorithms are combined to reduce detection false alarms; these fusion methods utilize hierarchical processing and fuzzy logic concepts. We have found this to be most necessary, since no single detection algorithm is best for all cases. For the final recognition stage, we describe a new method of representing all distorted versions of different classes of objects and determining the object class and pose that most closely matches that of a given input. Besides being efficient in terms of storage and on-line computations required, it overcomes many of the problems that other classifiers have in terms of the required training set size, poor generalization with many hidden layer neurons, etc. It is also attractive in its ability to reject input regions as clutter (non-objects) and to learn new object descriptions. We also discuss its use in processing a temporal sequence of input images of the contents of each local region of interest. We note how this leads to robust results in which estimation efforts in individual frames can be overcome. This seems very practical, since in many scenarios a decision need not be made after only one frame of data, since subsequent frames of data enter immediately in sequence.

Secret Codes: The Hidden Curriculum of Semantic Web Technologies

Science.gov (United States)

Edwards, Richard; Carmichael, Patrick

2012-01-01

There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate…

State-space dimensionality in short-memory hidden-variable theories

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

Recently we have presented a hidden-variable model of measurements for a qubit where the hidden-variable state-space dimension is one-half the quantum-state manifold dimension. The absence of a short memory (Markov) dynamics is the price paid for this dimensional reduction. The conflict between having the Markov property and achieving the dimensional reduction was proved by Montina [A. Montina, Phys. Rev. A 77, 022104 (2008)] using an additional hypothesis of trajectory relaxation. Here we analyze in more detail this hypothesis introducing the concept of invertible process and report a proof that makes clearer the role played by the topology of the hidden-variable space. This is accomplished by requiring suitable properties of regularity of the conditional probability governing the dynamics. In the case of minimal dimension the set of continuous hidden variables is identified with an object living an N-dimensional Hilbert space whose dynamics is described by the Schroedinger equation. A method for generating the economical non-Markovian model for the qubit is also presented.

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

Science.gov (United States)

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Peptide Pattern Recognition for high-throughput protein sequence analysis and clustering

DEFF Research Database (Denmark)

Busk, Peter Kamp

2017-01-01

Large collections of protein sequences with divergent sequences are tedious to analyze for understanding their phylogenetic or structure-function relation. Peptide Pattern Recognition is an algorithm that was developed to facilitate this task but the previous version does only allow a limited...... number of sequences as input. I implemented Peptide Pattern Recognition as a multithread software designed to handle large numbers of sequences and perform analysis in a reasonable time frame. Benchmarking showed that the new implementation of Peptide Pattern Recognition is twenty times faster than...... the previous implementation on a small protein collection with 673 MAP kinase sequences. In addition, the new implementation could analyze a large protein collection with 48,570 Glycosyl Transferase family 20 sequences without reaching its upper limit on a desktop computer. Peptide Pattern Recognition...

Frequency and analysis of non-clinical errors made in radiology reports using the National Integrated Medical Imaging System voice recognition dictation software.

Science.gov (United States)

Motyer, R E; Liddy, S; Torreggiani, W C; Buckley, O

2016-11-01

Voice recognition (VR) dictation of radiology reports has become the mainstay of reporting in many institutions worldwide. Despite benefit, such software is not without limitations, and transcription errors have been widely reported. Evaluate the frequency and nature of non-clinical transcription error using VR dictation software. Retrospective audit of 378 finalised radiology reports. Errors were counted and categorised by significance, error type and sub-type. Data regarding imaging modality, report length and dictation time was collected. 67 (17.72 %) reports contained ≥1 errors, with 7 (1.85 %) containing 'significant' and 9 (2.38 %) containing 'very significant' errors. A total of 90 errors were identified from the 378 reports analysed, with 74 (82.22 %) classified as 'insignificant', 7 (7.78 %) as 'significant', 9 (10 %) as 'very significant'. 68 (75.56 %) errors were 'spelling and grammar', 20 (22.22 %) 'missense' and 2 (2.22 %) 'nonsense'. 'Punctuation' error was most common sub-type, accounting for 27 errors (30 %). Complex imaging modalities had higher error rates per report and sentence. Computed tomography contained 0.040 errors per sentence compared to plain film with 0.030. Longer reports had a higher error rate, with reports >25 sentences containing an average of 1.23 errors per report compared to 0-5 sentences containing 0.09. These findings highlight the limitations of VR dictation software. While most error was deemed insignificant, there were occurrences of error with potential to alter report interpretation and patient management. Longer reports and reports on more complex imaging had higher error rates and this should be taken into account by the reporting radiologist.

Dopamine reward prediction errors reflect hidden state inference across time

Science.gov (United States)

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

Higher-dimensional black holes: hidden symmetries and separation of variables

International Nuclear Information System (INIS)

Frolov, Valeri P; Kubiznak, David

2008-01-01

In this paper, we discuss hidden symmetries in rotating black hole spacetimes. We start with an extended introduction which mainly summarizes results on hidden symmetries in four dimensions and introduces Killing and Killing-Yano tensors, objects responsible for hidden symmetries. We also demonstrate how starting with a principal CKY tensor (that is a closed non-degenerate conformal Killing-Yano 2-form) in 4D flat spacetime one can 'generate' the 4D Kerr-NUT-(A)dS solution and its hidden symmetries. After this we consider higher-dimensional Kerr-NUT-(A)dS metrics and demonstrate that they possess a principal CKY tensor which allows one to generate the whole tower of Killing-Yano and Killing tensors. These symmetries imply complete integrability of geodesic equations and complete separation of variables for the Hamilton-Jacobi, Klein-Gordon and Dirac equations in the general Kerr-NUT-(A)dS metrics

Syllabic Length Effect in Visual Word Recognition

Directory of Open Access Journals (Sweden)

Roya Ranjbar Mohammadi

2014-07-01

Full Text Available Studies on visual word recognition have resulted in different and sometimes contradictory proposals as Multi-Trace Memory Model (MTM, Dual-Route Cascaded Model (DRC, and Parallel Distribution Processing Model (PDP. The role of the number of syllables in word recognition was examined by the use of five groups of English words and non-words. The reaction time of the participants to these words was measured using reaction time measuring software. The results indicated that there was syllabic effect on recognition of both high and low frequency words. The pattern was incremental in terms of syllable number. This pattern prevailed in high and low frequency words and non-words except in one syllable words. In general, the results are in line with the PDP model which claims that a single processing mechanism is used in both words and non-words recognition. In other words, the findings suggest that lexical items are mainly processed via a lexical route.  A pedagogical implication of the findings would be that reading in English as a foreign language involves analytical processing of the syllable of the words.

Robotics control using isolated word recognition of voice input

Science.gov (United States)

Weiner, J. M.

1977-01-01

A speech input/output system is presented that can be used to communicate with a task oriented system. Human speech commands and synthesized voice output extend conventional information exchange capabilities between man and machine by utilizing audio input and output channels. The speech input facility is comprised of a hardware feature extractor and a microprocessor implemented isolated word or phrase recognition system. The recognizer offers a medium sized (100 commands), syntactically constrained vocabulary, and exhibits close to real time performance. The major portion of the recognition processing required is accomplished through software, minimizing the complexity of the hardware feature extractor.

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

Science.gov (United States)

Carr, Oliver

2002-10-01

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

Software compensation in particle flow reconstruction

Energy Technology Data Exchange (ETDEWEB)

Tran, Huong Lan; Krueger, Katja; Sefkow, Felix [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Green, Steven; Marshall, John; Thomson, Mark [Cavendish Laboratory, Cambridge (United Kingdom); Simon, Frank [Max-Planck-Institut fuer Physik, Muenchen (Germany)

2017-10-15

The particle flow approach to calorimetry benefits from highly granular calorimeters and sophisticated software algorithms in order to reconstruct and identify individual particles in complex event topologies. The high spatial granularity, together with analogue energy information, can be further exploited in software compensation. In this approach, the local energy density is used to discriminate electromagnetic and purely hadronic sub-showers within hadron showers in the detector to improve the energy resolution for single particles by correcting for the intrinsic non-compensation of the calorimeter system. This improvement in the single particle energy resolution also results in a better overall jet energy resolution by improving the energy measurement of identified neutral hadrons and improvements in the pattern recognition stage by a more accurate matching of calorimeter energies to tracker measurements. This paper describes the software compensation technique and its implementation in particle flow reconstruction with the Pandora Particle Flow Algorithm (PandoraPFA). The impact of software compensation on the choice of optimal transverse granularity for the analogue hadronic calorimeter option of the International Large Detector (ILD) concept is also discussed.

Software compensation in particle flow reconstruction

Energy Technology Data Exchange (ETDEWEB)

Tran, Huong Lan; Krueger, Katja; Sefkow, Felix [Deutsches Elektronen-Synchrotron DESY, Hamburg (Germany); Green, Steven; Marshall, John; Thomson, Mark [Cavendish Laboratory, Cambridge (United Kingdom); Simon, Frank [Max-Planck-Institut fuer Physik, Muenchen (Germany)

2017-10-15

The particle flow approach to calorimetry benefits from highly granular calorimeters and sophisticated software algorithms in order to reconstruct and identify individual particles in complex event topologies. The high spatial granularity, together with analogue energy information, can be further exploited in software compensation. In this approach, the local energy density is used to discriminate electromagnetic and purely hadronic sub-showers within hadron showers in the detector to improve the energy resolution for single particles by correcting for the intrinsic non-compensation of the calorimeter system. This improvement in the single particle energy resolution also results in a better overall jet energy resolution by improving the energy measurement of identified neutral hadrons and improvements in the pattern recognition stage by a more accurate matching of calorimeter energies to tracker measurements. This paper describes the software compensation technique and its implementation in particle flow reconstruction with the Pandora Particle Flow Algorithm (PandoraPFA). The impact of software compensation on the choice of optimal transverse granularity for the analogue hadronic calorimeter option of the International Large Detector (ILD) concept is also discussed. (orig.)

Software compensation in particle flow reconstruction

International Nuclear Information System (INIS)

Tran, Huong Lan; Krueger, Katja; Sefkow, Felix; Green, Steven; Marshall, John; Thomson, Mark; Simon, Frank

2017-10-01

The particle flow approach to calorimetry benefits from highly granular calorimeters and sophisticated software algorithms in order to reconstruct and identify individual particles in complex event topologies. The high spatial granularity, together with analogue energy information, can be further exploited in software compensation. In this approach, the local energy density is used to discriminate electromagnetic and purely hadronic sub-showers within hadron showers in the detector to improve the energy resolution for single particles by correcting for the intrinsic non-compensation of the calorimeter system. This improvement in the single particle energy resolution also results in a better overall jet energy resolution by improving the energy measurement of identified neutral hadrons and improvements in the pattern recognition stage by a more accurate matching of calorimeter energies to tracker measurements. This paper describes the software compensation technique and its implementation in particle flow reconstruction with the Pandora Particle Flow Algorithm (PandoraPFA). The impact of software compensation on the choice of optimal transverse granularity for the analogue hadronic calorimeter option of the International Large Detector (ILD) concept is also discussed.

Adaptive hidden Markov model with anomaly States for price manipulation detection.

Science.gov (United States)

Cao, Yi; Li, Yuhua; Coleman, Sonya; Belatreche, Ammar; McGinnity, Thomas Martin

2015-02-01

Price manipulation refers to the activities of those traders who use carefully designed trading behaviors to manually push up or down the underlying equity prices for making profits. With increasing volumes and frequency of trading, price manipulation can be extremely damaging to the proper functioning and integrity of capital markets. The existing literature focuses on either empirical studies of market abuse cases or analysis of particular manipulation types based on certain assumptions. Effective approaches for analyzing and detecting price manipulation in real time are yet to be developed. This paper proposes a novel approach, called adaptive hidden Markov model with anomaly states (AHMMAS) for modeling and detecting price manipulation activities. Together with wavelet transformations and gradients as the feature extraction methods, the AHMMAS model caters to price manipulation detection and basic manipulation type recognition. The evaluation experiments conducted on seven stock tick data from NASDAQ and the London Stock Exchange and 10 simulated stock prices by stochastic differential equation show that the proposed AHMMAS model can effectively detect price manipulation patterns and outperforms the selected benchmark models.

Photoacoustic imaging of hidden dental caries by using a fiber-based probing system

Science.gov (United States)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2017-04-01

Photoacoustic method to detect hidden dental caries is proposed. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating laser light to occlusal surface of model tooth. By making a map of intensity of these high frequency components, photoacoustic images of hidden caries were successfully obtained. A photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for using clinical application, and clear photoacoustic image of hidden caries was also obtained by this system.

A hidden history

OpenAIRE

Peppers, Emily

2008-01-01

The Cultural Collections Audit project began at the University of Edinburgh in 2004, searching for hidden treasures in its 'distributed heritage collections' across the university. The objects and collections recorded in the Audit ranged widely from fine art and furniture to historical scientific and teaching equipment and personalia relating to key figures in the university's long tradition of academic excellence. This information was gathered in order to create a central database of informa...

Life imitating art: depictions of the hidden curriculum in medical television programs.

Science.gov (United States)

Stanek, Agatha; Clarkin, Chantalle; Bould, M Dylan; Writer, Hilary; Doja, Asif

2015-09-26

The hidden curriculum represents influences occurring within the culture of medicine that indirectly alter medical professionals' interactions, beliefs and clinical practices throughout their training. One approach to increase medical student awareness of the hidden curriculum is to provide them with readily available examples of how it is enacted in medicine; as such the purpose of this study was to examine depictions of the hidden curriculum in popular medical television programs. One full season of ER, Grey's Anatomy and Scrubs were selected for review. A summative content analysis was performed to ascertain the presence of depictions of the hidden curriculum, as well as to record the type, frequency and quality of examples. A second reviewer also viewed a random selection of episodes from each series to establish coding reliability. The most prevalent themes across all television programs were: the hierarchical nature of medicine; challenges during transitional stages in medicine; the importance of role modeling; patient dehumanization; faking or overstating one's capabilities; unprofessionalism; the loss of idealism; and difficulties with work-life balance. The hidden curriculum is frequently depicted in popular medical television shows. These examples of the hidden curriculum could serve as a valuable teaching resource in undergraduate medical programs.

Rare Z boson decays to a hidden sector

Science.gov (United States)

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

2018-01-01

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery.

Science.gov (United States)

Ahmidi, Narges; Tao, Lingling; Sefati, Shahin; Gao, Yixin; Lea, Colin; Haro, Benjamin Bejar; Zappella, Luca; Khudanpur, Sanjeev; Vidal, Rene; Hager, Gregory D

2017-09-01

State-of-the-art techniques for surgical data analysis report promising results for automated skill assessment and action recognition. The contributions of many of these techniques, however, are limited to study-specific data and validation metrics, making assessment of progress across the field extremely challenging. In this paper, we address two major problems for surgical data analysis: First, lack of uniform-shared datasets and benchmarks, and second, lack of consistent validation processes. We address the former by presenting the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS), a public dataset that we have created to support comparative research benchmarking. JIGSAWS contains synchronized video and kinematic data from multiple performances of robotic surgical tasks by operators of varying skill. We address the latter by presenting a well-documented evaluation methodology and reporting results for six techniques for automated segmentation and classification of time-series data on JIGSAWS. These techniques comprise four temporal approaches for joint segmentation and classification: hidden Markov model, sparse hidden Markov model (HMM), Markov semi-Markov conditional random field, and skip-chain conditional random field; and two feature-based ones that aim to classify fixed segments: bag of spatiotemporal features and linear dynamical systems. Most methods recognize gesture activities with approximately 80% overall accuracy under both leave-one-super-trial-out and leave-one-user-out cross-validation settings. Current methods show promising results on this shared dataset, but room for significant progress remains, particularly for consistent prediction of gesture activities across different surgeons. The results reported in this paper provide the first systematic and uniform evaluation of surgical activity recognition techniques on the benchmark database.

Cosmological abundance of the QCD axion coupled to hidden photons

Science.gov (United States)

Kitajima, Naoya; Sekiguchi, Toyokazu; Takahashi, Fuminobu

2018-06-01

We study the cosmological evolution of the QCD axion coupled to hidden photons. For a moderately strong coupling, the motion of the axion field leads to an explosive production of hidden photons by tachyonic instability. We use lattice simulations to evaluate the cosmological abundance of the QCD axion. In doing so, we incorporate the backreaction of the produced hidden photons on the axion dynamics, which becomes significant in the non-linear regime. We find that the axion abundance is suppressed by at most O (102) for the decay constant fa =1016GeV, compared to the case without the coupling. For a sufficiently large coupling, the motion of the QCD axion becomes strongly damped, and as a result, the axion abundance is enhanced. Our results show that the cosmological upper bound on the axion decay constant can be relaxed by a few hundred for a certain range of the coupling to hidden photons.

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

Energy Technology Data Exchange (ETDEWEB)

Riber Marklund, A. [CEA, Cadarache, DEN/DTN/STCP/LIET, Batiment 202, 13108 St Paul-lez-Durance, (France); Kishore, S. [Fast Reactor Technology Group of IGCAR, (India); Prakash, V. [Vibrations Diagnostics Division, Fast Reactor Technology Group of IGCAR, (India); Rajan, K.K. [Fast Reactor Technology Group and Engineering Services Group of IGCAR, (India)

2015-07-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)

Low-scale gravity mediation in warped extra dimension and collider phenomenology on hidden sector

International Nuclear Information System (INIS)

Itoh, H.; Okada, N.; Yamashita, T.

2007-01-01

We propose a new scenario of gravity-mediated supersymmetry breaking (gravity mediation) in a supersymmetric Randall-Sundrum model, where the gravity mediation takes place at a low scale due to the warped metric. We investigate collider phenomenology involving the hidden sector field, and find a possibility that the hidden sector field can be produced at the LHC and the ILC. The hidden sector may no longer be hidden. (author)

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.

A Bayesian Approach for Structural Learning with Hidden Markov Models

Directory of Open Access Journals (Sweden)

Cen Li

2002-01-01

Full Text Available Hidden Markov Models(HMM have proved to be a successful modeling paradigm for dynamic and spatial processes in many domains, such as speech recognition, genomics, and general sequence alignment. Typically, in these applications, the model structures are predefined by domain experts. Therefore, the HMM learning problem focuses on the learning of the parameter values of the model to fit the given data sequences. However, when one considers other domains, such as, economics and physiology, model structure capturing the system dynamic behavior is not available. In order to successfully apply the HMM methodology in these domains, it is important that a mechanism is available for automatically deriving the model structure from the data. This paper presents a HMM learning procedure that simultaneously learns the model structure and the maximum likelihood parameter values of a HMM from data. The HMM model structures are derived based on the Bayesian model selection methodology. In addition, we introduce a new initialization procedure for HMM parameter value estimation based on the K-means clustering method. Experimental results with artificially generated data show the effectiveness of the approach.

Facial emotional recognition in schizophrenia: preliminary results of the virtual reality program for facial emotional recognition

Directory of Open Access Journals (Sweden)

Teresa Souto

2013-01-01

Full Text Available BACKGROUND: Significant deficits in emotional recognition and social perception characterize patients with schizophrenia and have direct negative impact both in inter-personal relationships and in social functioning. Virtual reality, as a methodological resource, might have a high potential for assessment and training skills in people suffering from mental illness. OBJECTIVES: To present preliminary results of a facial emotional recognition assessment designed for patients with schizophrenia, using 3D avatars and virtual reality. METHODS: Presentation of 3D avatars which reproduce images developed with the FaceGen® software and integrated in a three-dimensional virtual environment. Each avatar was presented to a group of 12 patients with schizophrenia and a reference group of 12 subjects without psychiatric pathology. RESULTS: The results show that the facial emotions of happiness and anger are better recognized by both groups and that the major difficulties arise in fear and disgust recognition. Frontal alpha electroencephalography variations were found during the presentation of anger and disgust stimuli among patients with schizophrenia. DISCUSSION: The developed program evaluation module can be of surplus value both for patient and therapist, providing the task execution in a non anxiogenic environment, however similar to the actual experience.

An impossibility theorem for parameter independent hidden variable theories

Science.gov (United States)

Leegwater, Gijs

2016-05-01

Recently, Roger Colbeck and Renato Renner (C&R) have claimed that '[n]o extension of quantum theory can have improved predictive power' (Colbeck & Renner, 2011, 2012b). If correct, this is a spectacular impossibility theorem for hidden variable theories, which is more general than the theorems of Bell (1964) and Leggett (2003). Also, C&R have used their claim in attempt to prove that a system's quantum-mechanical wave function is in a one-to-one correspondence with its 'ontic' state (Colbeck & Renner, 2012a). C&R's claim essentially means that in any hidden variable theory that is compatible with quantum-mechanical predictions, probabilities of measurement outcomes are independent of these hidden variables. This makes such variables otiose. On closer inspection, however, the generality and validity of the claim can be contested. First, it is based on an assumption called 'Freedom of Choice'. As the name suggests, this assumption involves the independence of an experimenter's choice of measurement settings. But in the way C&R define this assumption, a no-signalling condition is surreptitiously presupposed, making the assumption less innocent than it sounds. When using this definition, any hidden variable theory violating parameter independence, such as Bohmian Mechanics, is immediately shown to be incompatible with quantum-mechanical predictions. Also, the argument of C&R is hard to follow and their mathematical derivation contains several gaps, some of which cannot be closed in the way they suggest. We shall show that these gaps can be filled. The issue with the 'Freedom of Choice' assumption can be circumvented by explicitly assuming parameter independence. This makes the result less general, but better founded. We then obtain an impossibility theorem for hidden variable theories satisfying parameter independence only. As stated above, such hidden variable theories are impossible in the sense that any supplemental variables have no bearing on outcome probabilities

Entry deterrence and hidden competition

NARCIS (Netherlands)

Lavrutich, Maria; Huisman, Kuno; Kort, Peter

This paper studies strategic investment behavior of firms facing an uncertain demand in a duopoly setting. Firms choose both investment timing and the capacity level while facing additional uncertainty about market participants, which is introduced via the concept of hidden competition. We focus on

Adaptive Partially Hidden Markov Models

DEFF Research Database (Denmark)

Forchhammer, Søren Otto; Rasmussen, Tage

1996-01-01

Partially Hidden Markov Models (PHMM) have recently been introduced. The transition and emission probabilities are conditioned on the past. In this report, the PHMM is extended with a multiple token version. The different versions of the PHMM are applied to bi-level image coding....

Validation of Inter-Subject Training for Hidden Markov Models Applied to Gait Phase Detection in Children with Cerebral Palsy

Directory of Open Access Journals (Sweden)

Juri Taborri

2015-09-01

Full Text Available Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6, with the best performance for the distributed classifier in two-phase recognition (G = 0.02. Differences were found among gait partitioning models, while no differences were found between training procedures with the exception of the shank classifier. Our results raise the possibility of avoiding subject-specific training in HMM for gait-phase recognition and its implementation to control exoskeletons for the pediatric population.

Applications of hidden symmetries to black hole physics

International Nuclear Information System (INIS)

Frolov, Valeri

2011-01-01

This work is a brief review of applications of hidden symmetries to black hole physics. Symmetry is one of the most important concepts of the science. In physics and mathematics the symmetry allows one to simplify a problem, and often to make it solvable. According to the Noether theorem symmetries are responsible for conservation laws. Besides evident (explicit) spacetime symmetries, responsible for conservation of energy, momentum, and angular momentum of a system, there also exist what is called hidden symmetries, which are connected with higher order in momentum integrals of motion. A remarkable fact is that black holes in four and higher dimensions always possess a set ('tower') of explicit and hidden symmetries which make the equations of motion of particles and light completely integrable. The paper gives a general review of the recently obtained results. The main focus is on understanding why at all black holes have something (symmetry) to hide.

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

Science.gov (United States)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

Extricating Manual and Non-Manual Features for Subunit Level Medical Sign Modelling in Automatic Sign Language Classification and Recognition.

Science.gov (United States)

R, Elakkiya; K, Selvamani

2017-09-22

Subunit segmenting and modelling in medical sign language is one of the important studies in linguistic-oriented and vision-based Sign Language Recognition (SLR). Many efforts were made in the precedent to focus the functional subunits from the view of linguistic syllables but the problem is implementing such subunit extraction using syllables is not feasible in real-world computer vision techniques. And also, the present recognition systems are designed in such a way that it can detect the signer dependent actions under restricted and laboratory conditions. This research paper aims at solving these two important issues (1) Subunit extraction and (2) Signer independent action on visual sign language recognition. Subunit extraction involved in the sequential and parallel breakdown of sign gestures without any prior knowledge on syllables and number of subunits. A novel Bayesian Parallel Hidden Markov Model (BPaHMM) is introduced for subunit extraction to combine the features of manual and non-manual parameters to yield better results in classification and recognition of signs. Signer independent action aims in using a single web camera for different signer behaviour patterns and for cross-signer validation. Experimental results have proved that the proposed signer independent subunit level modelling for sign language classification and recognition has shown improvement and variations when compared with other existing works.

Application of unsupervised pattern recognition approaches for exploration of rare earth elements in Se-Chahun iron ore, central Iran

Science.gov (United States)

Sarparandeh, Mohammadali; Hezarkhani, Ardeshir

2017-12-01

The use of efficient methods for data processing has always been of interest to researchers in the field of earth sciences. Pattern recognition techniques are appropriate methods for high-dimensional data such as geochemical data. Evaluation of the geochemical distribution of rare earth elements (REEs) requires the use of such methods. In particular, the multivariate nature of REE data makes them a good target for numerical analysis. The main subject of this paper is application of unsupervised pattern recognition approaches in evaluating geochemical distribution of REEs in the Kiruna type magnetite-apatite deposit of Se-Chahun. For this purpose, 42 bulk lithology samples were collected from the Se-Chahun iron ore deposit. In this study, 14 rare earth elements were measured with inductively coupled plasma mass spectrometry (ICP-MS). Pattern recognition makes it possible to evaluate the relations between the samples based on all these 14 features, simultaneously. In addition to providing easy solutions, discovery of the hidden information and relations of data samples is the advantage of these methods. Therefore, four clustering methods (unsupervised pattern recognition) - including a modified basic sequential algorithmic scheme (MBSAS), hierarchical (agglomerative) clustering, k-means clustering and self-organizing map (SOM) - were applied and results were evaluated using the silhouette criterion. Samples were clustered in four types. Finally, the results of this study were validated with geological facts and analysis results from, for example, scanning electron microscopy (SEM), X-ray diffraction (XRD), ICP-MS and optical mineralogy. The results of the k-means clustering and SOM methods have the best matches with reality, with experimental studies of samples and with field surveys. Since only the rare earth elements are used in this division, a good agreement of the results with lithology is considerable. It is concluded that the combination of the proposed

Detecting Hidden Hierarchy of Non Hierarchical Terrorist Networks

DEFF Research Database (Denmark)

Memon, Nasrullah

measures (and combinations of them) to identify key players (important nodes) in terrorist networks. Our recently introduced techniques and algorithms (which are also implemented in the investigative data mining toolkit known as iMiner) will be particularly useful for law enforcement agencies that need...... to analyze terrorist networks and prioritize their targets. Applying recently introduced mathematical methods for constructing the hidden hierarchy of "nonhierarchical" terrorist networks; we present case studies of the terrorist attacks occurred / planned in the past, in order to identify hidden hierarchy...

SeisCode: A seismological software repository for discovery and collaboration

Science.gov (United States)

Trabant, C.; Reyes, C. G.; Clark, A.; Karstens, R.

2012-12-01

SeisCode is a community repository for software used in seismological and related fields. The repository is intended to increase discoverability of such software and to provide a long-term home for software projects. Other places exist where seismological software may be found, but none meet the requirements necessary for an always current, easy to search, well documented, and citable resource for projects. Organizations such as IRIS, ORFEUS, and the USGS have websites with lists of available or contributed seismological software. Since the authors themselves do often not maintain these lists, the documentation often consists of a sentence or paragraph, and the available software may be outdated. Repositories such as GoogleCode and SourceForge, which are directly maintained by the authors, provide version control and issue tracking but do not provide a unified way of locating geophysical software scattered in and among countless unrelated projects. Additionally, projects are hosted at language-specific sites such as Mathworks and PyPI, in FTP directories, and in websites strewn across the Web. Search engines are only partially effective discovery tools, as the desired software is often hidden deep within the results. SeisCode provides software authors a place to present their software, codes, scripts, tutorials, and examples to the seismological community. Authors can choose their own level of involvement. At one end of the spectrum, the author might simply create a web page that points to an existing site. At the other extreme, an author may choose to leverage the many tools provided by SeisCode, such as a source code management tool with integrated issue tracking, forums, news feeds, downloads, wikis, and more. For software development projects with multiple authors, SeisCode can also be used as a central site for collaboration. SeisCode provides the community with an easy way to discover software, while providing authors a way to build a community around their

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.

Signatures of a hidden cosmic microwave background.

Science.gov (United States)

Jaeckel, Joerg; Redondo, Javier; Ringwald, Andreas

2008-09-26

If there is a light Abelian gauge boson gamma' in the hidden sector its kinetic mixing with the photon can produce a hidden cosmic microwave background (HCMB). For meV masses, resonant oscillations gammagamma' happen after big bang nucleosynthesis (BBN) but before CMB decoupling, increasing the effective number of neutrinos Nnu(eff) and the baryon to photon ratio, and distorting the CMB blackbody spectrum. The agreement between BBN and CMB data provides new constraints. However, including Lyman-alpha data, Nnu(eff) > 3 is preferred. It is tempting to attribute this effect to the HCMB. The interesting parameter range will be tested in upcoming laboratory experiments.

Sneaking a peek: pigeons use peripheral vision (not mirrors) to find hidden food.

Science.gov (United States)

Ünver, Emre; Garland, Alexis; Tabrik, Sepideh; Güntürkün, Onur

2017-07-01

A small number of species are capable of recognizing themselves in the mirror when tested with the mark-and-mirror test. This ability is often seen as evidence of self-recognition and possibly even self-awareness. Strangely, a number of species, for example monkeys, pigs and dogs, are unable to pass the mark test but can locate rewarding objects by using the reflective properties of a mirror. Thus, these species seem to understand how a visual reflection functions but cannot apply it to their own image. We tested this discrepancy in pigeons-a species that does not spontaneously pass the mark test. Indeed, we discovered that pigeons can successfully find a hidden food reward using only the reflection, suggesting that pigeons can also use and potentially understand the reflective properties of mirrors, even in the absence of self-recognition. However, tested under monocular conditions, the pigeons approached and attempted to walk through the mirror rather than approach the physical food, displaying similar behavior to patients with mirror agnosia. These findings clearly show that pigeons do not use the reflection of mirrors to locate reward, but actually see the food peripherally with their near-panoramic vision. A re-evaluation of our current understanding of mirror-mediated behavior might be necessary-especially taking more fully into account species differences in visual field. This study suggests that use of reflections in a mirrored surface as a tool may be less widespread than currently thought.

Hidden inventory and safety considerations

International Nuclear Information System (INIS)

Anderson, A.R.; James, R.H.; Morgan, F.

1976-01-01

Preliminary results are described of the evaluation of residual plutonium in a process line used for the production of experimental fast reactor fuel. Initial attention has been focussed on a selection of work boxes used for processing powders and solutions. Amounts of material measured as ''hidden inventory'' are generally less than 0.1 percent of throughput but in one box containing very complex equipment the amount was exceptionally about 0.5 percent. The total surface area of the box and the installed equipment appears to be the most significant factor in determining the amount of plutonium held-up as ''hidden inventory,'' representing an average of about 4 x 10 -4 g cm -2 . Present results are based on gamma spectrometer measurements but neutron techniques are being developed to overcome some of the inherent uncertainties in the gamma method. It is suggested that the routine use of sample plates of known surface area would be valuable in monitoring the deposition of plutonium in work boxes

Hidden School Dropout among Immigrant Students: A Cross-Sectional Study

Science.gov (United States)

Makarova, Elena; Herzog, Walter

2013-01-01

Actual school dropout among immigrant youth has been addressed in a number of studies, but research on hidden school dropout among immigrant students is rare. Thus, the objective of this paper is to analyze hidden school dropout among primary school students with an immigrant background. The analyses were performed using survey data of 1186…

WIMPless dark matter from non-Abelian hidden sectors with anomaly-mediated supersymmetry breaking

International Nuclear Information System (INIS)

Feng, Jonathan L.; Shadmi, Yael

2011-01-01

In anomaly-mediated supersymmetry breaking models, superpartner masses are proportional to couplings squared. Their hidden sectors therefore naturally contain WIMPless dark matter, particles whose thermal relic abundance is guaranteed to be of the correct size, even though they are not weakly interacting massive particles. We study viable dark matter candidates in WIMPless anomaly-mediated supersymmetry breaking models with non-Abelian hidden sectors and highlight unusual possibilities that emerge in even the simplest models. In one example with a pure SU(N) hidden sector, stable hidden gluinos freeze out with the correct relic density, but have an extremely low, but natural, confinement scale, providing a framework for self-interacting dark matter. In another simple scenario, hidden gluinos freeze out and decay to visible Winos with the correct relic density, and hidden glueballs may either be stable, providing a natural framework for mixed cold-hot dark matter, or may decay, yielding astrophysical signals. Last, we present a model with light hidden pions that may be tested with improved constraints on the number of nonrelativistic degrees of freedom. All of these scenarios are defined by a small number of parameters, are consistent with gauge coupling unification, preserve the beautiful connection between the weak scale and the observed dark matter relic density, and are natural, with relatively light visible superpartners. We conclude with comments on interesting future directions.

QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting.

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Dominic Waithe

Full Text Available We report the development and testing of software called QuantiFly: an automated tool to quantify Drosophila egg laying. Many laboratories count Drosophila eggs as a marker of fitness. The existing method requires laboratory researchers to count eggs manually while looking down a microscope. This technique is both time-consuming and tedious, especially when experiments require daily counts of hundreds of vials. The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. The accuracy of the baseline algorithm is additionally increased in this study through correction of bias observed in the algorithm output. The QuantiFly software, which includes the refined algorithm, has been designed to be immediately accessible to scientists through an intuitive and responsive user-friendly graphical interface. The software is also open-source, self-contained, has no dependencies and is easily installed (https://github.com/dwaithe/quantifly. Compared to manual egg counts made from digital images, QuantiFly achieved average accuracies of 94% and 85% for eggs laid on transparent (defined and opaque (yeast-based fly media. Thus, the software is capable of detecting experimental differences in most experimental situations. Significantly, the advanced feature recognition capabilities of the software proved to be robust to food surface artefacts like bubbles and crevices. The user experience involves image acquisition, algorithm training by labelling a subset of eggs in images of some of the vials, followed by a batch analysis mode in which new images are automatically assessed for egg numbers. Initial training typically requires approximately 10 minutes, while subsequent image evaluation by the software is performed in just a few seconds. Given the average time per vial for manual counting is approximately 40 seconds, our software introduces a timesaving advantage for

On the hidden maxwell superalgebra underlying D = 4 supergravity

Energy Technology Data Exchange (ETDEWEB)

Penafiel, D.M. [Departamento de Fisica, Universidad de Concepcion (Chile); DISAT, Politecnico di Torino (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Torino (Italy); Ravera, L. [DISAT, Politecnico di Torino (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Torino (Italy)

2017-09-15

In this work, we expand the hidden AdS-Lorentz superalgebra underlying D = 4 supergravity, reaching a (hidden) Maxwell superalgebra. The latter can be viewed as an extension involving cosmological constant of the superalgebra underlying D = 4 supergravity in flat spacetime. We write the Maurer-Cartan equations in this context and we find some interesting extensions of the antisymmetric 3-form A{sup (3)} appearing in the Free Differential Algebra in Minkowski space. The structure of Free Differential Algebras is obtained by considering the zero curvature equations. We write the parametrization of A{sup (3)} in terms of 1-forms and we rend the topological features of its extensions manifest. We interestingly find out that the structure of these extensions, and consequently the structure of the corresponding boundary contribution dA{sup (3)}, strongly depends on the form of the extra fermionic generator appearing in the hidden Maxwell superalgebra. The model we develop in this work is defined in an enlarged superspace with respect to the ordinary one, and the extra bosonic and fermionic 1-forms required for the closure of the hidden Maxwell superalgebra must be considered as physical fields in this enlarged superspace. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Face recognition using elastic grid matching through photoshop: A new approach

Directory of Open Access Journals (Sweden)

Manavpreet Kaur

2015-12-01

Full Text Available Computing grids propose to be a very efficacious, economic and ascendable way of image identification. In this paper, we propose a grid based face recognition overture employing a general template matching method to solve the timeconsuming face recognition problem. A new approach has been employed in which the grid was prepared for a specific individual over his photograph using Adobe Photoshop CS5 software. The background was later removed and the grid prepared by merging layers was used as a template for image matching or comparison. This overture is computationally efficient, has high recognition rates and is able to identify a person with minimal efforts and in short time even from photographs taken at different magnifications and from different distances.

RF-Care: Device-Free Posture Recognition for Elderly People Using A Passive RFID Tag Array

Directory of Open Access Journals (Sweden)

Lina Yao

2015-09-01

Full Text Available Activity recognition is a fundamental research topic for a wide range of important applications such as fall detection for elderly people. Existing techniques mainly rely on wearable sensors, which may not be reliable and practical in real-world situations since people often forget to wear these sensors. For this reason, device-free activity recognition has gained the popularity in recent years. In this paper, we propose an RFID (radio frequency identification based, device-free posture recognition system. More specifically, we analyze Received Signal Strength Indicator (RSSI signal patterns from an RFID tag array, and systematically examine the impact of tag configuration on system performance. On top of selected optimal subset of tags, we study the challenges on posture recognition. Apart from exploring posture classification, we specially propose to infer posture transitions via Dirichlet Process Gaussian Mixture Model (DPGMM based Hidden Markov Model (HMM, which effectively captures the nature of uncertainty caused by signal strength varieties during posture transitions. We run a pilot study to evaluate our system with 12 orientation-sensitive postures and a series of posture change sequences. We conduct extensive experiments in both lab and real-life home environments. The results demonstrate that our system achieves high accuracy in both environments, which holds the potential to support assisted living of elderly people.

The Hidden Dimensions of Databases.

Science.gov (United States)

Jacso, Peter

1994-01-01

Discusses methods of evaluating commercial online databases and provides examples that illustrate their hidden dimensions. Topics addressed include size, including the number of records or the number of titles; the number of years covered; and the frequency of updates. Comparisons of Readers' Guide Abstracts and Magazine Article Summaries are…

The Hidden Diversity of Zanclea Associated with Scleractinians Revealed by Molecular Data.

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Simone Montano

Full Text Available Scleractinian reef corals have recently been acknowledged as the most numerous host group found in association with hydroids belonging to the Zanclea genus. However, knowledge of the molecular phylogenetic relationships among Zanclea species associated with scleractinians is just beginning. This study, using the nuclear 28S rDNA region and the fast-evolving mitochondrial 16S rRNA and COI genes, provides the most comprehensive phylogenetic reconstruction of the genus Zanclea with a particular focus on the genetic diversity among Zanclea specimens associated with 13 scleractinian genera. The monophyly of Zanclea associated with scleractinians was strongly supported in all nuclear and mitochondrial phylogenetic reconstructions. Furthermore, a combined mitochondrial 16S and COI phylogenetic tree revealed a multitude of hidden molecular lineages within this group (Clades I, II, III, V, VI, VII, and VIII, suggesting the existence of both host-generalist and genus-specific lineages of Zanclea associated with scleractinians. In addition to Z. gallii living in association with the genus Acropora, we discovered four well-supported lineages (Clades I, II, III, and VII, each one forming a strict association with a single scleractinian genus, including sequences of Zanclea associated with Montipora from two geographically separated areas (Maldives and Taiwan. Two host-generalist Zanclea lineages were also observed, and one of them was formed by Zanclea specimens symbiotic with seven scleractinian genera (Clade VIII. We also found that the COI gene allows the recognition of separated hidden lineages in agreement with the commonly recommended mitochondrial 16S as a DNA barcoding gene for Hydrozoa and shows reasonable potential for phylogenetic and evolutionary analyses in the genus Zanclea. Finally, as no DNA sequences are available for the majority of the nominal Zanclea species known, we note that they will be necessary to elucidate the diversity of the

The Hidden Diversity of Zanclea Associated with Scleractinians Revealed by Molecular Data

KAUST Repository

Montano, Simone

2015-07-24

Scleractinian reef corals have recently been acknowledged as the most numerous host group found in association with hydroids belonging to the Zanclea genus. However, knowledge of the molecular phylogenetic relationships among Zanclea species associated with scleractinians is just beginning. This study, using the nuclear 28S rDNA region and the fast-evolving mitochondrial 16S rRNA and COI genes, provides the most comprehensive phylogenetic reconstruction of the genus Zanclea with a particular focus on the genetic diversity among Zanclea specimens associated with 13 scleractinian genera. The monophyly of Zanclea associated with scleractinians was strongly supported in all nuclear and mitochondrial phylogenetic reconstructions. Furthermore, a combined mitochondrial 16S and COI phylogenetic tree revealed a multitude of hidden molecular lineages within this group (Clades I, II, III, V, VI, VII, and VIII), suggesting the existence of both host-generalist and genus-specific lineages of Zanclea associated with scleractinians. In addition to Z. gallii living in association with the genus Acropora, we discovered four well-supported lineages (Clades I, II, III, and VII), each one forming a strict association with a single scleractinian genus, including sequences of Zanclea associated with Montipora from two geographically separated areas (Maldives and Taiwan). Two host-generalist Zanclea lineages were also observed, and one of them was formed by Zanclea specimens symbiotic with seven scleractinian genera (Clade VIII). We also found that the COI gene allows the recognition of separated hidden lineages in agreement with the commonly recommended mitochondrial 16S as a DNA barcoding gene for Hydrozoa and shows reasonable potential for phylogenetic and evolutionary analyses in the genus Zanclea. Finally, as no DNA sequences are available for the majority of the nominal Zanclea species known, we note that they will be necessary to elucidate the diversity of the Zanclea

Automatic speech recognition for report generation in computed tomography

International Nuclear Information System (INIS)

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

1999-01-01

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

Low-intensity interference effects and hidden-variable theories

Energy Technology Data Exchange (ETDEWEB)

Buonomano, V [Universidade Estadual de Campinas (Brazil). Inst. de Matematica

1978-05-11

The double-slit interference experiment and other similar experiments in the low-intensity limit (that is, one photon in the apparatus at a time) are examined in the spirit of Bell's work from the point of view of hidden-variable theories. It is found that there exists a class of hidden-variable theories which disagrees with quantum mechanics for a certain type of interference experiment. A manufactured conceptualization of this class, which is a particle view of interference, is described. An experiment, which appears to be feasible, is proposed to examine this disagreement.

Application of Hidden Markov Models in Biomolecular Simulations.

Science.gov (United States)

Shukla, Saurabh; Shamsi, Zahra; Moffett, Alexander S; Selvam, Balaji; Shukla, Diwakar

2017-01-01

Hidden Markov models (HMMs) provide a framework to analyze large trajectories of biomolecular simulation datasets. HMMs decompose the conformational space of a biological molecule into finite number of states that interconvert among each other with certain rates. HMMs simplify long timescale trajectories for human comprehension, and allow comparison of simulations with experimental data. In this chapter, we provide an overview of building HMMs for analyzing bimolecular simulation datasets. We demonstrate the procedure for building a Hidden Markov model for Met-enkephalin peptide simulation dataset and compare the timescales of the process.

Detecting Faults By Use Of Hidden Markov Models

Science.gov (United States)

Smyth, Padhraic J.

1995-01-01

Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).

From the solar system fo hidden cosmic structures

Energy Technology Data Exchange (ETDEWEB)

Benes, K

1987-01-01

The development of experimental astrophysics showed that in the evolution of planets, natural processes of a common nature take place. They include, e.g., radiogenic heat, the production of magmas, volcanic activity, degassing, etc. The solar system is a cosmic formation in an advanced stage of development and it is a realistic assumption that in the Galaxy other hidden planetary systems in various stages of development exist. The views on the possibility of the origination of life in other systems differ; life, however, is seen as a hidden property of cosmic matter. (M.D.).

Search for hidden Higgs decay in ATLAS detector

International Nuclear Information System (INIS)

Gabrielli, A.

2013-01-01

In this paper, a brief overview of the search for the Higgs boson in Hidden Valley models is given. Hidden Valley models predict Higgs decays to neutral particles, which can be also long lived with decay paths comparable to the LHC detectors dimensions. Decay final states consist of collimated leptons (Lepton Jets). Results are presented of a search for Higgs decays to long lived particles in the ATLAS detector at the LHC, based on 1.92 fb −1 data collected during 2011 at a 7TeV center-of-mass energy.

Dissipative hidden sector dark matter

Science.gov (United States)

Foot, R.; Vagnozzi, S.

2015-01-01

A simple way of explaining dark matter without modifying known Standard Model physics is to require the existence of a hidden (dark) sector, which interacts with the visible one predominantly via gravity. We consider a hidden sector containing two stable particles charged under an unbroken U (1 )' gauge symmetry, hence featuring dissipative interactions. The massless gauge field associated with this symmetry, the dark photon, can interact via kinetic mixing with the ordinary photon. In fact, such an interaction of strength ε ˜10-9 appears to be necessary in order to explain galactic structure. We calculate the effect of this new physics on big bang nucleosynthesis and its contribution to the relativistic energy density at hydrogen recombination. We then examine the process of dark recombination, during which neutral dark states are formed, which is important for large-scale structure formation. Galactic structure is considered next, focusing on spiral and irregular galaxies. For these galaxies we modeled the dark matter halo (at the current epoch) as a dissipative plasma of dark matter particles, where the energy lost due to dissipation is compensated by the energy produced from ordinary supernovae (the core-collapse energy is transferred to the hidden sector via kinetic mixing induced processes in the supernova core). We find that such a dynamical halo model can reproduce several observed features of disk galaxies, including the cored density profile and the Tully-Fisher relation. We also discuss how elliptical and dwarf spheroidal galaxies could fit into this picture. Finally, these analyses are combined to set bounds on the parameter space of our model, which can serve as a guideline for future experimental searches.

Hidden twelve-dimensional super Poincare symmetry in eleven dimensions

International Nuclear Information System (INIS)

Bars, Itzhak; Deliduman, Cemsinan; Pasqua, Andrea; Zumino, Bruno

2004-01-01

First, we review a result in our previous paper, of how a ten-dimensional superparticle, taken off-shell, has a hidden eleven-dimensional super Poincare symmetry. Then, we show that the physical sector is defined by three first-class constraints which preserve the full eleven-dimensional symmetry. Applying the same concepts to the eleven-dimensional superparticle, taken off-shell, we discover a hidden twelve-dimensional super Poincare symmetry that governs the theory

Electroweak-charged bound states as LHC probes of hidden forces

Science.gov (United States)

Li, Lingfeng; Salvioni, Ennio; Tsai, Yuhsin; Zheng, Rui

2018-01-01

We explore the LHC reach on beyond-the-standard model (BSM) particles X associated with a new strong force in a hidden sector. We focus on the motivated scenario where the SM and hidden sectors are connected by fermionic mediators ψ+,0 that carry SM electroweak charges. The most promising signal is the Drell-Yan production of a ψ±ψ¯ 0 pair, which forms an electrically charged vector bound state ϒ± due to the hidden force and later undergoes resonant annihilation into W±X . We analyze this final state in detail in the cases where X is a real scalar ϕ that decays to b b ¯, or a dark photon γd that decays to dileptons. For prompt X decays, we show that the corresponding signatures can be efficiently probed by extending the existing ATLAS and CMS diboson searches to include heavy resonance decays into BSM particles. For long-lived X , we propose new searches where the requirement of a prompt hard lepton originating from the W boson ensures triggering and essentially removes any SM backgrounds. To illustrate the potential of our results, we interpret them within two explicit models that contain strong hidden forces and electroweak-charged mediators, namely λ -supersymmetry (SUSY) and non-SUSY ultraviolet extensions of the twin Higgs model. The resonant nature of the signals allows for the reconstruction of the mass of both ϒ± and X , thus providing a wealth of information about the hidden sector.

Behaviour Recognition from Sensory Streams in Smart Environments

Science.gov (United States)

Chua, Sook-Ling; Marsland, Stephen; Guesgen, Hans W.

One application of smart homes is to take sensor activations from a variety of sensors around the house and use them to recognise the particular behaviours of the inhabitants. This can be useful for monitoring of the elderly or cognitively impaired, amongst other applications. Since the behaviours themselves are not directly observed, only the observations by sensors, it is common to build a probabilistic model of how behaviours arise from these observations, for example in the form of a Hidden Markov Model (HMM). In this paper we present a method of selecting which of a set of trained HMMs best matches the current observations, together with experiments showing that it can reliably detect and segment the sensor stream into behaviours. We demonstrate our algorithm on real sensor data obtained from the MIT PlaceLab. The results show a significant improvement in the recognition accuracy over other approaches.

Application of ANNS in tube CHF prediction: effect on neuron number in hidden layer

International Nuclear Information System (INIS)

Han, L.; Shan, J.; Zhang, B.

2004-01-01

Prediction of the Critical Heat Flux (CHF) for upward flow of water in uniformly heated vertical round tube is studied with Artificial Neuron Networks (ANNs) method utilizing different neuron number in hidden layers. This study is based on thermal equilibrium conditions. The neuron number in hidden layers is chosen to vary from 5 to 30 with the step of 5. The effect due to the variety of the neuron number in hidden layers is analyzed. The analysis shows that the neuron number in hidden layers should be appropriate, too less will affect the prediction accuracy and too much may result in abnormal parametric trends. It is concluded that the appropriate neuron number in two hidden layers should be [15 15]. (authors)

UV Photography Shows Hidden Sun Damage

Science.gov (United States)

... mcat1=de12", ]; for (var c = 0; c UV photography shows hidden sun damage A UV photograph gives ... developing skin cancer and prematurely aged skin. Normal photography UV photography 18 months of age: This boy's ...

An Accurate and Efficient User Authentication Mechanism on Smart Glasses Based on Iris Recognition

Directory of Open Access Journals (Sweden)

Yung-Hui Li

2017-01-01

Full Text Available In modern society, mobile devices (such as smart phones and wearable devices have become indispensable to almost everyone, and people store personal data in devices. Therefore, how to implement user authentication mechanism for private data protection on mobile devices is a very important issue. In this paper, an intelligent iris recognition mechanism is designed to solve the problem of user authentication in wearable smart glasses. Our contributions include hardware and software. On the hardware side, we design a set of internal infrared camera modules, including well-designed infrared light source and lens module, which is able to take clear iris images within 2~5 cm. On the software side, we propose an innovative iris segmentation algorithm which is both efficient and accurate to be used on smart glasses device. Another improvement to the traditional iris recognition is that we propose an intelligent Hamming distance (HD threshold adaptation method which dynamically fine-tunes the HD threshold used for verification according to empirical data collected. Our final system can perform iris recognition with 66 frames per second on a smart glasses platform with 100% accuracy. As far as we know, this system is the world’s first application of iris recognition on smart glasses.

Impact of gender and opportunity recognition on attitude to piracy of ...

African Journals Online (AJOL)

Impact of gender and opportunity recognition on attitude to piracy of computer industry products. ... Software piracy has defied punitive measures, posing threats to jobs of millions of employees and the computer industry. The study proposed an ... Practical implications of findings and future research directions are discussed.

Toward a Differential Diagnosis of Hidden Hearing Loss in Humans.

Directory of Open Access Journals (Sweden)

M Charles Liberman

Full Text Available Recent work suggests that hair cells are not the most vulnerable elements in the inner ear; rather, it is the synapses between hair cells and cochlear nerve terminals that degenerate first in the aging or noise-exposed ear. This primary neural degeneration does not affect hearing thresholds, but likely contributes to problems understanding speech in difficult listening environments, and may be important in the generation of tinnitus and/or hyperacusis. To look for signs of cochlear synaptopathy in humans, we recruited college students and divided them into low-risk and high-risk groups based on self-report of noise exposure and use of hearing protection. Cochlear function was assessed by otoacoustic emissions and click-evoked electrocochleography; hearing was assessed by behavioral audiometry and word recognition with or without noise or time compression and reverberation. Both groups had normal thresholds at standard audiometric frequencies, however, the high-risk group showed significant threshold elevation at high frequencies (10-16 kHz, consistent with early stages of noise damage. Electrocochleography showed a significant difference in the ratio between the waveform peaks generated by hair cells (Summating Potential; SP vs. cochlear neurons (Action Potential; AP, i.e. the SP/AP ratio, consistent with selective neural loss. The high-risk group also showed significantly poorer performance on word recognition in noise or with time compression and reverberation, and reported heightened reactions to sound consistent with hyperacusis. These results suggest that the SP/AP ratio may be useful in the diagnosis of "hidden hearing loss" and that, as suggested by animal models, the noise-induced loss of cochlear nerve synapses leads to deficits in hearing abilities in difficult listening situations, despite the presence of normal thresholds at standard audiometric frequencies.

A Dynamic Hidden Forwarding Path Planning Method Based on Improved Q-Learning in SDN Environments

Directory of Open Access Journals (Sweden)

Yun Chen

2018-01-01

Full Text Available Currently, many methods are available to improve the target network’s security. The vast majority of them cannot obtain an optimal attack path and interdict it dynamically and conveniently. Almost all defense strategies aim to repair known vulnerabilities or limit services in target network to improve security of network. These methods cannot response to the attacks in real-time because sometimes they need to wait for manufacturers releasing corresponding countermeasures to repair vulnerabilities. In this paper, we propose an improved Q-learning algorithm to plan an optimal attack path directly and automatically. Based on this path, we use software-defined network (SDN to adjust routing paths and create hidden forwarding paths dynamically to filter vicious attack requests. Compared to other machine learning algorithms, Q-learning only needs to input the target state to its agents, which can avoid early complex training process. We improve Q-learning algorithm in two aspects. First, a reward function based on the weights of hosts and attack success rates of vulnerabilities is proposed, which can adapt to different network topologies precisely. Second, we remove the actions and merge them into every state that reduces complexity from O(N3 to O(N2. In experiments, after deploying hidden forwarding paths, the security of target network is boosted significantly without having to repair network vulnerabilities immediately.

Anomalies of hidden local chiral symmetries in sigma-models and extended supergravities

International Nuclear Information System (INIS)

Vecchia, P. di; Ferrara, S.; Girardello, L.

1985-01-01

Non-linear sigma-models with hidden gauge symmetries are anomalous, at the quantum level, when coupled to chiral fermions in not anomaly free representations of the hidden chiral symmetry. These considerations generally apply to supersymmetric kaehlerian sigma-models on coset spaces with hidden chiral symmetries as well as to extended supergravities in four dimensions with local SU(N) symmetry. The presence of the anomaly implies that the scenario of dynamical generation of gauge vector bosons has to be reconsidered in these theories. (orig.)

Review of hidden carbon emissions, trade, and labor income share in China, 2001–2011

International Nuclear Information System (INIS)

Wang, Shu-Hong; Song, Ma-Lin

2014-01-01

Coordinated development between the economy and the environment is currently one of the most important issues in China. By establishing models concerning labor income share and hidden carbon emissions, and taking trade as the link in their relationship, this study puts forward the scale effects, technological effects, and structural effects that relate to labor income share under the function of trade. We then establish multi-index and multi-indicator constitutive (MIMIC) equation to measure the ratio of hidden carbon emissions to total emissions, which is further considered the basis of the measurement model. Results of regression analysis carried out on labor income share show that hidden carbon emissions do have a positive effect on labor income share. In the meantime, we also prove that under scale effects, technological effects, and the structural effects of trade, hidden carbon emissions affect labor income shares in different directions. Our conclusions and policy implications are obtained from the calculated results. - Highlights: • This study establishes models concerning labor income share and hidden carbon emissions. • MIMIC is established to measure the ratio of hidden carbon emissions to total discharge. • Hidden carbon emissions have a positive effect on labor income share. • Hidden carbon emissions have various effects on the labor income share

Cross-Modality 2D-3D Face Recognition via Multiview Smooth Discriminant Analysis Based on ELM

Directory of Open Access Journals (Sweden)

Yi Jin

2014-01-01

Full Text Available In recent years, 3D face recognition has attracted increasing attention from worldwide researchers. Rather than homogeneous face data, more and more applications require flexible input face data nowadays. In this paper, we propose a new approach for cross-modality 2D-3D face recognition (FR, which is called Multiview Smooth Discriminant Analysis (MSDA based on Extreme Learning Machines (ELM. Adding the Laplacian penalty constrain for the multiview feature learning, the proposed MSDA is first proposed to extract the cross-modality 2D-3D face features. The MSDA aims at finding a multiview learning based common discriminative feature space and it can then fully utilize the underlying relationship of features from different views. To speed up the learning phase of the classifier, the recent popular algorithm named Extreme Learning Machine (ELM is adopted to train the single hidden layer feedforward neural networks (SLFNs. To evaluate the effectiveness of our proposed FR framework, experimental results on a benchmark face recognition dataset are presented. Simulations show that our new proposed method generally outperforms several recent approaches with a fast training speed.

The selection and implementation of hidden line algorithms

International Nuclear Information System (INIS)

Schneider, A.

1983-06-01

One of the most challenging problems in the field of computer graphics is the elimination of hidden lines in images of nontransparent bodies. In the real world the nontransparent material hinders the light ray coming from hidden regions to the observer. In the computer based image formation process there is no automatic visibility regulation of this kind. So many lines are created which result in a poor quality of the spacial representation. Therefore a three-dimensional representation on the screen is only meaningfull if the hidden lines are eliminated. For this process many algorithms have been developed in the past. A common feature of these codes is the large amount of computer time needed. In the first generation of algorithms, which are commonly used today, the bodies are modeled by plane polygons. More recently, however, also algorithms are in use, which are able to treat curved surfaces without discretisation by plane surfaces. In this paper the first group of algorithms is reviewed, and the most important codes are described. The experience obtained during the implementation of two algorithms is presented. (orig.) [de

Hidden sector behind the CKM matrix

Science.gov (United States)

Okawa, Shohei; Omura, Yuji

2017-08-01

The small quark mixing, described by the Cabibbo-Kobayashi-Maskawa (CKM) matrix in the standard model, may be a clue to reveal new physics around the TeV scale. We consider a simple scenario that extra particles in a hidden sector radiatively mediate the flavor violation to the quark sector around the TeV scale and effectively realize the observed CKM matrix. The lightest particle in the hidden sector, whose contribution to the CKM matrix is expected to be dominant, is a good dark matter (DM) candidate. There are many possible setups to describe this scenario, so that we investigate some universal predictions of this kind of model, focusing on the contribution of DM to the quark mixing and flavor physics. In this scenario, there is an explicit relation between the CKM matrix and flavor violating couplings, such as four-quark couplings, because both are radiatively induced by the particles in the hidden sector. Then, we can explicitly find the DM mass region and the size of Yukawa couplings between the DM and quarks, based on the study of flavor physics and DM physics. In conclusion, we show that DM mass in our scenario is around the TeV scale, and the Yukawa couplings are between O (0.01 ) and O (1 ). The spin-independent DM scattering cross section is estimated as O (10-9) [pb]. An extra colored particle is also predicted at the O (10 ) TeV scale.

The Computational Infrastructure for Geodynamics: An Example of Software Curation and Citation in the Geodynamics Community

Science.gov (United States)

Hwang, L.; Kellogg, L. H.

2017-12-01

Curation of software promotes discoverability and accessibility and works hand in hand with scholarly citation to ascribe value to, and provide recognition for software development. To meet this challenge, the Computational Infrastructure for Geodynamics (CIG) maintains a community repository built on custom and open tools to promote discovery, access, identification, credit, and provenance of research software for the geodynamics community. CIG (geodynamics.org) originated from recognition of the tremendous effort required to develop sound software and the need to reduce duplication of effort and to sustain community codes. CIG curates software across 6 domains and has developed and follows software best practices that include establishing test cases, documentation, and a citable publication for each software package. CIG software landing web pages provide access to current and past releases; many are also accessible through the CIG community repository on github. CIG has now developed abc - attribution builder for citation to enable software users to give credit to software developers. abc uses zenodo as an archive and as the mechanism to obtain a unique identifier (DOI) for scientific software. To assemble the metadata, we searched the software's documentation and research publications and then requested the primary developers to verify. In this process, we have learned that each development community approaches software attribution differently. The metadata gathered is based on guidelines established by groups such as FORCE11 and OntoSoft. The rollout of abc is gradual as developers are forward-looking, rarely willing to go back and archive prior releases in zenodo. Going forward all actively developed packages will utilize the zenodo and github integration to automate the archival process when a new release is issued. How to handle legacy software, multi-authored libraries, and assigning roles to software remain open issues.

Laser experiments explore the hidden sector

International Nuclear Information System (INIS)

Ahlers, M.

2007-11-01

Recently, the laser experiments BMV and GammeV, searching for light shining through walls, have published data and calculated new limits on the allowed masses and couplings for axion-like particles. In this note we point out that these experiments can serve to constrain a much wider variety of hidden-sector particles such as, e.g., minicharged particles and hidden-sector photons. The new experiments improve the existing bounds from the older BFRT experiment by a factor of two. Moreover, we use the new PVLAS constraints on a possible rotation and ellipticity of light after it has passed through a strong magnetic field to constrain pure minicharged particle models. For masses -7 times the electron electric charge. This is the best laboratory bound and comparable to bounds inferred from the energy spectrum of the cosmic microwave background. (orig.)

Criteria and tools for scientific software quality measurements

Energy Technology Data Exchange (ETDEWEB)

Tseng, M Y [Previse Inc., Willowdale ON (Canada)

1995-12-01

Not all software used in the nuclear industry needs the rigorous formal verification, reliability testing and quality assessment that are being applied to safety critical software. Recently, however, there is increasing recognition that systematic and objective quality assessment of the scientific software used in design and safety analyses of nuclear facilities is necessary to support safety and licensing decisions. Because of the complexity and large size of these programs and the resource constraints faced by the AECB reviewer, it is desirable that appropriate automated tools are used wherever practical. To objectively assess the quality of software, a set of attributes of a software product by which its quality is described and evaluated must be established. These attributes must be relevant to the application domain of software under evaluation. To effectively assess the quality of software, metrics defining quantitative scale and method appropriate to determine the value of attributes need to be applied. To cost-effectively perform the evaluation, use of suitable automated tools is desirable. In this project, criteria for evaluating the quality of scientific software are presented; metrics for which those criteria can be evaluated are identified; a survey of automated tools to measure those metrics was conducted and the most appropriate tool (QA Fortran) was acquired; and the tool usage was demonstrated on three sample programs. (author) 5 refs.

Criteria and tools for scientific software quality measurements

International Nuclear Information System (INIS)

Tseng, M.Y.

1995-12-01

Not all software used in the nuclear industry needs the rigorous formal verification, reliability testing and quality assessment that are being applied to safety critical software. Recently, however, there is increasing recognition that systematic and objective quality assessment of the scientific software used in design and safety analyses of nuclear facilities is necessary to support safety and licensing decisions. Because of the complexity and large size of these programs and the resource constraints faced by the AECB reviewer, it is desirable that appropriate automated tools are used wherever practical. To objectively assess the quality of software, a set of attributes of a software product by which its quality is described and evaluated must be established. These attributes must be relevant to the application domain of software under evaluation. To effectively assess the quality of software, metrics defining quantitative scale and method appropriate to determine the value of attributes need to be applied. To cost-effectively perform the evaluation, use of suitable automated tools is desirable. In this project, criteria for evaluating the quality of scientific software are presented; metrics for which those criteria can be evaluated are identified; a survey of automated tools to measure those metrics was conducted and the most appropriate tool (QA Fortran) was acquired; and the tool usage was demonstrated on three sample programs. (author) 5 refs

438 Optimal Number of States in Hidden Markov Models and its ...

African Journals Online (AJOL)

In this paper, Hidden Markov Model is applied to model human movements as to .... emit either discrete information or a continuous data derived from a Probability .... For each hidden state in the test set, the probability = ... by applying the Kullback-Leibler distance (Juang & Rabiner, 1985) which ..... One Size Does Not Fit.

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

Science.gov (United States)

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-04-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

Low scale gravity mediation with warped extra dimension and collider phenomenology on the hidden sector

International Nuclear Information System (INIS)

Itoh, Hideo; Okada, Nobuchika; Yamashita, Toshifumi

2006-01-01

We propose a scenario of gravity mediated supersymmetry breaking (gravity mediation) in a supersymmetric Randall-Sundrum model. In our setup, both the visible sector and the hidden sector coexist on the infrared (IR) brane. We introduce the Polonyi model as a simple hidden sector. Because of the warped metric, the effective cutoff scale on the IR brane is 'warped down', so that the gravity mediation occurs at a low scale. As a result, the gravitino is naturally the lightest superpartner (LSP) and contact interactions between the hidden and the visible sector fields become stronger. We address phenomenologies for various IR cutoff scales. In particular, we investigate collider phenomenology involving a scalar field (Polonyi field) in the hidden sector for the case with the IR cutoff around 10 TeV. We find a possibility that the hidden sector scalar can be produced at the LHC and the international linear collider (ILC). Interestingly, the scalar behaves like the Higgs boson of the standard model in the production process, while its decay process is quite different and, once produced, it will provide us with a very clean signature. The hidden sector may be no longer hidden

Development of an intelligent ultrasonic welding defect classification software

International Nuclear Information System (INIS)

Song, Sung Jin; Kim, Hak Joon; Jeong, Hee Don

1997-01-01

Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

In Brief: Hidden environment and health costs of energy

Science.gov (United States)

Showstack, Randy

2009-10-01

The hidden costs of energy production and use in the United States amounted to an estimated $120 billion in 2005, according to a 19 October report by the U.S. National Research Council. The report, “Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use,” examines hidden costs, including the cost of air pollution damage to human health, which are not reflected in market prices of energy sources, electricity, or gasoline. The report found that in 2005, the total annual external damages from sulfur dioxide, nitrogen oxides, and particulate matter created by coal-burning power plants that produced 95% of the nation's coal-generated electricity were about $62 billion, with nonclimate damages averaging about 3.2 cents for every kilowatt-hour of energy produced. It is estimated that by 2030, nonclimate damages will fall to 1.7 cents per kilowatt-hour. The 2030 figure assumes that new policies already slated for implementation are put in place.

LIBRA: LIgand Binding site Recognition Application.

Science.gov (United States)

Hung, Le Viet; Caprari, Silvia; Bizai, Massimiliano; Toti, Daniele; Polticelli, Fabio

2015-12-15

In recent years, structural genomics and ab initio molecular modeling activities are leading to the availability of a large number of structural models of proteins whose biochemical function is not known. The aim of this study was the development of a novel software tool that, given a protein's structural model, predicts the presence and identity of active sites and/or ligand binding sites. The algorithm implemented by ligand binding site recognition application (LIBRA) is based on a graph theory approach to find the largest subset of similar residues between an input protein and a collection of known functional sites. The algorithm makes use of two predefined databases for active sites and ligand binding sites, respectively, derived from the Catalytic Site Atlas and the Protein Data Bank. Tests indicate that LIBRA is able to identify the correct binding/active site in 90% of the cases analyzed, 90% of which feature the identified site as ranking first. As far as ligand binding site recognition is concerned, LIBRA outperforms other structure-based ligand binding sites detection tools with which it has been compared. The application, developed in Java SE 7 with a Swing GUI embedding a JMol applet, can be run on any OS equipped with a suitable Java Virtual Machine (JVM), and is available at the following URL: http://www.computationalbiology.it/software/LIBRAv1.zip. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Coupling of Hidden Sector

OpenAIRE

Królikowski, Wojciech

2016-01-01

A hypothetic Hidden Sector of the Universe, consisting of sterile fer\\-mions (``sterinos'') and sterile mediating bosons (``sterons'') of mass dimension 1 (not 2!) --- the last described by an antisymmetric tensor field --- requires to exist also a scalar isovector and scalar isoscalar in order to be able to construct electroweak invariant coupling (before spontaneously breaking its symmetry). The introduced scalar isoscalar might be a resonant source for the diphoton excess of 750 GeV, sugge...

Co-existing hidden attractors in a radio-physical oscillator system

DEFF Research Database (Denmark)

Kuznetsov, A. P.; Kuznetsov, S. P.; Mosekilde, Erik

2015-01-01

The term `hidden attractor' relates to a stable periodic, quasiperiodic or chaotic state whose basin of attraction does not overlap with the neighborhood of an unstable equilibrium point. Considering a three-dimensional oscillator system that does not allow for the existence of an equilibrium point...... frequency, describe the bifurcations through which hidden attractors of different type arise and disappear, and illustrate the form of the basins of attraction....

A two particle hidden sector and the oscillations with photons

Energy Technology Data Exchange (ETDEWEB)

Alvarez, Pedro D. [Universidad de Antofagasta, Departamento de Fisica, Antofagasta (Chile); Arias, Paola; Maldonado, Carlos [Universidad de Santiago de Chile, Departmento de Fisica, Santiago (Chile)

2018-01-15

We present a detailed study of the oscillations and optical properties for vacuum, in a model for the dark sector that contains axion-like particles and hidden photons. We provide bounds for the couplings versus the mass, using current results from ALPS-I and PVLAS. We also discuss the challenges for the detection of models with more than one hidden particle in light shining trough wall-like experiments. (orig.)

Computer-Aided Authoring of Programmed Instruction for Teaching Symbol Recognition. Final Report.

Science.gov (United States)

Braby, Richard; And Others

This description of AUTHOR, a computer program for the automated authoring of programmed texts designed to teach symbol recognition, includes discussions of the learning strategies incorporated in the design of the instructional materials, hardware description and the algorithm for the software, and current and future developments. Appendices…

Optimal no-go theorem on hidden-variable predictions of effect expectations

Science.gov (United States)

Blass, Andreas; Gurevich, Yuri

2018-03-01

No-go theorems prove that, under reasonable assumptions, classical hidden-variable theories cannot reproduce the predictions of quantum mechanics. Traditional no-go theorems proved that hidden-variable theories cannot predict correctly the values of observables. Recent expectation no-go theorems prove that hidden-variable theories cannot predict the expectations of observables. We prove the strongest expectation-focused no-go theorem to date. It is optimal in the sense that the natural weakenings of the assumptions and the natural strengthenings of the conclusion make the theorem fail. The literature on expectation no-go theorems strongly suggests that the expectation-focused approach is more general than the value-focused one. We establish that the expectation approach is not more general.

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.

Family-Based Benchmarking of Copy Number Variation Detection Software.

Science.gov (United States)

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition

Directory of Open Access Journals (Sweden)

Daniela Sánchez

2017-01-01

Full Text Available A grey wolf optimizer for modular neural network (MNN with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons. Nowadays, there is a great variety of approaches and new techniques within the evolutionary computing area, and these approaches and techniques have emerged to help find optimal solutions to problems or models and bioinspired algorithms are part of this area. In this work a grey wolf optimizer is proposed for the design of modular granular neural networks, and the results are compared against a genetic algorithm and a firefly algorithm in order to know which of these techniques provides better results when applied to human recognition.

Raising awareness of the hidden curriculum in veterinary medical education: a review and call for research.

Science.gov (United States)

Whitcomb, Tiffany L

2014-01-01

The hidden curriculum is characterized by information that is tacitly conveyed to and among students about the cultural and moral environment in which they find themselves. Although the hidden curriculum is often defined as a distinct entity, tacit information is conveyed to students throughout all aspects of formal and informal curricula. This unconsciously communicated knowledge has been identified across a wide spectrum of educational environments and is known to have lasting and powerful impacts, both positive and negative. Recently, medical education research on the hidden curriculum of becoming a doctor has come to the forefront as institutions struggle with inconsistencies between formal and hidden curricula that hinder the practice of patient-centered medicine. Similarly, the complex ethical questions that arise during the practice and teaching of veterinary medicine have the potential to cause disagreement between what the institution sets out to teach and what is actually learned. However, the hidden curriculum remains largely unexplored for this field. Because the hidden curriculum is retained effectively by students, elucidating its underlying messages can be a key component of program refinement. A review of recent literature about the hidden curriculum in a variety of fields, including medical education, will be used to explore potential hidden curricula in veterinary medicine and draw attention to the need for further investigation.

Nonparametric model validations for hidden Markov models with applications in financial econometrics.

Science.gov (United States)

Zhao, Zhibiao

2011-06-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

Inference with constrained hidden Markov models in PRISM

DEFF Research Database (Denmark)

Christiansen, Henning; Have, Christian Theil; Lassen, Ole Torp

2010-01-01

A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. De......_different are integrated. We experimentally validate our approach on the biologically motivated problem of global pairwise alignment.......A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference...

EVALUASI HIDDEN CURRICULUM DI SMP NEGERI BOJA, KABUPATEN KENDAL

Directory of Open Access Journals (Sweden)

Neni Lestari

2015-12-01

Full Text Available This study aimed to evaluate the implementation and impact of Hidden Curriculum, as well as the determinant factors of success and sustainability in SMPN 2 Boja Kendal. This study was an evaluative research using qualitative approach. The data collected by using observation, interviews, and documentation. Data analyzed by collecting and selecting to be deduce. Validity used triangulation data that combined the result of observation, interviews, and documentation. The results of the study were: 1 The activities of hidden curriculum development at SMPN 2 Boja Kendal, namely: flag ceremony, school environmental management, establishing and enforcing discipline, special religious worship, smiles, greetings and courtesies, exemplary, relationship among students and principal, teachers, and staff, school canteen services. 2 The impact of the hidden curriculum development was the changing of school community’s behavior being better, created clean and beautiful school environment, the improvement of public trust to the school toward their kids’ education. Development of the hidden curriculum could establish students good character and an optimal achievement as well as a good school culture. 3 Internal supporting factors including: qualified human resources, the availability of school facilities, school environment was clean and beautiful. External supporting factors occur in the form of endorsement of the parents, school committees and communities in establishing good and virtuous character for the students.

Hidden and generalized conformal symmetry of Kerr–Sen spacetimes

International Nuclear Information System (INIS)

Ghezelbash, A M; Siahaan, H M

2013-01-01

It is recently conjectured that generic non-extremal Kerr black hole could be holographically dual to a hidden conformal field theory (CFT) in two dimensions. Moreover, it is known that there are two CFT duals (pictures) to describe the charged rotating black holes which correspond to angular momentum J and electric charge Q of the black hole. Furthermore these two pictures can be incorporated by the CFT duals (general picture) that are generated by SL(2,Z) modular group. The general conformal structure can be revealed by looking at charged scalar wave equation in some appropriate values of frequency and charge. In this regard, we consider the wave equation of a charged massless scalar field in the background of Kerr–Sen black hole and show that in the ‘near region’, the wave equation can be reproduced by the Casimir operator of a local SL(2,R) L ×SL(2,R) R hidden conformal symmetry. We find the exact agreement between macroscopic and microscopic physical quantities like entropy and absorption cross section of scalars for Kerr–Sen black hole. We then find an extension of vector fields that in turn yields an extended local family of SL(2,R) L ×SL(2,R) R hidden conformal symmetry, parameterized by one parameter. For some special values of the parameter, we find a copy of SL(2,R) hidden conformal algebra for the charged Gibbons–Maeda–Garfinkle–Horowitz–Strominger black hole in the strong deflection limit. (paper)

Automatic Facial Expression Recognition and Operator Functional State

Science.gov (United States)

Blanson, Nina

2012-01-01

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

Automatic Facial Expression Recognition and Operator Functional State

Science.gov (United States)

Blanson, Nina

2011-01-01

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

Hidden solution to the μ/Bμ problem in gauge mediation

International Nuclear Information System (INIS)

Roy, Tuhin S.; Schmaltz, Martin

2008-01-01

We propose a solution to the μ/B μ problem in gauge mediation. The novel feature of our solution is that it uses dynamics of the hidden sector, which is often present in models with dynamical supersymmetry breaking. We give an explicit example model of gauge mediation where a very simple messenger sector generates both μ and B μ at one loop. The usual problem, that B μ is then too large, is solved by strong renormalization effects from the hidden sector which suppress B μ relative to μ. Our mechanism relies on an assumption about the signs of certain incalculable anomalous dimensions in the hidden sector. Making these assumptions not only allows us to solve the μ/B μ problem but also leads to a characteristic superpartner spectrum which would be a smoking gun signal for our mechanism.

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

Science.gov (United States)

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

Hidden Costs of Hospital Based Delivery from Two Tertiary Hospitals in Western Nepal.

Directory of Open Access Journals (Sweden)

Jeevan Acharya

Full Text Available Hospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs.A hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study.The total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%, clothes (9.8% and transport (7.3%. For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007, employed house head (p = 0.011, monthly family income more than 25,000 NRs (Nepalese Rupees (p = 0.014, private hospital as a place of delivery (p = 0.0001, C-section as a mode of delivery (p = 0.0001, longer duration (>5days of stay in hospital (p = 0.0001, longer distance (>15km from house to hospital (p = 0.0001 and longer travel time (>240 minutes from house to hospital (p = 0.007 showed a significant association with the higher hidden costs (>25000 NRs.Experiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time were associated with hidden costs. Hidden costs can be a

Hidden Costs of Hospital Based Delivery from Two Tertiary Hospitals in Western Nepal.

Science.gov (United States)

Acharya, Jeevan; Kaehler, Nils; Marahatta, Sujan Babu; Mishra, Shiva Raj; Subedi, Sudarshan; Adhikari, Bipin

2016-01-01

Hospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs. A hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study. The total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar) and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%), clothes (9.8%) and transport (7.3%). For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007), employed house head (p = 0.011), monthly family income more than 25,000 NRs (Nepalese Rupees) (p = 0.014), private hospital as a place of delivery (p = 0.0001), C-section as a mode of delivery (p = 0.0001), longer duration (>5days) of stay in hospital (p = 0.0001), longer distance (>15km) from house to hospital (p = 0.0001) and longer travel time (>240 minutes) from house to hospital (p = 0.007) showed a significant association with the higher hidden costs (>25000 NRs). Experiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time) were associated with hidden costs. Hidden costs can be a

Hidden-sector Spectroscopy with Gravitational Waves from Binary Neutron Stars

Science.gov (United States)

Croon, Djuna; Nelson, Ann E.; Sun, Chen; Walker, Devin G. E.; Xianyu, Zhong-Zhi

2018-05-01

We show that neutron star (NS) binaries can be ideal laboratories to probe hidden sectors with a long-range force. In particular, it is possible for gravitational wave (GW) detectors such as LIGO and Virgo to resolve the correction of waveforms from ultralight dark gauge bosons coupled to NSs. We observe that the interaction of the hidden sector affects both the GW frequency and amplitude in a way that cannot be fitted by pure gravity.

A Hidden Twelve-Dimensional SuperPoincare Symmetry In Eleven Dimensions

Energy Technology Data Exchange (ETDEWEB)

Bars, Itzhak; Deliduman, Cemsinan; Pasqua, Andrea; Zumino, Bruno

2003-12-13

First, we review a result in our previous paper, of how a ten-dimensional superparticle, taken off-shell, has a hidden eleven-dimensional superPoincare symmetry. Then, we show that the physical sector is defined by three first-class constraints which preserve the full eleven-dimensional symmetry. Applying the same concepts to the eleven dimensional superparticle, taken off-shell, we discover a hidden twelve dimensional superPoincare symmetry that governs the theory.

Practical guide to machine vision software an introduction with LabVIEW

CERN Document Server

Kwon, Kye-Si

2014-01-01

For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabli

Hidden costs, value lost: uninsurance in America

National Research Council Canada - National Science Library

Committee on the Consequences of Uninsurance

2003-01-01

Hidden Cost, Value Lost , the fifth of a series of six books on the consequences of uninsurance in the United States, illustrates some of the economic and social losses to the country of maintaining...

Hidden Markov Models for Human Genes

DEFF Research Database (Denmark)

Baldi, Pierre; Brunak, Søren; Chauvin, Yves

1997-01-01

We analyse the sequential structure of human genomic DNA by hidden Markov models. We apply models of widely different design: conventional left-right constructs and models with a built-in periodic architecture. The models are trained on segments of DNA sequences extracted such that they cover com...

The hidden costs of self-management services in the accounting activity of a company

Directory of Open Access Journals (Sweden)

Dan Ioan TOPOR

2017-05-01

Full Text Available This article addresses relevant aspects regarding the hidden costs of self-management services in the accounting area, within the accounting department of a company. With this aim, the authors conducted a study using a questionnaire, whose results were analyzed and interpreted. The hidden costs of the self-management of business accounting services observed in the accounting department of the company have been assessed and the causes of their generating sources were identified and analyzed. The debate of these hidden costs involved the treating of notions that exist in the accounting language, but are still not sufficiently explored by the specialists in the area. We also presented and analyzed the causes of the hidden costs of self-management in the accounting activity, as well as a reporting document for failures, arising from the case study. The article ends with the authors' conclusions regarding the hidden costs of self-management services in the accounting area.

Hidden Costs and the Role of Modularity

DEFF Research Database (Denmark)

Larsen, Marcus M.

2013-01-01

that the inability to effectively estimate the costs of implementing an activity in a foreign location has a negative impact on the process performance of that activity. Performance is deterred as operations are likely to be disrupted by opportunity costs and managerial responses. However, this relationship......This paper addresses estimation errors in strategic decision-making processes due to hidden costs. While previous research has investigated the antecedents of hidden costs, this paper investigates performance consequences. Using unique data on 221 offshoring implementations, it is argued...... is mitigated by the degree of modularity in the activity as it reduces the need for costly coordination in offshoring. This paper contributes to research on offshoring and strategic decision-making by emphasizing the importance of organizational design and of estimating the costs of internal organizational...

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.

Segmentation of laser range radar images using hidden Markov field models

International Nuclear Information System (INIS)

Pucar, P.

1993-01-01

Segmentation of images in the context of model based stochastic techniques is connected with high, very often unpracticle computational complexity. The objective with this thesis is to take the models used in model based image processing, simplify and use them in suboptimal, but not computationally demanding algorithms. Algorithms that are essentially one-dimensional, and their extensions to two dimensions are given. The model used in this thesis is the well known hidden Markov model. Estimation of the number of hidden states from observed data is a problem that is addressed. The state order estimation problem is of general interest and is not specifically connected to image processing. An investigation of three state order estimation techniques for hidden Markov models is given. 76 refs

Hidden costs of nuclear power

International Nuclear Information System (INIS)

England, R.W.

1979-01-01

Mr. England contends that these hidden costs add up to a figure much higher than those that appear in the electric utilities' profit and loss account - costs that are borne by Federal taxpayers, by nuclear industry workers, and by all those people who must share their environment with nuclear facilities. Costs he details are additional deaths and illnesses resulting from exposure to radiation, and the use of tax dollars to clean up the lethal garbage produced by those activities. He asserts that careless handling of uranium ore and mill tailings in past years has apparently resulted in serious public health problems in those mining communities. In another example, Mr. England states that the failure to isolate uranium tailings physically from their environment has probably contributed to an acute leukemia rate in Mesa County, Colorado. He mentions much of the technology development for power reactors being done by the Federal government, not by private reactor manufacturers - thus, again, hidden costs that do not show up in electric bills of customers. The back end of the nuclear fuel cycle as a place for Federally subsidized research and development is discussed briefly. 1 figure, 2 tables

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

Science.gov (United States)

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

Limits of performance for the model reduction problem of hidden Markov models

KAUST Repository

Kotsalis, Georgios

2015-12-15

We introduce system theoretic notions of a Hankel operator, and Hankel norm for hidden Markov models. We show how the related Hankel singular values provide lower bounds on the norm of the difference between a hidden Markov model of order n and any lower order approximant of order n̂ < n.

Limits of performance for the model reduction problem of hidden Markov models

KAUST Repository

Kotsalis, Georgios; Shamma, Jeff S.

2015-01-01

We introduce system theoretic notions of a Hankel operator, and Hankel norm for hidden Markov models. We show how the related Hankel singular values provide lower bounds on the norm of the difference between a hidden Markov model of order n and any lower order approximant of order n̂ < n.

A dynamic texture-based approach to recognition of facial actions and their temporal models.

Science.gov (United States)

Koelstra, Sander; Pantic, Maja; Patras, Ioannis

2010-11-01

In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the dynamics and the appearance in the face region of an input video are compared: an extended version of Motion History Images and a novel method based on Nonrigid Registration using Free-Form Deformations (FFDs). The extracted motion representation is used to derive motion orientation histogram descriptors in both the spatial and temporal domain. Per AU, a combination of discriminative, frame-based GentleBoost ensemble learners and dynamic, generative Hidden Markov Models detects the presence of the AU in question and its temporal segments in an input image sequence. When tested for recognition of all 27 lower and upper face AUs, occurring alone or in combination in 264 sequences from the MMI facial expression database, the proposed method achieved an average event recognition accuracy of 89.2 percent for the MHI method and 94.3 percent for the FFD method. The generalization performance of the FFD method has been tested using the Cohn-Kanade database. Finally, we also explored the performance on spontaneous expressions in the Sensitive Artificial Listener data set.

Hidden Valley Higgs Decays in the ATLAS detector

CERN Document Server

Ciapetti, G

2009-01-01

A number of extensions of the Standard Model result in particles that are neutral, weakly-coupled and have macroscopic decay lengths that can be comparable with LHC detector dimensions. These particles represent, from an experimental point of view, a challenge both for the trigger and for the reconstruction capabilities of the ATLAS apparatus. For the purpose of exploring the challenges to the trigger posed by long-lived particles, the Hidden Valley scenario serves as an excellent setting. In this note we present the results of a first study of ATLAS detector performance for some Hidden Valley processes with long-lived, neutral states that decay throughout the detector volume to multi heavy-flavor jets, mainly b-bbar.

The hidden epidemic: confronting sexually transmitted diseases

National Research Council Canada - National Science Library

Eng, Thomas R; Butler, William T

.... In addition, STDs increase the risk of HIV transmission. The Hidden Epidemic examines the scope of sexually transmitted infections in the United States and provides a critical assessment of the nation's response to this public health crisis...

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...

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

Science.gov (United States)

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

2006-06-01

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

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.

Dimensional reduction in field theory and hidden symmetries in extended supergravity

International Nuclear Information System (INIS)

Kremmer, E.

1985-01-01

Dimensional reduction in field theories is discussed both in theories which do not include gravity and in gravity theories. In particular, 11-dimensional supergravity and its reduction to 4 dimensions is considered. Hidden symmetries of supergravity with N=8 in 4 dimensions, global E 7 and local SU(8)-invariances in particular are detected. The hidden symmmetries permit to interpret geometrically the scalar fields

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

Science.gov (United States)

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

2002-01-01

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

Multimodal emotion recognition as assessment for learning in a game-based communication skills training

NARCIS (Netherlands)

Nadolski, Rob; Bahreini, Kiavash; Westera, Wim

2014-01-01

This paper presentation describes how our FILTWAM software artifacts for face and voice emotion recognition will be used for assessing learners' progress and providing adequate feedback in an online game-based communication skills training. This constitutes an example of in-game assessment for

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.

Experimental search for solar hidden photons in the eV energy range using kinetic mixing with photons

International Nuclear Information System (INIS)

Mizumoto, T.; Ohta, R.; Horie, T.; Suzuki, J.; Minowa, M.; Inoue, Y.

2013-01-01

We have searched for solar hidden photons in the eV energy range using a dedicated hidden photon detector. The detector consisted of a parabolic mirror with a diameter of 500 mm and a focal length of 1007 mm installed in a vacuum chamber, and a photomultiplier tube at its focal point. The detector was attached to the Tokyo axion helioscope, Sumico which has a mechanism to track the sun. From the result of the measurement, we found no evidence for the existence of hidden photons and set a limit on the photon-hidden photon mixing parameter χ depending on the hidden photon mass m γ'

Sharp Contradiction for Local-Hidden-State Model in Quantum Steering

Science.gov (United States)

Chen, Jing-Ling; Su, Hong-Yi; Xu, Zhen-Peng; Pati, Arun Kumar

2016-08-01

In quantum theory, no-go theorems are important as they rule out the existence of a particular physical model under consideration. For instance, the Greenberger-Horne-Zeilinger (GHZ) theorem serves as a no-go theorem for the nonexistence of local hidden variable models by presenting a full contradiction for the multipartite GHZ states. However, the elegant GHZ argument for Bell’s nonlocality does not go through for bipartite Einstein-Podolsky-Rosen (EPR) state. Recent study on quantum nonlocality has shown that the more precise description of EPR’s original scenario is “steering”, i.e., the nonexistence of local hidden state models. Here, we present a simple GHZ-like contradiction for any bipartite pure entangled state, thus proving a no-go theorem for the nonexistence of local hidden state models in the EPR paradox. This also indicates that the very simple steering paradox presented here is indeed the closest form to the original spirit of the EPR paradox.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

Science.gov (United States)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

Searching for confining hidden valleys at LHCb, ATLAS, and CMS

Science.gov (United States)

Pierce, Aaron; Shakya, Bibhushan; Tsai, Yuhsin; Zhao, Yue

2018-05-01

We explore strategies for probing hidden valley scenarios exhibiting confinement. Such scenarios lead to a moderate multiplicity of light hidden hadrons for generic showering and hadronization similar to QCD. Their decays are typically soft and displaced, making them challenging to probe with traditional LHC searches. We show that the low trigger requirements and excellent track and vertex reconstruction at LHCb provide a favorable environment to search for such signals. We propose novel search strategies in both muonic and hadronic channels. We also study existing ATLAS and CMS searches and compare them with our proposals at LHCb. We find that the reach at LHCb is generically better in the parameter space we consider here, even with optimistic background estimations for ATLAS and CMS searches. We discuss potential modifications at ATLAS and CMS that might make these experiments competitive with the LHCb reach. Our proposed searches can be applied to general hidden valley models as well as exotic Higgs boson decays, such as in twin Higgs models.

Single-hidden-layer feed-forward quantum neural network based on Grover learning.

Science.gov (United States)

Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

2013-09-01

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Eigenvector Weighting Function in Face Recognition

Directory of Open Access Journals (Sweden)

Pang Ying Han

2011-01-01

Full Text Available Graph-based subspace learning is a class of dimensionality reduction technique in face recognition. The technique reveals the local manifold structure of face data that hidden in the image space via a linear projection. However, the real world face data may be too complex to measure due to both external imaging noises and the intra-class variations of the face images. Hence, features which are extracted by the graph-based technique could be noisy. An appropriate weight should be imposed to the data features for better data discrimination. In this paper, a piecewise weighting function, known as Eigenvector Weighting Function (EWF, is proposed and implemented in two graph based subspace learning techniques, namely Locality Preserving Projection and Neighbourhood Preserving Embedding. Specifically, the computed projection subspace of the learning approach is decomposed into three partitions: a subspace due to intra-class variations, an intrinsic face subspace, and a subspace which is attributed to imaging noises. Projected data features are weighted differently in these subspaces to emphasize the intrinsic face subspace while penalizing the other two subspaces. Experiments on FERET and FRGC databases are conducted to show the promising performance of the proposed technique.

Main real time software for high-energy physics experiments

International Nuclear Information System (INIS)

Tikhonov, A.N.

1985-01-01

The general problems of organization of software complexes, as well as development of typical algorithms and packages of applied programs for real time systems used in experiments with charged particle accelerators are discussed. It is noted that numerous qualitatively different real time tasks are solved by parallel programming of the processes of data acquisition, equipment control, data exchange with remote terminals, data express processing and accumulation, operator's instruction interpretation, generation and buffering of resulting files for data output and information processing which is realized on the basis of multicomputer system utilization. Further development of software for experiments is associated with improving the algorithms for automatic recognition and analysis of events with complex topology and standardization of applied program packages

Nurture Hidden Talents: Transform School Culture into One That Values Teacher Expertise

Science.gov (United States)

Zimmerman, Diane P.

2014-01-01

This article looks into the school culture where teacher expertise is often hidden and underused. While the media-rich culture places a high value on talent, the irony is that talent is underrated in most schools, and educators often remain silent about their hidden talents. Many school cultures are not conducive to dialogue that supports displays…

Real Time Recognition Of Speakers From Internet Audio Stream

Directory of Open Access Journals (Sweden)

Weychan Radoslaw

2015-09-01

Full Text Available In this paper we present an automatic speaker recognition technique with the use of the Internet radio lossy (encoded speech signal streams. We show an influence of the audio encoder (e.g., bitrate on the speaker model quality. The model of each speaker was calculated with the use of the Gaussian mixture model (GMM approach. Both the speaker recognition and the further analysis were realized with the use of short utterances to facilitate real time processing. The neighborhoods of the speaker models were analyzed with the use of the ISOMAP algorithm. The experiments were based on four 1-hour public debates with 7–8 speakers (including the moderator, acquired from the Polish radio Internet services. The presented software was developed with the MATLAB environment.

Multimodal Emotion Recognition for Assessment of Learning in a Game-Based Communication Skills Training

NARCIS (Netherlands)

Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2015-01-01

This paper describes how our FILTWAM software artifacts for face and voice emotion recognition will be used for assessing learners' progress and providing adequate feedback in an online game-based communication skills training. This constitutes an example of in-game assessment for mainly formative

Long memory of financial time series and hidden Markov models with time-varying parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

Hidden Markov models are often used to capture stylized facts of daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior for the ability to reproduce the stylized...... facts have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time-varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared...... daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step predictions....

Photoacoustic imaging of hidden dental caries by using a bundle of hollow optical fibers

Science.gov (United States)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2018-02-01

Photoacoustic imaging system using a bundle of hollow-optical fibers to detect hidden dental caries is proposed. Firstly, we fabricated a hidden caries model with a brown pigment simulating a common color of caries lesion. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating Nd:YAG laser light with a 532 nm wavelength to occlusal surface of model tooth. We calculated by Fourier transform and found that the waveform from the carious part provides frequency components of approximately from 0.5 to 1.2 MHz. Then a photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for clinical applications. From intensity map of frequency components in 0.5-1.2 MHz, photoacoustic images of hidden caries in the simulated samples were successfully obtained.

An intelligent software approach to ultrasonic flaw classification in weldments

International Nuclear Information System (INIS)

Song, Sung Jin; Kim, Hak Joon; Lee, Hyun

1997-01-01

Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress on this methodology, it has not been widely used in practical ultrasonic inspection of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments using various tools in artificial intelligence such as neural networks. This software shows excellent performances in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks.

Segment-based acoustic models for continuous speech recognition

Science.gov (United States)

Ostendorf, Mari; Rohlicek, J. R.

1993-07-01

This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition, by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which are more costly than traditional approaches because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the fourth quarter of the project, we have completed the following: (1) ported our recognition system to the Wall Street Journal task, a standard task in the ARPA community; (2) developed an initial dependency-tree model of intra-utterance observation correlation; and (3) implemented baseline language model estimation software. Our initial results on the Wall Street Journal task are quite good and represent significantly improved performance over most HMM systems reporting on the Nov. 1992 5k vocabulary test set.

Hidden loss

DEFF Research Database (Denmark)

Kieffer-Kristensen, Rikke; Johansen, Karen Lise Gaardsvig

2013-01-01

to participate. RESULTS: All children were affected by their parents' ABI and the altered family situation. The children's expressions led the authors to identify six themes, including fear of losing the parent, distress and estrangement, chores and responsibilities, hidden loss, coping and support. The main......PRIMARY OBJECTIVE: The purpose of this study was to listen to and learn from children showing high levels of post-traumatic stress symptoms after parental acquired brain injury (ABI), in order to achieve an in-depth understanding of the difficulties the children face in their everyday lives...... finding indicates that the children experienced numerous losses, many of which were often suppressed or neglected by the children to protect the ill parents. CONCLUSIONS: The findings indicated that the children seemed to make a special effort to hide their feelings of loss and grief in order to protect...

Hidden Markov models: the best models for forager movements?

Science.gov (United States)

Joo, Rocio; Bertrand, Sophie; Tam, Jorge; Fablet, Ronan

2013-01-01

One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs). We propose here to evaluate two sets of alternative and state-of-the-art modelling approaches. First, we consider hidden semi-Markov models (HSMMs). They may better represent the behavioural dynamics of foragers since they explicitly model the duration of the behavioural modes. Second, we consider discriminative models which state the inference of behavioural modes as a classification issue, and may take better advantage of multivariate and non linear combinations of movement pattern descriptors. For this work, we use a dataset of >200 trips from human foragers, Peruvian fishermen targeting anchovy. Their movements were recorded through a Vessel Monitoring System (∼1 record per hour), while their behavioural modes (fishing, searching and cruising) were reported by on-board observers. We compare the efficiency of hidden Markov, hidden semi-Markov, and three discriminative models (random forests, artificial neural networks and support vector machines) for inferring the fishermen behavioural modes, using a cross-validation procedure. HSMMs show the highest accuracy (80%), significantly outperforming HMMs and discriminative models. Simulations show that data with higher temporal resolution, HSMMs reach nearly 100% of accuracy. Our results demonstrate to what extent the sequential nature of movement is critical for accurately inferring behavioural modes from a trajectory and we strongly recommend the use of HSMMs for such purpose. In addition, this work opens perspectives on the use of hybrid HSMM-discriminative models, where a discriminative setting for the observation process of HSMMs could greatly improve inference performance.

Hidden Markov models: the best models for forager movements?

Directory of Open Access Journals (Sweden)

Rocio Joo

Full Text Available One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs. We propose here to evaluate two sets of alternative and state-of-the-art modelling approaches. First, we consider hidden semi-Markov models (HSMMs. They may better represent the behavioural dynamics of foragers since they explicitly model the duration of the behavioural modes. Second, we consider discriminative models which state the inference of behavioural modes as a classification issue, and may take better advantage of multivariate and non linear combinations of movement pattern descriptors. For this work, we use a dataset of >200 trips from human foragers, Peruvian fishermen targeting anchovy. Their movements were recorded through a Vessel Monitoring System (∼1 record per hour, while their behavioural modes (fishing, searching and cruising were reported by on-board observers. We compare the efficiency of hidden Markov, hidden semi-Markov, and three discriminative models (random forests, artificial neural networks and support vector machines for inferring the fishermen behavioural modes, using a cross-validation procedure. HSMMs show the highest accuracy (80%, significantly outperforming HMMs and discriminative models. Simulations show that data with higher temporal resolution, HSMMs reach nearly 100% of accuracy. Our results demonstrate to what extent the sequential nature of movement is critical for accurately inferring behavioural modes from a trajectory and we strongly recommend the use of HSMMs for such purpose. In addition, this work opens perspectives on the use of hybrid HSMM-discriminative models, where a discriminative setting for the observation process of HSMMs could greatly improve inference performance.

Chimpanzees (Pan troglodytes) use markers to monitor the movement of a hidden item.

Science.gov (United States)

Beran, Michael J; Beran, Mary M; Menzel, Charles R

2005-10-01

Four chimpanzees (Pan troglodytes) monitored the movement of hidden items in arrays of opaque cups. A chocolate candy was hidden in an array of four cups and temporarily presented paper markers indicated the location of the candy (which otherwise was not visible). These markers were either non-symbolic or symbolic (lexigram) stimuli that in other contexts acted as a label for the hidden candy, and the array was either rotated 180 degrees after the marker was removed or the array remained in the same location. For three of four chimpanzees, performance was better than chance in all conditions and there was no effect of the type of marker. These experiments indicate that chimpanzees can track the movement of a hidden item in an array of identical cups even when they never see the item itself, but only see a temporarily presented marker for the location of that item. However, there was no benefit to the use of symbolic as opposed to non-symbolic stimuli in this performance.

Significance of hidden advertising of the media business models in Latvia

OpenAIRE

Rožukalne, Anda

2012-01-01

Since 2002 parliamentary and municipal elections in Latvia, media content researches have shown a considerable amount of hidden advertising: media publish information that is paid-for, yet not identified as advertising, assigning this information with the qualities of independent content, therefore misleading its audience. In order to analyze this practice, a research was commissioned to find out why Latvian media publish hidden advertising, what is the force behind this practice, who are com...

Enhanced axion-photon coupling in GUT with hidden photon

Science.gov (United States)

Daido, Ryuji; Takahashi, Fuminobu; Yokozaki, Norimi

2018-05-01

We show that the axion coupling to photons can be enhanced in simple models with a single Peccei-Quinn field, if the gauge coupling unification is realized by a large kinetic mixing χ = O (0.1) between hypercharge and unbroken hidden U(1)H. The key observation is that the U(1)H gauge coupling should be rather strong to induce such large kinetic mixing, leading to enhanced contributions of hidden matter fields to the electromagnetic anomaly. We find that the axion-photon coupling is enhanced by about a factor of 10-100 with respect to the GUT-axion models with E / N = 8 / 3.

Multistability and hidden attractors in a multilevel DC/DC converter

DEFF Research Database (Denmark)

Zhusubaliyev, Zhanybai T.; Mosekilde, Erik

2015-01-01

An attracting periodic, quasiperiodic or chaotic set of a smooth, autonomous system may be referred to as a "hidden attractor" if its basin of attraction does not overlap with the neighborhood of an unstable equilibrium point. Historically, this condition has implied that the basin of attraction...... produce complicated structures of attracting and repelling states organized around the basic switching cycle. This leads us to suggest the existence of hidden attractors in such systems as well. In this case, the condition will be that the basin of attraction does not overlap with the fixed point...

Exploring inequality violations by classical hidden variables numerically

International Nuclear Information System (INIS)

Vongehr, Sascha

2013-01-01

There are increasingly suggestions for computer simulations of quantum statistics which try to violate Bell type inequalities via classical, common cause correlations. The Clauser–Horne–Shimony–Holt (CHSH) inequality is very robust. However, we argue that with the Einstein–Podolsky–Rosen setup, the CHSH is inferior to the Bell inequality, although and because the latter must assume anti-correlation of entangled photon singlet states. We simulate how often quantum behavior violates both inequalities, depending on the number of photons. Violating Bell 99% of the time is argued to be an ideal benchmark. We present hidden variables that violate the Bell and CHSH inequalities with 50% probability, and ones which violate Bell 85% of the time when missing 13% anti-correlation. We discuss how to present the quantum correlations to a wide audience and conclude that, when defending against claims of hidden classicality, one should demand numerical simulations and insist on anti-correlation and the full amount of Bell violation. -- Highlights: •The widely assumed superiority of the CHSH fails in the EPR problem. •We simulate Bell type inequalities behavior depending on the number of photons. •The core of Bell’s theorem in the EPR setup is introduced in a simple way understandable to a wide audience. •We present hidden variables that violate both inequalities with 50% probability. •Algorithms have been supplied in form of Mathematica programs

Mass spectra of hidden-charm molecular pentaquarks states

International Nuclear Information System (INIS)

Patel, Smruti; Vinodkumar, P.C.

2016-01-01

Very recently, the LHCb Collaboration has reported two hidden-charmed resonances P_c(4380) and P_c(4450) consistent with pentaquark states in the Λ_b"0 → K"-J/Ψp process with masses (widths) (4380 ±8 ± 29) MeV ((205 ±18 ± 86) MeV) and (4449.8 ±1.7 ± 2.5) MeV ((39 ±5 ±19) MeV), respectively. The observation of the P_c states has aroused the theorist's strong interest in the hidden-charm pentaquark states. They have been studied in various frameworks, such as the molecule-like pentaquark states, the diquark-diquark-antiquark type pentaquark states, the diquark-triquark type pentaquark states, re-scattering effects, etc. An identification of pentaquark states as exotic hadron has been one of the long standing problems in the physics of strong interaction and quantum chromodynamics (QCD). A decade ago lots of discussion were made about pentaquarks states but due to lack of further experimental evidences the study of pentaquarks have been almost gone in the darkness. But, recent remarkable observation of two resonances i.e. P_c(4380) and P_c(4450) with hidden charm and the minimal quark content cc-baruud provided new impact for studies of pentaquark states and opens a new window to study the exotic hadronic matter

Hidden supersymmetry and large N

International Nuclear Information System (INIS)

Alfaro, J.

1988-01-01

In this paper we present a new method to deal with the leading order in the large-N expansion of a quantum field theory. The method uses explicitly the hidden supersymmetry that is present in the path-integral formulation of a stochastic process. In addition to this we derive a new relation that is valid in the leading order of the large-N expansion of the hermitian-matrix model for any spacetime dimension. (orig.)

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments

Science.gov (United States)

Misra, Archan; Cook, Diane

2016-01-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional ‘hidden’ context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions. PMID:27042240

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

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

Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

2016-01-01

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....

Hidden Broad-line Regions in Seyfert 2 Galaxies: From the Spectropolarimetric Perspective

International Nuclear Information System (INIS)

Du, Pu; Wang, Jian-Min; Zhang, Zhi-Xiang

2017-01-01

The hidden broad-line regions (BLRs) in Seyfert 2 galaxies, which display broad emission lines (BELs) in their polarized spectra, are a key piece of evidence in support of the unified model for active galactic nuclei (AGNs). However, the detailed kinematics and geometry of hidden BLRs are still not fully understood. The virial factor obtained from reverberation mapping of type 1 AGNs may be a useful diagnostic of the nature of hidden BLRs in type 2 objects. In order to understand the hidden BLRs, we compile six type 2 objects from the literature with polarized BELs and dynamical measurements of black hole masses. All of them contain pseudobulges. We estimate their virial factors, and find the average value is 0.60 and the standard deviation is 0.69, which agree well with the value of type 1 AGNs with pseudobulges. This study demonstrates that (1) the geometry and kinematics of BLR are similar in type 1 and type 2 AGNs of the same bulge type (pseudobulges), and (2) the small values of virial factors in Seyfert 2 galaxies suggest that, similar to type 1 AGNs, BLRs tend to be very thick disks in type 2 objects.

Finite-time Lyapunov dimension and hidden attractor of the Rabinovich system

OpenAIRE

Kuznetsov, N. V.; Leonov, G. A.; Mokaev, T. N.; Prasad, A.; Shrimali, M. D.

2015-01-01

The Rabinovich system, describing the process of interaction between waves in plasma, is considered. It is shown that the Rabinovich system can exhibit a hidden attractor in the case of multistability as well as a classical self-excited attractor. The hidden attractor in this system can be localized by analytical/numerical methods based on the continuation and perpetual points. The concept of finite-time Lyapunov dimension is developed for numerical study of the dimension of attractors. A con...

Intense gamma-ray lines from hidden vector dark matter decay

International Nuclear Information System (INIS)

Arina, Chiara; Hambye, Thomas

2009-12-01

Scenarios with hidden, spontaneously broken, non-abelian gauge groups contain a natural dark matter candidate, the hidden vector, whose longevity is due to an accidental custodial symmetry in the renormalizable Lagrangian. Nevertheless, non-renormalizable dimension six operators break the custodial symmetry and induce the decay of the dark matter particle at cosmological times. We discuss in this paper the cosmic ray signatures of this scenario and we show that the decay of hidden vector dark matter particles generically produce an intense gamma ray line which could be observed by the Fermi-LAT experiment, if the scale of custodial symmetry breaking is close to the Grand Unification scale. This gamma line proceeds directly from a tree level dark matter 2-body decay in association with a Higgs boson. Within this model we also perform a determination of the relic density constraints taking into account the dark matter annihilation processes with one dark matter particle in the final state. The corresponding direct detection rates can be easily of order the current experimental sensitivities. (orig.)

Intense gamma-ray lines from hidden vector dark matter decay

Energy Technology Data Exchange (ETDEWEB)

Arina, Chiara; Hambye, Thomas [Universite Libre de Bruxelles (Belgium). Service de Physique Theorique; Ibarra, Alejandro [Technische Univ. Muenchen, Garching (Germany). Physik-Department; Weniger, Christoph [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2009-12-15

Scenarios with hidden, spontaneously broken, non-abelian gauge groups contain a natural dark matter candidate, the hidden vector, whose longevity is due to an accidental custodial symmetry in the renormalizable Lagrangian. Nevertheless, non-renormalizable dimension six operators break the custodial symmetry and induce the decay of the dark matter particle at cosmological times. We discuss in this paper the cosmic ray signatures of this scenario and we show that the decay of hidden vector dark matter particles generically produce an intense gamma ray line which could be observed by the Fermi-LAT experiment, if the scale of custodial symmetry breaking is close to the Grand Unification scale. This gamma line proceeds directly from a tree level dark matter 2-body decay in association with a Higgs boson. Within this model we also perform a determination of the relic density constraints taking into account the dark matter annihilation processes with one dark matter particle in the final state. The corresponding direct detection rates can be easily of order the current experimental sensitivities. (orig.)

Intense gamma-ray lines from hidden vector dark matter decay

International Nuclear Information System (INIS)

Arina, Chiara; Hambye, Thomas; Ibarra, Alejandro; Weniger, Christoph

2010-01-01

Scenarios with hidden, spontaneously broken, non-abelian gauge groups contain a natural dark matter candidate, the hidden vector, whose longevity is due to an accidental custodial symmetry in the renormalizable Lagrangian. Nevertheless, non-renormalizable dimension six operators break the custodial symmetry and induce the decay of the dark matter particle at cosmological times. We discuss in this paper the cosmic ray signatures of this scenario and we show that the decay of hidden vector dark matter particles generically produce an intense gamma ray line which could be observed by the Fermi-LAT experiment, if the scale of custodial symmetry breaking is close to the Grand Unification scale. This gamma line proceeds directly from a tree level dark matter 2-body decay in association with a Higgs boson. Within this model we also perform a determination of the relic density constraints taking into account the dark matter annihilation processes with one dark matter particle in the final state. The corresponding direct detection rates can be easily of order the current experimental sensitivities

USING CONVOLUTIONAL NEURAL NETWORKS FOR LICENSE PLATES RECOGNITION. ADVANTAGES AND DISADVANTAGES IN COMPARISON WITH TEMPLATE-BASED METHOD

OpenAIRE

Mikhalevich Y. S.; Tkachenko V. V.

2016-01-01

Car license plates recognition problem is one of the typical tasks of computer vision. Video surveillance software usually provides license plates recognition function. Meanwhile, there are many approaches to solve this problem, where template-based methods are the most common. Such methods providing predictable and short enough execution time, and little percent of mistakes. However, such methods are far less effective in case there is a need to recognize car’s license plate, which may be lo...

Theoretical analysis of hidden photon searches in high-precision experiments

International Nuclear Information System (INIS)

Beranek, Tobias

2014-01-01

Although the Standard Model of particle physics (SM) provides an extremely successful description of the ordinary matter, one knows from astronomical observations that it accounts only for around 5% of the total energy density of the Universe, whereas around 30% are contributed by the dark matter. Motivated by anomalies in cosmic ray observations and by attempts to solve questions of the SM like the (g-2) μ discrepancy, proposed U(1) extensions of the Standard Model gauge group SU(3) x SU(2) x U(1) have raised attention in recent years. In the considered U(1) extensions a new, light messenger particle γ', the hidden photon, couples to the hidden sector as well as to the electromagnetic current of the SM by kinetic mixing. This allows for a search for this particle in laboratory experiments exploring the electromagnetic interaction. Various experimental programs have been started to search for the γ' boson, such as in electron-scattering experiments, which are a versatile tool to explore various physics phenomena. One approach is the dedicated search in fixed-target experiments at modest energies as performed at MAMI or at JLAB. In these experiments the scattering of an electron beam off a hadronic target e→e(A,Z)l + l - is investigated and a search for a very narrow resonance in the invariant mass distribution of the l + l - pair is performed. This requires an accurate understanding of the theoretical basis of the underlying processes. For this purpose it is demonstrated in the first part of this work, in which way the hidden photon can be motivated from existing puzzles encountered at the precision frontier of the SM. The main part of this thesis deals with the analysis of the theoretical framework for electron scattering fixed-target experiments searching for hidden photons. As a first step, the cross section for the bremsstrahlung emission of hidden photons in such experiments is studied. Based on these results, the applicability of the Weizsaecker

Sterile neutrino, hidden dark matter and their cosmological signatures

International Nuclear Information System (INIS)

Das, Subinoy

2012-01-01

Though thermal dark matter has been the central idea behind the dark matter candidates, it is highly possible that dark matter of the universe is non-thermal in origin or it might be in thermal contact with some hidden or dark sector but not with standard model. Here we explore the cosmological bounds as well as the signatures on two types of non-thermal dark matter candidates. First we discuss a hidden dark matter with almost no interaction (or very feeble) with standard model particles so that it is not in thermal contact with visible sector but we assume it is thermalized with in a hidden sector due to some interaction. While encompassing the standard cold WIMP scenario, we do not require the freeze-out process to be non-relativistic. Rather, freeze-out may also occur when dark matter particles are semi-relativistic or relativistic. Especially we focus on the warm dark matter scenario in this set up and find the constraints on the warm dark matter mass, cross-section and hidden to visible sector temperature ratio which accounts for the observed dark-matter density, satisfies the Tremaine-Gunn bound on dark-matter phase space density and has a free-streaming length consistent with cosmological constraints on the matter power spectrum. Our method can also be applied to keV sterile neutrino dark matter which is not thermalized with standard model but is thermalized with in a dark sector. The second part of this proceeding focuses on an exotic dark matter candidate which arises from the existence of eV mass sterile neutrino through a late phase transition. Due to existence of a strong scalar force the light sterile states get trapped into stable degenerate micro nuggets. We find that its signature in matter power spectra is close to a warm dark matter candidate.

Reflowing-driven paragraph recognition for electronic books in PDF

Science.gov (United States)

Fang, Jing; Tang, Zhi; Gao, Liangcai

2011-01-01

When reading electronic books on handheld devices, content sometimes should be reflowed and recomposed to adapt for small-screen mobile devices. According to people's reading practice, it is reasonable to reflow the text content based on paragraphs. Hence, this paper addresses the requirement and proposes a set of novel methods on paragraph recognition for electronic books in PDF. The proposed methods consist of three steps, namely, physical structure analysis, paragraph segmentation, and reading order detection. We make use of locally ordered property of PDF documents and layout style of books to improve traditional page recognition results. In addition, we employ the optimal matching of Bipartite Graph technology to detect paragraphs' reading order. Experiments show that our methods achieve high accuracy. It is noteworthy that, the research has been applied in a commercial software package for Chinese E-book production.

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

Science.gov (United States)

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

2004-11-01

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

Spatial pattern recognition of seismic events in South West Colombia

Science.gov (United States)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

Exposing the Hidden-Web Induced by Ajax

NARCIS (Netherlands)

Mesbah, A.; Van Deursen, A.

2008-01-01

AJAX is a very promising approach for improving rich interactivity and responsiveness of web applications. At the same time, AJAX techniques increase the totality of the hidden web by shattering the metaphor of a web ‘page’ upon which general search engines are based. This paper describes a

K­MEANS CLUSTERING FOR HIDDEN MARKOV MODEL

NARCIS (Netherlands)

Perrone, M.P.; Connell, S.D.

2004-01-01

An unsupervised k­means clustering algorithm for hidden Markov models is described and applied to the task of generating subclass models for individual handwritten character classes. The algorithm is compared to a related clustering method and shown to give a relative change in the error rate of as

Algorithms for a parallel implementation of Hidden Markov Models with a small state space

DEFF Research Database (Denmark)

Nielsen, Jesper; Sand, Andreas

2011-01-01

Two of the most important algorithms for Hidden Markov Models are the forward and the Viterbi algorithms. We show how formulating these using linear algebra naturally lends itself to parallelization. Although the obtained algorithms are slow for Hidden Markov Models with large state spaces...

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

Science.gov (United States)

2010-01-01

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

Testing string vacua in the lab. From a hidden CMB to dark forces in flux compactifications

Energy Technology Data Exchange (ETDEWEB)

Cicoli, Michele; Goodsell, Mark; Ringwald, Andreas [Deutsches Elektronen-Synchrotron DESY, Hamburg (Germany). Theory Group; Jaeckel, Joerg [Durham Univ. (United Kingdom). Inst. for Particle Physics Phenomenolgy

2011-03-15

We perform a detailed analysis of the phenomenological properties of hidden Abelian gauge bosons with a kinetic mixing with the ordinary photon within type IIB flux compactifications. We study the interplay between moduli stabilisation and the Green-Schwarz mechanism that gives mass to the hidden photon paying particular attention to the role of D-terms. We present two generic classes of explicit Calabi-Yau examples with an isotropic and an anisotropic shape of the extra dimensions showing how the last case turns out to be very promising to make contact with current experiments. In fact, anisotropic compactifications lead naturally to a GeV-scale hidden photon (''dark forces'' that can be searched for in beam dump experiments) for an intermediate string scale; or even to an meV-scale hidden photon (which could lead to a ''hidden CMB'' and can be tested by light-shining-through-a-wall experiments) in the case of TeV-scale strings. (orig.)

Has Bell's inequality a general meaning for hidden-variable theories

International Nuclear Information System (INIS)

Lochak, G.

1976-01-01

The proof given by J. S. Bell of an inequality between mean values of measurement results which, according to him, would be characteristic of any local hidden-parameter theory, is analyzed. It is shown that Bell's proof is based upon a hypothesis already contained in von Neumann's famous theorem: It consists in the admission that hidden values of parameters must obey the same statistical laws as observed values. This hypothesis contradicts in advance well known and certainly correct statistical relations in measurement results: one must therefore reject the type of theory considered by Bell, and his inequality has no general meaning

Problems in software development for nuclear robotics

International Nuclear Information System (INIS)

Shinohara, Yoshikuni

1986-01-01

Major technical problems in developing softwares for intelligent robots for future nuclear applications are explained briefly. In order that a robot can perform various kinds of complex works, it must be equipped with a high level of artificial intelligence which includes sensing functions such as visiual, auditory, tactile, proximity sensing, cognitive functions such as recognition of objects and understanding of working environment, decision-making functions such as work planning and control functions such as manipulator and locomotion controls. A large amount of various kinds of signals and informations must be processed with a high speed for an integrated control of these functions. It will be desirable that the computer program for controlling a robot which must run in a real-time will have a functionally hierarchical and distributed structure from the view point of software development. Parallel processing will be required from the view point of computation time. (author)

Swallowing sound detection using hidden markov modeling of recurrence plot features