WorldWideScience

Sample records for seed-target recognition step

  1. DEVELOPMENT OF HOLE RECOGNITION SYSTEM FROM STEP FILE

    Directory of Open Access Journals (Sweden)

    C. F. Tan

    2017-11-01

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

  2. Recognition of knowledge – A step towards optimization of education

    Directory of Open Access Journals (Sweden)

    Vanda Rebolj

    2011-03-01

    In her presentation of the knowledge recognition procedures, the author relies on constructivist theories on knowledge and highlights the importance of the achieved levels of knowledge, paying equal attention to the low levels (skills, higher levels and the highest levels (problem­solving, none of which should be omitted in the assessment and recognition procedures. The author then presents the experience in knowledge recognition gained in the last five years by several colleges providing part­time studies, starting with a course in accounting and proceeding with other programmes. It is essential that knowledge recognition should not be pushed into the domain of experts or become an administrative procedure; it must remain part of the regular teaching procedure and under control of the teacher. This requires implementation of appropriate teacher training. Despite the fact that the recognition procedures developed so far have proved to be valid and have gained on credibility, numerous new research issues are being raised in this field.

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  4. Step detection and activity recognition accuracy of seven physical activity monitors.

    Directory of Open Access Journals (Sweden)

    Fabio A Storm

    Full Text Available The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts, Up (Jawbone, One (Fitbit, ActivPAL (PAL Technologies Ltd., Nike+ Fuelband (Nike Inc., Tractivity (Kineteks Corp. and Sensewear Armband Mini (Bodymedia. Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration. The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications.

  5. Step detection and activity recognition accuracy of seven physical activity monitors.

    Science.gov (United States)

    Storm, Fabio A; Heller, Ben W; Mazzà, Claudia

    2015-01-01

    The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts), Up (Jawbone), One (Fitbit), ActivPAL (PAL Technologies Ltd.), Nike+ Fuelband (Nike Inc.), Tractivity (Kineteks Corp.) and Sensewear Armband Mini (Bodymedia). Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc) were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration. The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications.

  6. A two-step recognition of signal sequences determines the translocation efficiency of proteins.

    Science.gov (United States)

    Belin, D; Bost, S; Vassalli, J D; Strub, K

    1996-02-01

    The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated derivatives thereof, ovalbumin and preprolactin) were found to have the differential activities in the two events. For example, the mPAI-2 signal sequence first binds SRP with moderate efficiency and secondly promotes the vectorial transport of only a fraction of the SRP-bound nascent chains. Our results provide evidence that the translocation efficiency of proteins can be controlled by the recognition of their signal sequences at two steps: during SRP-mediated targeting and during formation of a committed translocation complex. This second recognition may occur at several time points during the insertion/translocation step. In conclusion, signal sequences have a more complex structure than previously anticipated, allowing for multiple and independent interactions with the translocation machinery.

  7. Mother Vocal Recognition in Antarctic Fur Seal Arctocephalus gazella Pups: A Two-Step Process.

    Directory of Open Access Journals (Sweden)

    Thierry Aubin

    Full Text Available In otariids, mother's recognition by pups is essential to their survival since females nurse exclusively their own young and can be very aggressive towards non-kin. Antarctic fur seal, Arctocephalus gazella, come ashore to breed and form dense colonies. During the 4-month lactation period, females alternate foraging trips at sea with suckling period ashore. On each return to the colony, females and pups first use vocalizations to find each other among several hundred conspecifics and olfaction is used as a final check. Such vocal identification has to be highly efficient. In this present study, we investigated the components of the individual vocal signature used by pups to identify their mothers by performing playback experiments on pups with synthetic signals. We thus tested the efficiency of this individual vocal signature by performing propagation tests and by testing pups at different playback distances. Pups use both amplitude and frequency modulations to identify their mother's voice, as well as the energy spectrum. Propagation tests showed that frequency modulations propagated reliably up to 64m, whereas amplitude modulations and spectral content greatly were highly degraded for distances over 8m. Playback on pups at different distances suggested that the individual identification is a two-step process: at long range, pups identified first the frequency modulation pattern of their mother's calls, and other components of the vocal signature at closer range. The individual vocal recognition system developed by Antarctic fur seals is well adapted to face the main constraint of finding kin in a crowd.

  8. Two-step interrogation then recognition of DNA binding site by Integration Host Factor: an architectural DNA-bending protein.

    Science.gov (United States)

    Velmurugu, Yogambigai; Vivas, Paula; Connolly, Mitchell; Kuznetsov, Serguei V; Rice, Phoebe A; Ansari, Anjum

    2018-02-28

    The dynamics and mechanism of how site-specific DNA-bending proteins initially interrogate potential binding sites prior to recognition have remained elusive for most systems. Here we present these dynamics for Integration Host factor (IHF), a nucleoid-associated architectural protein, using a μs-resolved T-jump approach. Our studies show two distinct DNA-bending steps during site recognition by IHF. While the faster (∼100 μs) step is unaffected by changes in DNA or protein sequence that alter affinity by >100-fold, the slower (1-10 ms) step is accelerated ∼5-fold when mismatches are introduced at DNA sites that are sharply kinked in the specific complex. The amplitudes of the fast phase increase when the specific complex is destabilized and decrease with increasing [salt], which increases specificity. Taken together, these results indicate that the fast phase is non-specific DNA bending while the slow phase, which responds only to changes in DNA flexibility at the kink sites, is specific DNA kinking during site recognition. Notably, the timescales for the fast phase overlap with one-dimensional diffusion times measured for several proteins on DNA, suggesting that these dynamics reflect partial DNA bending during interrogation of potential binding sites by IHF as it scans DNA.

  9. A two-step recognition of signal sequences determines the translocation efficiency of proteins.

    OpenAIRE

    Belin, D; Bost, S; Vassalli, J D; Strub, K

    1996-01-01

    The cytosolic and secreted, N-glycosylated, forms of plasminogen activator inhibitor-2 (PAI-2) are generated by facultative translocation. To study the molecular events that result in the bi-topological distribution of proteins, we determined in vitro the capacities of several signal sequences to bind the signal recognition particle (SRP) during targeting, and to promote vectorial transport of murine PAI-2 (mPAI-2). Interestingly, the six signal sequences we compared (mPAI-2 and three mutated...

  10. Recognition

    DEFF Research Database (Denmark)

    Gimmler, Antje

    2017-01-01

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

  11. Medical device registration, agreements on mutual recognition - a step forward to global harmonization?

    International Nuclear Information System (INIS)

    Eidenberger, R.Reiner

    2000-01-01

    The purpose of this article is to give a short overview of some different regulations in Europe and the United States with regard to the clearance of medical devices and to give an outlook of what the Agreements on Mutual Recognition will bring in terms of Global Harmonization. Recent European legislation, the Council Directive 93/42/EEC of 14 June 1993 concerning medical devices (Medical Device Directive, MDD), requires that all medical devices placed on the European market bear the CE marking. From 14 June 1998, medical devices fall under the scope of this European Medical Device Directive and there is a harmonization within the European market. Similar to this, but for another market, are the USA FDA requirements, Premarket Approval (PMA) and Premarket notification (510(k)). The same medical device, the same goal - a safe product - but different legislation and thus duplication of registration procedures. The European Commission is presently discussing a series of agreements with third countries, Australia, New Zealand, USA, Canada, Japan and Eastern European countries wishing to join the EU, concerning the mutual acceptance of inspection bodies and, ultimately, proof of conformity (for example reports on examination, certificates, licenses and marks of conformity) in connection with medical devices. Meanwhile agreements with Australia, New Zealand, USA and Canada came into force. (author)

  12. Improved Gender Recognition during Stepping Activity for Rehab Application Using the Combinatorial Fusion Approach of EMG and HRV

    Directory of Open Access Journals (Sweden)

    Nor Aziyatul Izni Mohd Rosli

    2017-03-01

    Full Text Available Gender recognition is trivial for a physiotherapist, but it is considered a challenge for computers. The electromyography (EMG and heart rate variability (HRV were utilized in this work for gender recognition during exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC function in a combinatorial fusion approach (CFA (Hsu et al. was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB, decision tree (J48, k-nearest neighbor (KNN and support vector machine (SVM. Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient and effective for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Barani’s work (90.34%, Nazarloo’s work (92.50%, and other classifiers.

  13. About miRNAs, miRNA seeds, target genes and target pathways.

    Science.gov (United States)

    Kehl, Tim; Backes, Christina; Kern, Fabian; Fehlmann, Tobias; Ludwig, Nicole; Meese, Eckart; Lenhof, Hans-Peter; Keller, Andreas

    2017-12-05

    miRNAs are typically repressing gene expression by binding to the 3' UTR, leading to degradation of the mRNA. This process is dominated by the eight-base seed region of the miRNA. Further, miRNAs are known not only to target genes but also to target significant parts of pathways. A logical line of thoughts is: miRNAs with similar (seed) sequence target similar sets of genes and thus similar sets of pathways. By calculating similarity scores for all 3.25 million pairs of 2,550 human miRNAs, we found that this pattern frequently holds, while we also observed exceptions. Respective results were obtained for both, predicted target genes as well as experimentally validated targets. We note that miRNAs target gene set similarity follows a bimodal distribution, pointing at a set of 282 miRNAs that seems to target genes with very high specificity. Further, we discuss miRNAs with different (seed) sequences that nonetheless regulate similar gene sets or pathways. Most intriguingly, we found miRNA pairs that regulate different gene sets but similar pathways such as miR-6886-5p and miR-3529-5p. These are jointly targeting different parts of the MAPK signaling cascade. The main goal of this study is to provide a general overview on the results, to highlight a selection of relevant results on miRNAs, miRNA seeds, target genes and target pathways and to raise awareness for artifacts in respective comparisons. The full set of information that allows to infer detailed results on each miRNA has been included in miRPathDB, the miRNA target pathway database (https://mpd.bioinf.uni-sb.de).

  14. Dance-the-Music: an educational platform for the modeling, recognition and audiovisual monitoring of dance steps using spatiotemporal motion templates

    Science.gov (United States)

    Maes, Pieter-Jan; Amelynck, Denis; Leman, Marc

    2012-12-01

    In this article, a computational platform is presented, entitled "Dance-the-Music", that can be used in a dance educational context to explore and learn the basics of dance steps. By introducing a method based on spatiotemporal motion templates, the platform facilitates to train basic step models from sequentially repeated dance figures performed by a dance teacher. Movements are captured with an optical motion capture system. The teachers' models can be visualized from a first-person perspective to instruct students how to perform the specific dance steps in the correct manner. Moreover, recognition algorithms-based on a template matching method-can determine the quality of a student's performance in real time by means of multimodal monitoring techniques. The results of an evaluation study suggest that the Dance-the-Music is effective in helping dance students to master the basics of dance figures.

  15. Speech Recognition

    Directory of Open Access Journals (Sweden)

    Adrian Morariu

    2009-01-01

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

  16. Single step synthesis of gold-amino acid composite, with the evidence of the catalytic hydrogen atom transfer (HAT) reaction, for the electrochemical recognition of Serotonin

    Science.gov (United States)

    Choudhary, Meenakshi; Siwal, Samarjeet; Nandi, Debkumar; Mallick, Kaushik

    2016-03-01

    A composite architecture of amino acid and gold nanoparticles has been synthesized using a generic route of 'in-situ polymerization and composite formation (IPCF)' [1,2]. The formation mechanism of the composite has been supported by a model hydrogen atom (H•≡H++e-) transfer (HAT) type of reaction which belongs to the proton coupled electron transfer (PCET) mechanism. The 'gold-amino acid composite' was used as a catalyst for the electrochemical recognition of Serotonin.

  17. Dual-Recognition Förster Resonance Energy Transfer Based Platform for One-Step Sensitive Detection of Pathogenic Bacteria Using Fluorescent Vancomycin-Gold Nanoclusters and Aptamer-Gold Nanoparticles.

    Science.gov (United States)

    Yu, Mengqun; Wang, Hong; Fu, Fei; Li, Linyao; Li, Jing; Li, Gan; Song, Yang; Swihart, Mark T; Song, Erqun

    2017-04-04

    The effective monitoring, identification, and quantification of pathogenic bacteria is essential for addressing serious public health issues. In this study, we present a universal and facile one-step strategy for sensitive and selective detection of pathogenic bacteria using a dual-molecular affinity-based Förster (fluorescence) resonance energy transfer (FRET) platform based on the recognition of bacterial cell walls by antibiotic and aptamer molecules, respectively. As a proof of concept, Vancomycin (Van) and a nucleic acid aptamer were employed in a model dual-recognition scheme for detecting Staphylococcus aureus (Staph. aureus). Within 30 min, by using Van-functionalized gold nanoclusters and aptamer-modified gold nanoparticles as the energy donor and acceptor, respectively, the FRET signal shows a linear variation with the concentration of Staph. aureus in the range from 20 to 10 8 cfu/mL with a detection limit of 10 cfu/mL. Other nontarget bacteria showed negative results, demonstrating the good specificity of the approach. When employed to assay Staph. aureus in real samples, the dual-recognition FRET strategy showed recoveries from 99.00% to the 109.75% with relative standard derivations (RSDs) less than 4%. This establishes a universal detection platform for sensitive, specific, and simple pathogenic bacteria detection, which could have great impact in the fields of food/public safety monitoring and infectious disease diagnosis.

  18. 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

  19. Facial Expression Recognition

    NARCIS (Netherlands)

    Pantic, Maja; Li, S.; Jain, A.

    2009-01-01

    Facial expression recognition is a process performed by humans or computers, which consists of: 1. Locating faces in the scene (e.g., in an image; this step is also referred to as face detection), 2. Extracting facial features from the detected face region (e.g., detecting the shape of facial

  20. Touchless palmprint recognition systems

    CERN Document Server

    Genovese, Angelo; Scotti, Fabio

    2014-01-01

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

  1. License plate recognition using DTCNNs

    NARCIS (Netherlands)

    ter Brugge, M.H; Stevens, J.H; Nijhuis, J.A G; Spaanenburg, L; Tavsanonoglu, V

    1998-01-01

    Automatic license plate recognition requires a series of complex image processing steps. For practical use, the amount of data to he processed must be minimized early on. This paper shows that the computationally most intensive steps can be realized by DTCNNs. Moreover; high-level operations like

  2. Mathematical symbol hypothesis recognition with rejection option

    OpenAIRE

    Julca-Aguilar , Frank; Hirata , Nina ,; Viard-Gaudin , Christian; Mouchère , Harold; Medjkoune , Sofiane

    2014-01-01

    International audience; In the context of handwritten mathematical expressions recognition, a first step consist on grouping strokes (segmentation) to form symbol hypotheses: groups of strokes that might represent a symbol. Then, the symbol recognition step needs to cope with the identification of wrong segmented symbols (false hypotheses). However, previous works on symbol recognition consider only correctly segmented symbols. In this work, we focus on the problem of mathematical symbol reco...

  3. Speaker Recognition

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther

    2005-01-01

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

  4. Iris analysis for biometric recognition systems

    CERN Document Server

    Bodade, Rajesh M

    2014-01-01

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

  5. Simultaneous tracking and activity recognition

    DEFF Research Database (Denmark)

    Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.

    2011-01-01

    be used to improve the prediction step of the tracking, while, at the same time, tracking information can be used for online activity recognition. Experimental results in two different settings show that our approach 1) decreases the error rate and improves the identity maintenance of the positional......Many tracking problems involve several distinct objects interacting with each other. We develop a framework that takes into account interactions between objects allowing the recognition of complex activities. In contrast to classic approaches that consider distinct phases of tracking and activity...... tracking and 2) identifies the correct activity with higher accuracy than standard approaches....

  6. Application of stepping motor

    International Nuclear Information System (INIS)

    1980-10-01

    This book is divided into three parts, which is about practical using of stepping motor. The first part has six chapters. The contents of the first part are about stepping motor, classification of stepping motor, basic theory og stepping motor, characteristic and basic words, types and characteristic of stepping motor in hybrid type and basic control of stepping motor. The second part deals with application of stepping motor with hardware of stepping motor control, stepping motor control by microcomputer and software of stepping motor control. The last part mentions choice of stepping motor system, examples of stepping motor, measurement of stepping motor and practical cases of application of stepping motor.

  7. Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Aleš Procházka

    2018-05-01

    Full Text Available Multimodal signal analysis based on sophisticated sensors, efficient communicationsystems and fast parallel processing methods has a rapidly increasing range of multidisciplinaryapplications. The present paper is devoted to pattern recognition, machine learning, and the analysisof sleep stages in the detection of sleep disorders using polysomnography (PSG data, includingelectroencephalography (EEG, breathing (Flow, and electro-oculogram (EOG signals. The proposedmethod is based on the classification of selected features by a neural network system with sigmoidaland softmax transfer functions using Bayesian methods for the evaluation of the probabilities of theseparate classes. The application is devoted to the analysis of the sleep stages of 184 individualswith different diagnoses, using EEG and further PSG signals. Data analysis points to an averageincrease of the length of the Wake stage by 2.7% per 10 years and a decrease of the length of theRapid Eye Movement (REM stages by 0.8% per 10 years. The mean classification accuracy for givensets of records and single EEG and multimodal features is 88.7% ( standard deviation, STD: 2.1 and89.6% (STD:1.9, respectively. The proposed methods enable the use of adaptive learning processesfor the detection and classification of health disorders based on prior specialist experience andman–machine interaction.

  8. Step out - Step in Sequencing Games

    NARCIS (Netherlands)

    Musegaas, M.; Borm, P.E.M.; Quant, M.

    2014-01-01

    In this paper a new class of relaxed sequencing games is introduced: the class of Step out - Step in sequencing games. In this relaxation any player within a coalition is allowed to step out from his position in the processing order and to step in at any position later in the processing order.

  9. Step out-step in sequencing games

    NARCIS (Netherlands)

    Musegaas, Marieke; Borm, Peter; Quant, Marieke

    2015-01-01

    In this paper a new class of relaxed sequencing games is introduced: the class of Step out–Step in sequencing games. In this relaxation any player within a coalition is allowed to step out from his position in the processing order and to step in at any position later in the processing order. First,

  10. Face Detection and Recognition

    National Research Council Canada - National Science Library

    Jain, Anil K

    2004-01-01

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

  11. Graphical symbol recognition

    OpenAIRE

    K.C. , Santosh; Wendling , Laurent

    2015-01-01

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

  12. Parametric Primitives for Hand Gesture Recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan; Krüger, Volker

    2009-01-01

    Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper  an online algorithm to recognize parametric actions with object context is presented. Objects are key instruments in understanding...

  13. Face Recognition using Gabor Filters

    Directory of Open Access Journals (Sweden)

    Sajjad MOHSIN

    2011-01-01

    Full Text Available An Elastic Bunch Graph Map (EBGM algorithm is being proposed in this research paper that successfully implements face recognition using Gabor filters. The proposed system applies 40 different Gabor filters on an image. As aresult of which 40 images with different angles and orientation are received. Next, maximum intensity points in each filtered image are calculated and mark them as Fiducial points. The system reduces these points in accordance to distance between them. The next step is calculating the distances between the reduced points using distance formula. At last, the distances are compared with database. If match occurs, it means that the image is recognized.

  14. Recognition and Toleration

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2010-01-01

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

  15. Internship guide : Work placements step by step

    NARCIS (Netherlands)

    Haag, Esther

    2013-01-01

    Internship Guide: Work Placements Step by Step has been written from the practical perspective of a placement coordinator. This book addresses the following questions : what problems do students encounter when they start thinking about the jobs their degree programme prepares them for? How do you

  16. The way to collisions, step by step

    CERN Multimedia

    2009-01-01

    While the LHC sectors cool down and reach the cryogenic operating temperature, spirits are warming up as we all eagerly await the first collisions. No reason to hurry, though. Making particles collide involves the complex manoeuvring of thousands of delicate components. The experts will make it happen using a step-by-step approach.

  17. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Directory of Open Access Journals (Sweden)

    Muhammad Hameed Siddiqi

    2013-12-01

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

  18. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Science.gov (United States)

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

    2013-01-01

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

  19. 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...

  20. Optical Pattern Recognition

    Science.gov (United States)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

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

  1. Microsoft Office professional 2010 step by step

    CERN Document Server

    Cox, Joyce; Frye, Curtis

    2011-01-01

    Teach yourself exactly what you need to know about using Office Professional 2010-one step at a time! With STEP BY STEP, you build and practice new skills hands-on, at your own pace. Covering Microsoft Word, PowerPoint, Outlook, Excel, Access, Publisher, and OneNote, this book will help you learn the core features and capabilities needed to: Create attractive documents, publications, and spreadsheetsManage your e-mail, calendar, meetings, and communicationsPut your business data to workDevelop and deliver great presentationsOrganize your ideas and notes in one placeConnect, share, and accom

  2. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on-site and on-time. At this point, the use of smart cameras – of which the popularity has been increasing – is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image-processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high-bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general-purpose processors. In smart cameras – which are real-life applications of such methods – the widest use is on DSPs. In the present study, the Viola-Jones face detection method – which was reported to run faster on PCs – was optimized for DSPs; the face recognition method was combined with the developed sub-region and mask-based DCT (Discrete Cosine Transform. As the employed DSP is a fixed-point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub-regions and from each sub-region the robust coefficients against disruptive elements – like face expression, illumination, etc. – were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for recognition. Thanks to its

  3. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  4. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

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

  5. Stereo vision with distance and gradient recognition

    Science.gov (United States)

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

    2007-12-01

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

  6. Face Recognition in Humans and Machines

    Science.gov (United States)

    O'Toole, Alice; Tistarelli, Massimo

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

  7. Step by Step Microsoft Office Visio 2003

    CERN Document Server

    Lemke, Judy

    2004-01-01

    Experience learning made easy-and quickly teach yourself how to use Visio 2003, the Microsoft Office business and technical diagramming program. With STEP BY STEP, you can take just the lessons you need, or work from cover to cover. Either way, you drive the instruction-building and practicing the skills you need, just when you need them! Produce computer network diagrams, organization charts, floor plans, and moreUse templates to create new diagrams and drawings quicklyAdd text, color, and 1-D and 2-D shapesInsert graphics and pictures, such as company logosConnect shapes to create a basic f

  8. Paradigms in object recognition

    International Nuclear Information System (INIS)

    Mutihac, R.; Mutihac, R.C.

    1999-09-01

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

  9. Infant Visual Recognition Memory

    Science.gov (United States)

    Rose, Susan A.; Feldman, Judith F.; Jankowski, Jeffery J.

    2004-01-01

    Visual recognition memory is a robust form of memory that is evident from early infancy, shows pronounced developmental change, and is influenced by many of the same factors that affect adult memory; it is surprisingly resistant to decay and interference. Infant visual recognition memory shows (a) modest reliability, (b) good discriminant…

  10. Recognition and Toleration

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2010-01-01

    Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms or inter...

  11. Challenging ocular image recognition

    Science.gov (United States)

    Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.

    2011-06-01

    Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

  12. Free Modal Algebras Revisited: The Step-by-Step Method

    NARCIS (Netherlands)

    Bezhanishvili, N.; Ghilardi, Silvio; Jibladze, Mamuka

    2012-01-01

    We review the step-by-step method of constructing finitely generated free modal algebras. First we discuss the global step-by-step method, which works well for rank one modal logics. Next we refine the global step-by-step method to obtain the local step-by-step method, which is applicable beyond

  13. Diabetes PSA (:30) Step By Step

    Centers for Disease Control (CDC) Podcasts

    2009-10-24

    First steps to preventing diabetes. For Hispanic and Latino American audiences.  Created: 10/24/2009 by National Diabetes Education Program (NDEP), a joint program of the Centers for Disease Control and Prevention and the National Institutes of Health.   Date Released: 10/24/2009.

  14. Diabetes PSA (:60) Step By Step

    Centers for Disease Control (CDC) Podcasts

    2009-10-24

    First steps to preventing diabetes. For Hispanic and Latino American audiences.  Created: 10/24/2009 by National Diabetes Education Program (NDEP), a joint program of the Centers for Disease Control and Prevention and the National Institutes of Health.   Date Released: 10/24/2009.

  15. Recognition and cinema: new ways of approaching

    Directory of Open Access Journals (Sweden)

    José Luis GARCÍA MARTÍNEZ

    2016-09-01

    Full Text Available Along the following lines we propose the use of films for educational purposes. Our main argument, based on philosophical grounds, shows the use of film format to emphasize and understand people’s motivations and actions. The reflections brought about by empathy with the characters are the first step in the approach of the topic of recognition, a term that in the medical framework involves taking into account the various aspects of inter-human relationships. Recognition of “the other” as he/she stands, implies addressing differences and providing a better doctor-patient relationship. The analysis of several films might encourage the acknowledgement of recognition as one of the key concepts to understand our ways of relating within plural societies with different lifestyles and different outlooks on the world. We believe that the effort made in dealing with such topics results in greater closeness to the patient and, therefore, better care.

  16. Microsoft Office Word 2007 step by step

    CERN Document Server

    Cox, Joyce

    2007-01-01

    Experience learning made easy-and quickly teach yourself how to create impressive documents with Word 2007. With Step By Step, you set the pace-building and practicing the skills you need, just when you need them!Apply styles and themes to your document for a polished lookAdd graphics and text effects-and see a live previewOrganize information with new SmartArt diagrams and chartsInsert references, footnotes, indexes, a table of contentsSend documents for review and manage revisionsTurn your ideas into blogs, Web pages, and moreYour all-in-one learning experience includes:Files for building sk

  17. Success with voice recognition.

    Science.gov (United States)

    Sferrella, Sheila M

    2003-01-01

    You need a compelling reason to implement voice recognition technology. At my institution, the compelling reason was a turnaround time for Radiology results of more than two days. Only 41 percent of our reports were transcribed and signed within 24 hours. In November 1998, a team from Lehigh Valley Hospital went to RSNA and reviewed every voice system on the market. The evaluation was done with the radiologist workflow in mind, and we came back from the meeting with the vendor selection completed. The next steps included developing a business plan, approval of funds, reference calls to more than 15 sites and contract negotiation, all of which took about six months. The department of Radiology at Lehigh Valley Hospital and Health Network (LVHHN) is a multi-site center that performs over 360,000 procedures annually. The department handles all modalities of radiology: general diagnosis, neuroradiology, ultrasound, CT Scan, MRI, interventional radiology, arthography, myelography, bone densitometry, nuclear medicine, PET imaging, vascular lab and other advanced procedures. The department consists of 200 FTEs and a medical staff of more than 40 radiologists. The budget is in the $10.3 million range. There are three hospital sites and four outpatient imaging center sites where services are provided. At Lehigh Valley Hospital, radiologists are not dedicated to one subspecialty, so implementing a voice system by modality was not an option. Because transcription was so far behind, we needed to eliminate that part of the process. As a result, we decided to deploy the system all at once and with the radiologists as editors. The planning and testing phase took about four months, and the implementation took two weeks. We deployed over 40 workstations and trained close to 50 physicians. The radiologists brought in an extra radiologist from our group for the two weeks of training. That allowed us to train without taking a radiologist out of the department. We trained three to six

  18. 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...

  19. GENDER RECOGNITION BASED ON SIFT FEATURES

    OpenAIRE

    Sahar Yousefi; Morteza Zahedi

    2011-01-01

    This paper proposes a robust approach for face detection and gender classification in color images. Previous researches about gender recognition suppose an expensive computational and time-consuming pre-processing step in order to alignment in which face images are aligned so that facial landmarks like eyes, nose, lips, chin are placed in uniform locations in image. In this paper, a novel technique based on mathematical analysis is represented in three stages that eliminates align...

  20. New FASB standard addresses revenue recognition considerations.

    Science.gov (United States)

    McKee, Thomas E

    2015-12-01

    Healthcare organizations are expected to apply the following steps in revenue recognition under the new standard issued in May 2014 by the Financial Accounting Standards Board: Identify the customer contract. Identify the performance obligations in the contract. Determine the transaction price. Allocate the transaction price to the performance obligations in the contract. Recognize revenue when--or in some circumstances, as--the entity satisfies the performance obligation.

  1. Harmonization versus Mutual Recognition

    DEFF Research Database (Denmark)

    Jørgensen, Jan Guldager; Schröder, Philipp

    The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired with the oppor......The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired...... countries and three firms, where firms first lobby for the policy coordination regime (harmonization versus mutual recognition), and subsequently, in case of harmonization, the global standard is auctioned among the firms. We discuss welfare effects and conclude with policy implications. In particular......, harmonized standards may fail to harvest the full pro-competitive effects from trade liberalization compared to mutual recognition; moreover, the issue is most pronounced in markets featuring price competition....

  2. CASE Recognition Awards.

    Science.gov (United States)

    Currents, 1985

    1985-01-01

    A total of 294 schools, colleges, and universities received prizes in this year's CASE Recognition program. Awards were given in: public relations programs, student recruitment, marketing, program pulications, news writing, fund raising, radio programming, school periodicals, etc. (MLW)

  3. Forensic speaker recognition

    NARCIS (Netherlands)

    Meuwly, Didier

    2013-01-01

    The aim of forensic speaker recognition is to establish links between individuals and criminal activities, through audio speech recordings. This field is multidisciplinary, combining predominantly phonetics, linguistics, speech signal processing, and forensic statistics. On these bases, expert-based

  4. The Recognition Of Fatigue

    DEFF Research Database (Denmark)

    Elsass, Peter; Jensen, Bodil; Mørup, Rikke

    2007-01-01

    Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87......Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87...

  5. Evaluating music emotion recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....

  6. Why recognition is rational

    Directory of Open Access Journals (Sweden)

    Clintin P. Davis-Stober

    2010-07-01

    Full Text Available The Recognition Heuristic (Gigerenzer and Goldstein, 1996; Goldstein and Gigerenzer, 2002 makes the counter-intuitive prediction that a decision maker utilizing less information may do as well as, or outperform, an idealized decision maker utilizing more information. We lay a theoretical foundation for the use of single-variable heuristics such as the Recognition Heuristic as an optimal decision strategy within a linear modeling framework. We identify conditions under which over-weighting a single predictor is a mini-max strategy among a class of a priori chosen weights based on decision heuristics with respect to a measure of statistical lack of fit we call ``risk''. These strategies, in turn, outperform standard multiple regression as long as the amount of data available is limited. We also show that, under related conditions, weighting only one variable and ignoring all others produces the same risk as ignoring the single variable and weighting all others. This approach has the advantage of generalizing beyond the original environment of the Recognition Heuristic to situations with more than two choice options, binary or continuous representations of recognition, and to other single variable heuristics. We analyze the structure of data used in some prior recognition tasks and find that it matches the sufficient conditions for optimality in our results. Rather than being a poor or adequate substitute for a compensatory model, the Recognition Heuristic closely approximates an optimal strategy when a decision maker has finite data about the world.

  7. Automatic Emotion Recognition in Speech: Possibilities and Significance

    Directory of Open Access Journals (Sweden)

    Milana Bojanić

    2009-12-01

    Full Text Available Automatic speech recognition and spoken language understanding are crucial steps towards a natural humanmachine interaction. The main task of the speech communication process is the recognition of the word sequence, but the recognition of prosody, emotion and stress tags may be of particular importance as well. This paper discusses thepossibilities of recognition emotion from speech signal in order to improve ASR, and also provides the analysis of acoustic features that can be used for the detection of speaker’s emotion and stress. The paper also provides a short overview of emotion and stress classification techniques. The importance and place of emotional speech recognition is shown in the domain of human-computer interactive systems and transaction communication model. The directions for future work are given at the end of this work.

  8. Fingerprint recognition system by use of graph matching

    Science.gov (United States)

    Shen, Wei; Shen, Jun; Zheng, Huicheng

    2001-09-01

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

  9. 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

  10. Focal cryotherapy: step by step technique description

    Directory of Open Access Journals (Sweden)

    Cristina Redondo

    Full Text Available ABSTRACT Introduction and objective: Focal cryotherapy emerged as an efficient option to treat favorable and localized prostate cancer (PCa. The purpose of this video is to describe the procedure step by step. Materials and methods: We present the case of a 68 year-old man with localized PCa in the anterior aspect of the prostate. Results: The procedure is performed under general anesthesia, with the patient in lithotomy position. Briefly, the equipment utilized includes the cryotherapy console coupled with an ultrasound system, argon and helium gas bottles, cryoprobes, temperature probes and an urethral warming catheter. The procedure starts with a real-time trans-rectal prostate ultrasound, which is used to outline the prostate, the urethra and the rectal wall. The cryoprobes are pretested and placed in to the prostate through the perineum, following a grid template, along with the temperature sensors under ultrasound guidance. A cystoscopy confirms the right positioning of the needles and the urethral warming catheter is installed. Thereafter, the freeze sequence with argon gas is started, achieving extremely low temperatures (-40°C to induce tumor cell lysis. Sequentially, the thawing cycle is performed using helium gas. This process is repeated one time. Results among several series showed a biochemical disease-free survival between 71-93% at 9-70 month- follow-up, incontinence rates between 0-3.6% and erectile dysfunction between 0-42% (1–5. Conclusions: Focal cryotherapy is a feasible procedure to treat anterior PCa that may offer minimal morbidity, allowing good cancer control and better functional outcomes when compared to whole-gland treatment.

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

    Science.gov (United States)

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Pavol Partila

    2015-01-01

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

  13. Probabilistic Open Set Recognition

    Science.gov (United States)

    Jain, Lalit Prithviraj

    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

  14. Step-by-step cyclic processes scheduling

    DEFF Research Database (Denmark)

    Bocewicz, G.; Nielsen, Izabela Ewa; Banaszak, Z.

    2013-01-01

    Automated Guided Vehicles (AGVs) fleet scheduling is one of the big problems in Flexible Manufacturing System (FMS) control. The problem is more complicated when concurrent multi-product manufacturing and resource deadlock avoidance policies are considered. The objective of the research is to pro......Automated Guided Vehicles (AGVs) fleet scheduling is one of the big problems in Flexible Manufacturing System (FMS) control. The problem is more complicated when concurrent multi-product manufacturing and resource deadlock avoidance policies are considered. The objective of the research...... is to provide a declarative model enabling to state a constraint satisfaction problem aimed at AGVs fleet scheduling subject to assumed itineraries of concurrently manufactured product types. In other words, assuming a given layout of FMS’s material handling and production routes of simultaneously manufactured...... orders, the main objective is to provide the declarative framework aimed at conditions allowing one to calculate the AGVs fleet schedule in online mode. An illustrative example of the relevant algebra-like driven step-by-stem cyclic scheduling is provided....

  15. [Prosopagnosia and facial expression recognition].

    Science.gov (United States)

    Koyama, Shinichi

    2014-04-01

    This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

  16. Optical Character Recognition.

    Science.gov (United States)

    Converso, L.; Hocek, S.

    1990-01-01

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

  17. Recognition of fractal graphs

    NARCIS (Netherlands)

    Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM

    1999-01-01

    Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems

  18. Mutual Trust and Cross-Border Enforcement of Judgments in Civil Matters in the EU: Does the Step-by-Step Approach Work?

    NARCIS (Netherlands)

    Zilinsky, M.

    2017-01-01

    Mutual trust is one of the cornerstones of cooperation in the field of European Union private international law. Based on this principle the rules on the cross-border recognition and enforcement of judgments in the European Union are still subject to simplification. The step-by-step approach of the

  19. The Seven Step Strategy

    Science.gov (United States)

    Schaffer, Connie

    2017-01-01

    Many well-intended instructors use Socratic or leveled questioning to facilitate the discussion of an assigned reading. While this engages a few students, most can opt to remain silent. The seven step strategy described in this article provides an alternative to classroom silence and engages all students. Students discuss a single reading as they…

  20. Galeotti on recognition as inclusion

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2008-01-01

    Anna Elisabetta Galeotti's theory of 'toleration as recognition' has been criticised by Peter Jones for being conceptually incoherent, since liberal toleration presupposes a negative attitude to differences, whereas multicultural recognition requires positive affirmation hereof. The paper spells ...

  1. School IPM Recognition and Certification

    Science.gov (United States)

    Schools and school districts can get support and recognition for implementation of school IPM. EPA is developing a program to provide recognition for school districts that are working towards or have achieved a level of success with school IPM programs.

  2. Stereotype Associations and Emotion Recognition

    NARCIS (Netherlands)

    Bijlstra, Gijsbert; Holland, Rob W.; Dotsch, Ron; Hugenberg, Kurt; Wigboldus, Daniel H. J.

    We investigated whether stereotype associations between specific emotional expressions and social categories underlie stereotypic emotion recognition biases. Across two studies, we replicated previously documented stereotype biases in emotion recognition using both dynamic (Study 1) and static

  3. Automatic anatomy recognition on CT images with pathology

    Science.gov (United States)

    Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

    2016-03-01

    Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

  4. A REVIEW: OPTICAL CHARACTER RECOGNITION

    OpenAIRE

    Swati Tomar*1 & Amit Kishore2

    2018-01-01

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

  5. Investigation of the Relationship between Entrepreneurial Opportunity Recognition and Entrepreneurial Capitals

    OpenAIRE

    Susan Ramezanpour; Seyran Amiriyan; Ali Naghi Mosleh Shirazy

    2014-01-01

    The heart of entrepreneurship is the creation and/or recognition of opportunities. Although there is no universal definition of entrepreneurship, opportunity recognition has been viewed as the central definition of this phenomenon. Without an opportunity there is no entrepreneurship. Therefore opportunity recognition is widely seen as a key step of the entrepreneurial processes. The identification of opportunities has been recognized as one of the most important abilities of successful entrep...

  6. Superficial Priming in Episodic Recognition

    Science.gov (United States)

    Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.

    2010-01-01

    We explored the effect of superficial priming in episodic recognition and found it to be different from the effect of semantic priming in episodic recognition. Participants made recognition judgments to pairs of items, with each pair consisting of a prime item and a test item. Correct positive responses to the test item were impeded if the prime…

  7. Word Recognition in Auditory Cortex

    Science.gov (United States)

    DeWitt, Iain D. J.

    2013-01-01

    Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

  8. Visual Recognition Memory across Contexts

    Science.gov (United States)

    Jones, Emily J. H.; Pascalis, Olivier; Eacott, Madeline J.; Herbert, Jane S.

    2011-01-01

    In two experiments, we investigated the development of representational flexibility in visual recognition memory during infancy using the Visual Paired Comparison (VPC) task. In Experiment 1, 6- and 9-month-old infants exhibited recognition when familiarization and test occurred in the same room, but showed no evidence of recognition when…

  9. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Quaglia, Adamo; Epifano, Calogera M.

    2012-01-01

    The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a

  10. Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey

    NARCIS (Netherlands)

    Avci, A.; Bosch, S.; Marin Perianu, Mihai; Marin Perianu, Raluca; Havinga, Paul J.M.

    This paper surveys the current research directions of activity recognition using inertial sensors, with potential application in healthcare, wellbeing and sports. The analysis of related work is organized according to the five main steps involved in the activity recognition process: preprocessing,

  11. Toward fast feature adaptation and localization for real-time face recognition systems

    NARCIS (Netherlands)

    Zuo, F.; With, de P.H.N.; Ebrahimi, T.; Sikora, T.

    2003-01-01

    In a home environment, video surveillance employing face detection and recognition is attractive for new applications. Facial feature (e.g. eyes and mouth) localization in the face is an essential task for face recognition because it constitutes an indispensable step for face geometry normalization.

  12. Linear step drive

    International Nuclear Information System (INIS)

    Haniger, L.; Elger, R.; Kocandrle, L.; Zdebor, J.

    1986-01-01

    A linear step drive is described developed in Czechoslovak-Soviet cooperation and intended for driving WWER-1000 control rods. The functional principle is explained of the motor and the mechanical and electrical parts of the drive, power control, and the indicator of position are described. The motor has latches situated in the reactor at a distance of 3 m from magnetic armatures, it has a low structural height above the reactor cover, which suggests its suitability for seismic localities. Its magnetic circuits use counterpoles; the mechanical shocks at the completion of each step are damped using special design features. The position indicator is of a special design and evaluates motor position within ±1% of total travel. A drive diagram and the flow chart of both the control electronics and the position indicator are presented. (author) 4 figs

  13. Computational Abstraction Steps

    DEFF Research Database (Denmark)

    Thomsen, Lone Leth; Thomsen, Bent; Nørmark, Kurt

    2010-01-01

    and class instantiations. Our teaching experience shows that many novice programmers find it difficult to write programs with abstractions that materialise to concrete objects later in the development process. The contribution of this paper is the idea of initiating a programming process by creating...... or capturing concrete values, objects, or actions. As the next step, some of these are lifted to a higher level by computational means. In the object-oriented paradigm the target of such steps is classes. We hypothesise that the proposed approach primarily will be beneficial to novice programmers or during...... the exploratory phase of a program development process. In some specific niches it is also expected that our approach will benefit professional programmers....

  14. Step 3: Manage Your Diabetes

    Science.gov (United States)

    ... please turn JavaScript on. Feature: Type 2 Diabetes Step 3: Manage Your Diabetes Past Issues / Fall 2014 ... 2 Diabetes" Articles Diabetes Is Serious But Manageable / Step 1: Learn About Diabetes / Step 2: Know Your ...

  15. FlexiTerm: a flexible term recognition method

    NARCIS (Netherlands)

    Spasic, I.; Greenwood, M.; Preece, A.; Francis, N.; Elwyn, G.

    2013-01-01

    BACKGROUND: The increasing amount of textual information in biomedicine requires effective term recognition methods to identify textual representations of domain-specific concepts as the first step toward automating its semantic interpretation. The dictionary look-up approaches may not always be

  16. Overview of radar intra-pulse modulation recognition

    Science.gov (United States)

    Zang, Hanlin; Li, Yanling

    2018-05-01

    This paper introduces the current radar intra-pulse modulation method, describes the status quo and development direction of the intentional modulation and unintentional modulation in the pulse, and summarizes the existing problems and prospects for the future. Looking forward to the future, and providing a reference direction for the research on radar signal recognition in the next step.

  17. Pattern Recognition as a Human Centered non-Euclidean Problem

    NARCIS (Netherlands)

    Duin, R.P.W.

    2010-01-01

    Regularities in the world are human defined. Patterns in the observed phenomena are there because we define and recognize them as such. Automatic pattern recognition tries to bridge the gap between human judgment and measurements made by artificial sensors. This is done in two steps: representation

  18. Semantic Activity Recognition

    OpenAIRE

    Thonnat , Monique

    2008-01-01

    International audience; Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia Antipolis. Our main objective is to analyse in real-time video streams captured by static video cameras and to recogniz...

  19. Object Recognition In HADOOP Using HIPI

    Directory of Open Access Journals (Sweden)

    Ankit Kumar Agrawal

    2015-07-01

    Full Text Available Abstract The amount of images and videos being shared by the user is exponentially increasing but applications that perform video analytics is severely lacking or work on limited set of data. It is also challenging to perform analytics with less time complexity. Object recognition is the primary step in video analytics. We implement a robust method to extract objects from the data which is in unstructured format and cannot be processed directly by relational databases. In this study we present our report with results after performance evaluation and compare them with results of MATLAB.

  20. Pattern Recognition Control Design

    Science.gov (United States)

    Gambone, Elisabeth A.

    2018-01-01

    Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

  1. Optical character recognition of handwritten Arabic using hidden Markov models

    Science.gov (United States)

    Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

    2011-04-01

    The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

  2. Superpixel-Based Feature for Aerial Image Scene Recognition

    Directory of Open Access Journals (Sweden)

    Hongguang Li

    2018-01-01

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

  3. 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.

  4. Stepping Stones through Time

    Directory of Open Access Journals (Sweden)

    Emily Lyle

    2012-03-01

    Full Text Available Indo-European mythology is known only through written records but it needs to be understood in terms of the preliterate oral-cultural context in which it was rooted. It is proposed that this world was conceptually organized through a memory-capsule consisting of the current generation and the three before it, and that there was a system of alternate generations with each generation taking a step into the future under the leadership of a white or red king.

  5. SYSTEMATIZATION OF THE BASIC STEPS OF THE STEP-AEROBICS

    Directory of Open Access Journals (Sweden)

    Darinka Korovljev

    2011-03-01

    Full Text Available Following the development of the powerful sport industry, in front of us appeared a lot of new opportunities for creating of the new programmes of exercising with certain requisites. One of such programmes is certainly step-aerobics. Step-aerobics can be defined as a type of aerobics consisting of the basic aerobic steps (basic steps applied in exercising on stepper (step bench, with a possibility to regulate its height. Step-aerobics itself can be divided into several groups, depending on the following: type of music, working methods and adopted knowledge of the attendants. In this work, the systematization of the basic steps in step-aerobics was made on the basis of the following criteria: steps origin, number of leg motions in stepping and relating the body support at the end of the step. Systematization of the basic steps of the step-aerobics is quite significant for making a concrete review of the existing basic steps, thus making creation of the step-aerobics lesson easier

  6. Re-thinking employee recognition: understanding employee experiences of recognition

    OpenAIRE

    Smith, Charlotte

    2013-01-01

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

  7. SPAR-H Step-by-Step Guidance

    International Nuclear Information System (INIS)

    Galyean, W.J.; Whaley, A.M.; Kelly, D.L.; Boring, R.L.

    2011-01-01

    This guide provides step-by-step guidance on the use of the SPAR-H method for quantifying Human Failure Events (HFEs). This guide is intended to be used with the worksheets provided in: 'The SPAR-H Human Reliability Analysis Method,' NUREG/CR-6883, dated August 2005. Each step in the process of producing a Human Error Probability (HEP) is discussed. These steps are: Step-1, Categorizing the HFE as Diagnosis and/or Action; Step-2, Rate the Performance Shaping Factors; Step-3, Calculate PSF-Modified HEP; Step-4, Accounting for Dependence, and; Step-5, Minimum Value Cutoff. The discussions on dependence are extensive and include an appendix that describes insights obtained from the psychology literature.

  8. SPAR-H Step-by-Step Guidance

    Energy Technology Data Exchange (ETDEWEB)

    W. J. Galyean; A. M. Whaley; D. L. Kelly; R. L. Boring

    2011-05-01

    This guide provides step-by-step guidance on the use of the SPAR-H method for quantifying Human Failure Events (HFEs). This guide is intended to be used with the worksheets provided in: 'The SPAR-H Human Reliability Analysis Method,' NUREG/CR-6883, dated August 2005. Each step in the process of producing a Human Error Probability (HEP) is discussed. These steps are: Step-1, Categorizing the HFE as Diagnosis and/or Action; Step-2, Rate the Performance Shaping Factors; Step-3, Calculate PSF-Modified HEP; Step-4, Accounting for Dependence, and; Step-5, Minimum Value Cutoff. The discussions on dependence are extensive and include an appendix that describes insights obtained from the psychology literature.

  9. [Research progress of multi-model medical image fusion and recognition].

    Science.gov (United States)

    Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

    2013-10-01

    Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

  10. Human activity recognition and prediction

    CERN Document Server

    2016-01-01

    This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

  11. [Comparative studies of face recognition].

    Science.gov (United States)

    Kawai, Nobuyuki

    2012-07-01

    Every human being is proficient in face recognition. However, the reason for and the manner in which humans have attained such an ability remain unknown. These questions can be best answered-through comparative studies of face recognition in non-human animals. Studies in both primates and non-primates show that not only primates, but also non-primates possess the ability to extract information from their conspecifics and from human experimenters. Neural specialization for face recognition is shared with mammals in distant taxa, suggesting that face recognition evolved earlier than the emergence of mammals. A recent study indicated that a social insect, the golden paper wasp, can distinguish their conspecific faces, whereas a closely related species, which has a less complex social lifestyle with just one queen ruling a nest of underlings, did not show strong face recognition for their conspecifics. Social complexity and the need to differentiate between one another likely led humans to evolve their face recognition abilities.

  12. Genetic specificity of face recognition.

    Science.gov (United States)

    Shakeshaft, Nicholas G; Plomin, Robert

    2015-10-13

    Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

  13. Hippocampus discovery First steps

    Directory of Open Access Journals (Sweden)

    Eliasz Engelhardt

    Full Text Available The first steps of the discovery, and the main discoverers, of the hippocampus are outlined. Arantius was the first to describe a structure he named "hippocampus" or "white silkworm". Despite numerous controversies and alternate designations, the term hippocampus has prevailed until this day as the most widely used term. Duvernoy provided an illustration of the hippocampus and surrounding structures, considered the first by most authors, which appeared more than one and a half century after Arantius' description. Some authors have identified other drawings and texts which they claim predate Duvernoy's depiction, in studies by Vesalius, Varolio, Willis, and Eustachio, albeit unconvincingly. Considering the definition of the hippocampal formation as comprising the hippocampus proper, dentate gyrus and subiculum, Arantius and Duvernoy apparently described the gross anatomy of this complex. The pioneering studies of Arantius and Duvernoy revealed a relatively small hidden formation that would become one of the most valued brain structures.

  14. Radically enhanced molecular recognition

    KAUST Repository

    Trabolsi, Ali; Khashab, Niveen M.; Fahrenbach, Albert C.; Friedman, Douglas C.; Colvin, Michael T.; Coti, Karla K.; Bení tez, Diego S.; Tkatchouk, Ekaterina; Olsen, John Carl; Belowich, Matthew E.; Carmieli, Raanan; Khatib, Hussam A.; Goddard, William Andrew III; Wasielewski, Michael R.; Stoddart, Fraser Fraser Raser

    2009-01-01

    The tendency for viologen radical cations to dimerize has been harnessed to establish a recognition motif based on their ability to form extremely strong inclusion complexes with cyclobis(paraquat-p-phenylene) in its diradical dicationic redox state. This previously unreported complex involving three bipyridinium cation radicals increases the versatility of host-guest chemistry, extending its practice beyond the traditional reliance on neutral and charged guests and hosts. In particular, transporting the concept of radical dimerization into the field of mechanically interlocked molecules introduces a higher level of control within molecular switches and machines. Herein, we report that bistable and tristable [2]rotaxanes can be switched by altering electrochemical potentials. In a tristable [2]rotaxane composed of a cyclobis(paraquat-p-phenylene) ring and a dumbbell with tetrathiafulvalene, dioxynaphthalene and bipyridinium recognition sites, the position of the ring can be switched. On oxidation, it moves from the tetrathiafulvalene to the dioxynaphthalene, and on reduction, to the bipyridinium radical cation, provided the ring is also reduced simultaneously to the diradical dication. © 2010 Macmillan Publishers Limited. All rights reserved.

  15. Radically enhanced molecular recognition

    KAUST Repository

    Trabolsi, Ali

    2009-12-17

    The tendency for viologen radical cations to dimerize has been harnessed to establish a recognition motif based on their ability to form extremely strong inclusion complexes with cyclobis(paraquat-p-phenylene) in its diradical dicationic redox state. This previously unreported complex involving three bipyridinium cation radicals increases the versatility of host-guest chemistry, extending its practice beyond the traditional reliance on neutral and charged guests and hosts. In particular, transporting the concept of radical dimerization into the field of mechanically interlocked molecules introduces a higher level of control within molecular switches and machines. Herein, we report that bistable and tristable [2]rotaxanes can be switched by altering electrochemical potentials. In a tristable [2]rotaxane composed of a cyclobis(paraquat-p-phenylene) ring and a dumbbell with tetrathiafulvalene, dioxynaphthalene and bipyridinium recognition sites, the position of the ring can be switched. On oxidation, it moves from the tetrathiafulvalene to the dioxynaphthalene, and on reduction, to the bipyridinium radical cation, provided the ring is also reduced simultaneously to the diradical dication. © 2010 Macmillan Publishers Limited. All rights reserved.

  16. Speech Recognition on Mobile Devices

    DEFF Research Database (Denmark)

    Tan, Zheng-Hua; Lindberg, Børge

    2010-01-01

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

  17. Molecular Mechanisms of Odor Recognition

    National Research Council Canada - National Science Library

    Anholt, Robert

    2000-01-01

    .... We characterized the transduction pathway for the recognition of pheromones in the vomeronasal organ and also characterized subpopulations of olfactory neurons expressing different axonal G proteins...

  18. 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

  19. Sudden Event Recognition: A Survey

    Directory of Open Access Journals (Sweden)

    Mohd Asyraf Zulkifley

    2013-08-01

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

  20. Astronomical sketching a step-by-step introduction

    CERN Document Server

    Handy, Richard; Perez, Jeremy; Rix, Erika; Robbins, Sol

    2007-01-01

    This book presents the amateur with fine examples of astronomical sketches and step-by-step tutorials in each medium, from pencil to computer graphics programs. This unique book can teach almost anyone to create beautiful sketches of celestial objects.

  1. Vehicle license plate recognition based on geometry restraints and multi-feature decision

    Science.gov (United States)

    Wu, Jianwei; Wang, Zongyue

    2005-10-01

    Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

  2. Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

    Science.gov (United States)

    Yao, Shoukui; Qin, Xiaojuan

    2018-02-01

    Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

  3. Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

    Science.gov (United States)

    Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

    2013-01-01

    Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

  4. Medial prefrontal cortex role in recognition memory in rodents.

    Science.gov (United States)

    Morici, Juan Facundo; Bekinschtein, Pedro; Weisstaub, Noelia V

    2015-10-01

    The study of the neurobiology of recognition memory, defined by the integration of the different components of experiences that support recollection of past experiences have been a challenge for memory researches for many years. In the last twenty years, with the development of the spontaneous novel object recognition task and all its variants this has started to change. The features of recognition memory include a particular object or person ("what"), the context in which the experience took place, which can be the arena itself or the location within a particular arena ("where") and the particular time at which the event occurred ("when"). This definition instead of the historical anthropocentric one allows the study of this type of episodic memory in animal models. Some forms of recognition memory that require integration of different features recruit the medial prefrontal cortex. Focusing on findings from spontaneous recognition memory tasks performed by rodents, this review concentrates on the description of previous works that have examined the role that the medial prefrontal cortex has on the different steps of recognition memory. We conclude that this structure, independently of the task used, is required at different memory stages when the task cannot be solved by a single item strategy. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Chinese character recognition based on Gabor feature extraction and CNN

    Science.gov (United States)

    Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

    2018-03-01

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

  6. STEP and fundamental physics

    Science.gov (United States)

    Overduin, James; Everitt, Francis; Worden, Paul; Mester, John

    2012-09-01

    The Satellite Test of the Equivalence Principle (STEP) will advance experimental limits on violations of Einstein's equivalence principle from their present sensitivity of two parts in 1013 to one part in 1018 through multiple comparison of the motions of four pairs of test masses of different compositions in a drag-free earth-orbiting satellite. We describe the experiment, its current status and its potential implications for fundamental physics. Equivalence is at the heart of general relativity, our governing theory of gravity and violations are expected in most attempts to unify this theory with the other fundamental interactions of physics, as well as in many theoretical explanations for the phenomenon of dark energy in cosmology. Detection of such a violation would be equivalent to the discovery of a new force of nature. A null result would be almost as profound, pushing upper limits on any coupling between standard-model fields and the new light degrees of freedom generically predicted by these theories down to unnaturally small levels.

  7. STEP and fundamental physics

    International Nuclear Information System (INIS)

    Overduin, James; Everitt, Francis; Worden, Paul; Mester, John

    2012-01-01

    The Satellite Test of the Equivalence Principle (STEP) will advance experimental limits on violations of Einstein's equivalence principle from their present sensitivity of two parts in 10 13 to one part in 10 18 through multiple comparison of the motions of four pairs of test masses of different compositions in a drag-free earth-orbiting satellite. We describe the experiment, its current status and its potential implications for fundamental physics. Equivalence is at the heart of general relativity, our governing theory of gravity and violations are expected in most attempts to unify this theory with the other fundamental interactions of physics, as well as in many theoretical explanations for the phenomenon of dark energy in cosmology. Detection of such a violation would be equivalent to the discovery of a new force of nature. A null result would be almost as profound, pushing upper limits on any coupling between standard-model fields and the new light degrees of freedom generically predicted by these theories down to unnaturally small levels. (paper)

  8. One-step microlithography

    Science.gov (United States)

    Kahlen, Franz-Josef; Sankaranarayanan, Srikanth; Kar, Aravinda

    1997-09-01

    Subject of this investigation is a one-step rapid machining process to create miniaturized 3D parts, using the original sample material. An experimental setup where metal powder is fed to the laser beam-material interaction region has been built. The powder is melted and forms planar, 2D geometries as the substrate is moved under the laser beam in XY- direction. After completing the geometry in the plane, the substrate is displaced in Z-direction, and a new layer of material is placed on top of the just completed deposit. By continuous repetition of this process, 3D parts wee created. In particular, the impact of the focal spot size of the high power laser beam on the smallest achievable structures was investigated. At a translation speed of 51 mm/s a minimum material thickness of 590 micrometers was achieved. Also, it was shown that a small Z-displacement has a negligible influence on the continuity of the material deposition over this power range. A high power CO2 laser was used as energy source, the material powder under investigation was stainless steel SS304L. Helium was used as shield gas at a flow rate of 15 1/min. The incident CO2 laser beam power was varied between 300 W and 400 W, with the laser beam intensity distribute in a donut mode. The laser beam was focused to a focal diameter of 600 (Mu) m.

  9. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara; Rockwood, Alyn; Ghanem, Bernard

    2015-01-01

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  10. Iris Recognition Using Wavelet

    Directory of Open Access Journals (Sweden)

    Khaliq Masood

    2013-08-01

    Full Text Available Biometric systems are getting more attention in the present era. Iris recognition is one of the most secure and authentic among the other biometrics and this field demands more authentic, reliable and fast algorithms to implement these biometric systems in real time. In this paper, an efficient localization technique is presented to identify pupil and iris boundaries using histogram of the iris image. Two small portions of iris have been used for polar transformation to reduce computational time and to increase the efficiency of the system. Wavelet transform is used for feature vector generation. Rotation of iris is compensated without shifts in the iris code. System is tested on Multimedia University Iris Database and results show that proposed system has encouraging performance.

  11. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara

    2015-10-15

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  12. Step 1: Learn about Diabetes

    Science.gov (United States)

    ... please turn JavaScript on. Feature: Type 2 Diabetes Step 1: Learn About Diabetes Past Issues / Fall 2014 ... the whole family healthy! Here are four key steps to help you control your diabetes and live ...

  13. General tensor discriminant analysis and gabor features for gait recognition.

    Science.gov (United States)

    Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

    2007-10-01

    The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine

  14. SPAR-H Step-by-Step Guidance

    Energy Technology Data Exchange (ETDEWEB)

    April M. Whaley; Dana L. Kelly; Ronald L. Boring; William J. Galyean

    2012-06-01

    Step-by-step guidance was developed recently at Idaho National Laboratory for the US Nuclear Regulatory Commission on the use of the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method for quantifying Human Failure Events (HFEs). This work was done to address SPAR-H user needs, specifically requests for additional guidance on the proper application of various aspects of the methodology. This paper overviews the steps of the SPAR-H analysis process and highlights some of the most important insights gained during the development of the step-by-step directions. This supplemental guidance for analysts is applicable when plant-specific information is available, and goes beyond the general guidance provided in existing SPAR-H documentation. The steps highlighted in this paper are: Step-1, Categorizing the HFE as Diagnosis and/or Action; Step-2, Rate the Performance Shaping Factors; Step-3, Calculate PSF-Modified HEP; Step-4, Accounting for Dependence, and; Step-5, Minimum Value Cutoff.

  15. The Legal Recognition of Sign Languages

    Science.gov (United States)

    De Meulder, Maartje

    2015-01-01

    This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

  16. Unequal recognition, misrecognition and injustice

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2012-01-01

    by the state of religious minorities. It argues that state–religion relations can be analysed as relations of recognition, which are not only unequal but also multi-dimensional, and that it is difficult to answer the question whether multi-dimensional recognitive inequalities are unjust or wrong if one...

  17. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; van den Biggelaar, Olivier

    As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss

  18. Infants' Recognition Memory for Hue

    Science.gov (United States)

    Bornstein, Marc H.

    1976-01-01

    Fifty 4-month-old infants were habituated to one wavelength of light and then tested for recognition with the original and two new spectral lights. After short- and long-term delays with different types of retroactive interference, the results indicated that the infants' recognition memory for hue was quite resilient to interference or delay. (JMB)

  19. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

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

    2010-01-01

    Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is

  20. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2010-01-01

    Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face

  1. FILTWAM and Voice Emotion Recognition

    NARCIS (Netherlands)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2014-01-01

    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone

  2. Multiple stage miniature stepping motor

    International Nuclear Information System (INIS)

    Niven, W.A.; Shikany, S.D.; Shira, M.L.

    1981-01-01

    A stepping motor comprising a plurality of stages which may be selectively activated to effect stepping movement of the motor, and which are mounted along a common rotor shaft to achieve considerable reduction in motor size and minimum diameter, whereby sequential activation of the stages results in successive rotor steps with direction being determined by the particular activating sequence followed

  3. Online handwritten mathematical expression recognition

    Science.gov (United States)

    Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

    2007-01-01

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

  4. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Souvenir Richard

    2009-01-01

    Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  5. Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report.

    Science.gov (United States)

    Poth, Christian H; Schneider, Werner X

    2016-01-01

    Human vision is organized in discrete processing episodes (e.g., eye fixations or task-steps). Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM), which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of 10 letters and reported as many as possible after a retention interval (whole report). Next, participants viewed a probe letter and indicated whether it had been one of the 10 letters (probe recognition). In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters) compared with non-encoded letters (non-reported letters). Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2, participants reported only one of 10 letters (partial report) and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

  6. Episodic Short-Term Recognition Requires Encoding into Visual Working Memory: Evidence from Probe Recognition after Letter Report

    Directory of Open Access Journals (Sweden)

    Christian H. Poth

    2016-09-01

    Full Text Available Human vision is organized in discrete processing episodes (e.g. eye fixations or task-steps. Object information must be transmitted across episodes to enable episodic short-term recognition: recognizing whether a current object has been seen in a previous episode. We ask whether episodic short-term recognition presupposes that objects have been encoded into capacity-limited visual working memory (VWM, which retains visual information for report. Alternatively, it could rely on the activation of visual features or categories that occurs before encoding into VWM. We assessed the dependence of episodic short-term recognition on VWM by a new paradigm combining letter report and probe recognition. Participants viewed displays of ten letters and reported as many as possible after a retention interval (whole report. Next, participants viewed a probe letter and indicated whether it had been one of the ten letters (probe recognition. In Experiment 1, probe recognition was more accurate for letters that had been encoded into VWM (reported letters compared with non-encoded letters (non-reported letters. Interestingly, those letters that participants reported in their whole report had been near to one another within the letter displays. This suggests that the encoding into VWM proceeded in a spatially clustered manner. In Experiment 2 participants reported only one of ten letters (partial report and probes either referred to this letter, to letters that had been near to it, or far from it. Probe recognition was more accurate for near than for far letters, although none of these letters had to be reported. These findings indicate that episodic short-term recognition is constrained to a small number of simultaneously presented objects that have been encoded into VWM.

  7. 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.

  8. Effects of walking speed on the step-by-step control of step width.

    Science.gov (United States)

    Stimpson, Katy H; Heitkamp, Lauren N; Horne, Joscelyn S; Dean, Jesse C

    2018-02-08

    Young, healthy adults walking at typical preferred speeds use step-by-step adjustments of step width to appropriately redirect their center of mass motion and ensure mediolateral stability. However, it is presently unclear whether this control strategy is retained when walking at the slower speeds preferred by many clinical populations. We investigated whether the typical stabilization strategy is influenced by walking speed. Twelve young, neurologically intact participants walked on a treadmill at a range of prescribed speeds (0.2-1.2 m/s). The mediolateral stabilization strategy was quantified as the proportion of step width variance predicted by the mechanical state of the pelvis throughout a step (calculated as R 2 magnitude from a multiple linear regression). Our ability to accurately predict the upcoming step width increased over the course of a step. The strength of the relationship between step width and pelvis mechanics at the start of a step was reduced at slower speeds. However, these speed-dependent differences largely disappeared by the end of a step, other than at the slowest walking speed (0.2 m/s). These results suggest that mechanics-dependent adjustments in step width are a consistent component of healthy gait across speeds and contexts. However, slower walking speeds may ease this control by allowing mediolateral repositioning of the swing leg to occur later in a step, thus encouraging slower walking among clinical populations with limited sensorimotor control. Published by Elsevier Ltd.

  9. Specification for projects of radiogeologic recognition

    International Nuclear Information System (INIS)

    1979-01-01

    This instruction is a guidance to achievement of radiogeologic recognition projects. The radiogeologic recognition is a prospecting method that join the classic geologic recognition with measures of rock radioactivity. (C.M.)

  10. Autonomy, recognition and education

    Directory of Open Access Journals (Sweden)

    Angelo Vitório Cenci

    2015-01-01

    Full Text Available This paper addresses Honneth’s concept of autonomy from two dimensions of his work, distinct, though inseparable. The first one is suggested through the subject’s positive practical self-relation linked to the patterns of reciprocal recognition of love, right and social esteem; the second is formulated as non-centered autonomy opposed to the present-day criticism of the modern autonomous subject encompassing three levels, namely: the capacity of linguistic articulation, the narrative coherence of life and the complementation of being guided by principles with some criteria of moral sensitivity to the context. We defend the position that, by metaphysically anchoring the concept of autonomy onto the intersubjective assumptions of his/her theory of the subject, and exploring it linked to the subject’s positive practical self-relation and to a non-centered meaning, Honneth has managed to renew it, which allows drawing important consequences of such effort to the field of education.

  11. Pattern recognition in spectra

    International Nuclear Information System (INIS)

    Gebran, M; Paletou, F

    2017-01-01

    We present a new automated procedure that simultaneously derives the effective temperature T eff , surface gravity log g , metallicity [ Fe/H ], and equatorial projected rotational velocity v e sin i for stars. The procedure is inspired by the well-known PCA-based inversion of spectropolarimetric full-Stokes solar data, which was used both for Zeeman and Hanle effects. The efficiency and accuracy of this procedure have been proven for FGK, A, and late type dwarf stars of K and M spectral types. Learning databases are generated from the Elodie stellar spectra library using observed spectra for which fundamental parameters were already evaluated or with synthetic data. The synthetic spectra are calculated using ATLAS9 model atmospheres. This technique helped us to detect many peculiar stars such as Am, Ap, HgMn, SiEuCr and binaries. This fast and efficient technique could be used every time a pattern recognition is needed. One important application is the understanding of the physical properties of planetary surfaces by comparing aboard instrument data to synthetic ones. (paper)

  12. Vision-Based Navigation and Recognition

    National Research Council Canada - National Science Library

    Rosenfeld, Azriel

    1998-01-01

    .... (4) Invariants: both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

  13. Vision-Based Navigation and Recognition

    National Research Council Canada - National Science Library

    Rosenfeld, Azriel

    1996-01-01

    .... (4) Invariants -- both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

  14. Recognition Using Classification and Segmentation Scoring

    National Research Council Canada - National Science Library

    Kimball, Owen; Ostendorf, Mari; Rohlicek, Robin

    1992-01-01

    .... We describe an approach to connected word recognition that allows the use of segmental information through an explicit decomposition of the recognition criterion into classification and segmentation scoring...

  15. 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...

  16. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

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

  17. Facial recognition in education system

    Science.gov (United States)

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

    2017-11-01

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

  18. Iris recognition via plenoptic imaging

    Science.gov (United States)

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

    2017-11-07

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

  19. Face Recognition using Approximate Arithmetic

    DEFF Research Database (Denmark)

    Marso, Karol

    Face recognition is image processing technique which aims to identify human faces and found its use in various different fields for example in security. Throughout the years this field evolved and there are many approaches and many different algorithms which aim to make the face recognition as effective...... processing applications the results do not need to be completely precise and use of the approximate arithmetic can lead to reduction in terms of delay, space and power consumption. In this paper we examine possible use of approximate arithmetic in face recognition using Eigenfaces algorithm....

  20. Evaluating music emotion recognition:Lessons from music genre recognition?

    OpenAIRE

    Sturm, Bob L.

    2013-01-01

    A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER syste...

  1. Facial expressions recognition with an emotion expressive robotic head

    Science.gov (United States)

    Doroftei, I.; Adascalitei, F.; Lefeber, D.; Vanderborght, B.; Doroftei, I. A.

    2016-08-01

    The purpose of this study is to present the preliminary steps in facial expressions recognition with a new version of an expressive social robotic head. So, in a first phase, our main goal was to reach a minimum level of emotional expressiveness in order to obtain nonverbal communication between the robot and human by building six basic facial expressions. To evaluate the facial expressions, the robot was used in some preliminary user studies, among children and adults.

  2. Spoken word recognition without a TRACE

    Science.gov (United States)

    Hannagan, Thomas; Magnuson, James S.; Grainger, Jonathan

    2013-01-01

    How do we map the rapid input of spoken language onto phonological and lexical representations over time? Attempts at psychologically-tractable computational models of spoken word recognition tend either to ignore time or to transform the temporal input into a spatial representation. TRACE, a connectionist model with broad and deep coverage of speech perception and spoken word recognition phenomena, takes the latter approach, using exclusively time-specific units at every level of representation. TRACE reduplicates featural, phonemic, and lexical inputs at every time step in a large memory trace, with rich interconnections (excitatory forward and backward connections between levels and inhibitory links within levels). As the length of the memory trace is increased, or as the phoneme and lexical inventory of the model is increased to a realistic size, this reduplication of time- (temporal position) specific units leads to a dramatic proliferation of units and connections, begging the question of whether a more efficient approach is possible. Our starting point is the observation that models of visual object recognition—including visual word recognition—have grappled with the problem of spatial invariance, and arrived at solutions other than a fully-reduplicative strategy like that of TRACE. This inspires a new model of spoken word recognition that combines time-specific phoneme representations similar to those in TRACE with higher-level representations based on string kernels: temporally independent (time invariant) diphone and lexical units. This reduces the number of necessary units and connections by several orders of magnitude relative to TRACE. Critically, we compare the new model to TRACE on a set of key phenomena, demonstrating that the new model inherits much of the behavior of TRACE and that the drastic computational savings do not come at the cost of explanatory power. PMID:24058349

  3. Algorithms for adaptive nonlinear pattern recognition

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric; Key, Gary

    2011-09-01

    In Bayesian pattern recognition research, static classifiers have featured prominently in the literature. A static classifier is essentially based on a static model of input statistics, thereby assuming input ergodicity that is not realistic in practice. Classical Bayesian approaches attempt to circumvent the limitations of static classifiers, which can include brittleness and narrow coverage, by training extensively on a data set that is assumed to cover more than the subtense of expected input. Such assumptions are not realistic for more complex pattern classification tasks, for example, object detection using pattern classification applied to the output of computer vision filters. In contrast, we have developed a two step process, that can render the majority of static classifiers adaptive, such that the tracking of input nonergodicities is supported. Firstly, we developed operations that dynamically insert (or resp. delete) training patterns into (resp. from) the classifier's pattern database, without requiring that the classifier's internal representation of its training database be completely recomputed. Secondly, we developed and applied a pattern replacement algorithm that uses the aforementioned pattern insertion/deletion operations. This algorithm is designed to optimize the pattern database for a given set of performance measures, thereby supporting closed-loop, performance-directed optimization. This paper presents theory and algorithmic approaches for the efficient computation of adaptive linear and nonlinear pattern recognition operators that use our pattern insertion/deletion technology - in particular, tabular nearest-neighbor encoding (TNE) and lattice associative memories (LAMs). Of particular interest is the classification of nonergodic datastreams that have noise corruption with time-varying statistics. The TNE and LAM based classifiers discussed herein have been successfully applied to the computation of object classification in hyperspectral

  4. 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

  5. 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.

  6. HTSC-Josephson step contacts

    International Nuclear Information System (INIS)

    Herrmann, K.

    1994-03-01

    In this work the properties of josephson step contacts are investigated. After a short introduction into Josephson step contacts the structure, properties and the Josphson contacts of YBa 2 Cu 3 O 7-x high-T c superconductors is presented. The fabrication of HTSC step contacts and the microstructure is discussed. The electric properties of these contacts are measured together with the Josephson emission and the magnetic field dependence. The temperature dependence of the stationary transport properties is given. (WL)

  7. Image simulation for automatic license plate recognition

    Science.gov (United States)

    Bala, Raja; Zhao, Yonghui; Burry, Aaron; Kozitsky, Vladimir; Fillion, Claude; Saunders, Craig; Rodríguez-Serrano, José

    2012-01-01

    Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.

  8. Handwritten Sindhi Character Recognition Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Shafique Ahmed Awan

    2018-01-01

    Full Text Available OCR (OpticalCharacter Recognition is a technology in which text image is used to understand and write text by machines. The work on languages containing isolated characters such as German, English, French and others is at its peak. The OCR and ICR (Intelligent Character Recognition research in Sindhi script is currently at in starting stages and not sufficient work have been cited in this area even though Sindhi language is rich in culture and history. This paper presents one of the initial steps in recognizing Sindhi handwritten characters. The isolated characters of Sindhi script written by thesubjects have been recognized. The various subjects were asked to write Sindhi characters in unconstrained form and then the written samples were collected and scanned through a flatbed scanner. The scanned documents were preprocessedwith the help of binary conversion, removing noise by pepper noise and the lines were segmented with the help of horizontal profile technique. The segmented lines were used to extract characters from scanned pages.This character segmentation was done by vertical projection. The extracted characters have been used to extract features so that the characters can be classified easily. Zoning was used for the feature extraction technique. For the classification, neural network has been used. The recognized characters converted into editable text with an average accuracy of 85%.

  9. Feature Vector Construction Method for IRIS Recognition

    Science.gov (United States)

    Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

    2017-05-01

    One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

  10. The NIST Step Class Library (Step Into the Future)

    Science.gov (United States)

    1990-09-01

    Figure 6. Excerpt from a STEP exclange file based on the Geometry model 1be NIST STEP Class Libary Page 13 An issue of concern in this...Scheifler, R., Gettys, J., and Newman, P., X Window System: C Library and Protocol Reference. Digital Press, Bedford, Mass, 1988. [Schenck90] Schenck, D

  11. Step-by-Step Visual Manuals: Design and Development

    Science.gov (United States)

    Urata, Toshiyuki

    2004-01-01

    The types of handouts and manuals that are used in technology training vary. Some describe procedures in a narrative way without graphics; some employ step-by-step instructions with screen captures. According to Thirlway (1994), a training manual should be like a tutor that permits a student to learn at his own pace and gives him confidence for…

  12. On the Convexity of Step out - Step in Sequencing Games

    NARCIS (Netherlands)

    Musegaas, Marieke; Borm, Peter; Quant, Marieke

    2016-01-01

    The main result of this paper is the convexity of Step out - Step in (SoSi) sequencing games, a class of relaxed sequencing games first analyzed by Musegaas, Borm, and Quant (2015). The proof makes use of a polynomial time algorithm determining the value and an optimal processing order for an

  13. Valve cam design using numerical step-by-step method

    OpenAIRE

    Vasilyev, Aleksandr; Bakhracheva, Yuliya; Kabore, Ousman; Zelenskiy, Yuriy

    2014-01-01

    This article studies the numerical step-by-step method of cam profile design. The results of the study are used for designing the internal combustion engine valve gear. This method allows to profile the peak efficiency of cams in view of many restrictions, connected with valve gear serviceability and reliability.

  14. The bounded proof property via step algebras and step frames

    NARCIS (Netherlands)

    Bezhanishvili, N.; Ghilardi, Silvio

    2013-01-01

    We develop a semantic criterion for a specific rule-based calculus Ax axiomatizing a given logic L to have the so-called bounded proof property. This property is a kind of an analytic subformula property limiting the proof search space. Our main tools are one-step frames and one-step algebras. These

  15. Leading Change Step-by-Step: Tactics, Tools, and Tales

    Science.gov (United States)

    Spiro, Jody

    2010-01-01

    "Leading Change Step-by-Step" offers a comprehensive and tactical guide for change leaders. Spiro's approach has been field-tested for more than a decade and proven effective in a wide variety of public sector organizations including K-12 schools, universities, international agencies and non-profits. The book is filled with proven tactics for…

  16. Indoor navigation by image recognition

    Science.gov (United States)

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

    2017-07-01

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

  17. Pattern recognition and string matching

    CERN Document Server

    Cheng, Xiuzhen

    2002-01-01

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

  18. License plate recognition (phase B).

    Science.gov (United States)

    2010-06-01

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

  19. Similarity measures for face recognition

    CERN Document Server

    Vezzetti, Enrico

    2015-01-01

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

  20. Sugar recognition by human galactokinase

    Directory of Open Access Journals (Sweden)

    Timson David J

    2003-11-01

    Full Text Available Abstract Background Galactokinase catalyses the first committed step of galactose catabolism in which the sugar is phosphorylated at the expense of MgATP. Recent structural studies suggest that the enzyme makes several contacts with galactose – five side chain and two main chain hydrogen bonds. Furthermore, it has been suggested that inhibition of galactokinase may help sufferers of the genetic disease classical galactosemia which is caused by defects in another enzyme of the pathway galactose-1-phosphate uridyl transferase. Galactokinases from different sources have a range of substrate specificities and a diversity of kinetic mechanisms. Therefore only studies on the human enzyme are likely to be of value in the design of therapeutically useful inhibitors. Results Using recombinant human galactokinase expressed in and purified from E. coli we have investigated the sugar specificity of the enzyme and the kinetic consequences of mutating residues in the sugar-binding site in order to improve our understanding of substrate recognition by this enzyme. D-galactose and 2-deoxy-D-galactose are substrates for the enzyme, but N-acetyl-D-galactosamine, L-arabinose, D-fucose and D-glucose are all not phosphorylated. Mutation of glutamate-43 (which forms a hydrogen bond to the hydroxyl group attached to carbon 6 of galactose to alanine results in only minor changes in the kinetic parameters of the enzyme. Mutation of this residue to glycine causes a ten-fold drop in the turnover number. In contrast, mutation of histidine 44 to either alanine or isoleucine results in insoluble protein following expression in E. coli. Alteration of the residue that makes hydrogen bonds to the hydroxyl attached to carbons 3 and 4 (aspartate 46 results in an enzyme that although soluble is essentially inactive. Conclusions The enzyme is tolerant to small changes at position 2 of the sugar ring, but not at positions 4 and 6. The results from site directed mutagenesis could

  1. Real-Time Hand Posture Recognition Using a Range Camera

    Science.gov (United States)

    Lahamy, Herve

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

  2. [Neurological disease and facial recognition].

    Science.gov (United States)

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

    2012-07-01

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

  3. Voice congruency facilitates word recognition.

    Directory of Open Access Journals (Sweden)

    Sandra Campeanu

    Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  4. Voice congruency facilitates word recognition.

    Science.gov (United States)

    Campeanu, Sandra; Craik, Fergus I M; Alain, Claude

    2013-01-01

    Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs) while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent) varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  5. A small step for mankind

    NARCIS (Netherlands)

    Huizing, C.; Koymans, R.L.C.; Kuiper, R.; Dams, D.; Hannemann, U.; Steffen, M.

    2010-01-01

    For many programming languages, the only formal semantics published is an SOS big-step semantics. Such a semantics is not suited for investigations that observe intermediate states, such as invariant techniques. In this paper, a construction is proposed that generates automatically a small-step SOS

  6. Grief: Difficult Times, Simple Steps.

    Science.gov (United States)

    Waszak, Emily Lane

    This guide presents techniques to assist others in coping with the loss of a loved one. Using the language of 9 layperson, the book contains more than 100 tips for caregivers or loved ones. A simple step is presented on each page, followed by reasons and instructions for each step. Chapters include: "What to Say"; "Helpful Things to Do"; "Dealing…

  7. Comparing Face Detection and Recognition Techniques

    OpenAIRE

    Korra, Jyothi

    2016-01-01

    This paper implements and compares different techniques for face detection and recognition. One is find where the face is located in the images that is face detection and second is face recognition that is identifying the person. We study three techniques in this paper: Face detection using self organizing map (SOM), Face recognition by projection and nearest neighbor and Face recognition using SVM.

  8. Optimal pattern synthesis for speech recognition based on principal component analysis

    Science.gov (United States)

    Korsun, O. N.; Poliyev, A. V.

    2018-02-01

    The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

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

    Directory of Open Access Journals (Sweden)

    Marco Zennaro

    2010-12-01

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

  10. Microprocessor controller for stepping motors

    International Nuclear Information System (INIS)

    Strait, B.G.; Thuot, M.E.

    1977-01-01

    A new concept for digital computer control of multiple stepping motors which operate in a severe electromagnetic pulse environment is presented. The motors position mirrors in the beam-alignment system of a 100-kJ CO 2 laser. An asynchronous communications channel of a computer is used to send coded messages, containing the motor address and stepping-command information, to the stepping-motor controller in a bit serial format over a fiber-optics communications link. The addressed controller responds by transmitting to the computer its address and other motor information, thus confirming the received message. Each controller is capable of controlling three stepping motors. The controller contains the fiber-optics interface, a microprocessor, and the stepping-motor driven circuits. The microprocessor program, which resides in an EPROM, decodes the received messages, transmits responses, performs the stepping-motor sequence logic, maintains motor-position information, and monitors the motor's reference switch. For multiple stepping-motor application, the controllers are connected in a daisy chain providing control of many motors from one asynchronous communications channel of the computer

  11. Adsorption-induced step formation

    DEFF Research Database (Denmark)

    Thostrup, P.; Christoffersen, Ebbe; Lorensen, Henrik Qvist

    2001-01-01

    Through an interplay between density functional calculations, Monte Carlo simulations and scanning tunneling microscopy experiments, we show that an intermediate coverage of CO on the Pt(110) surface gives rise to a new rough equilibrium structure with more than 50% step atoms. CO is shown to bind...... so strongly to low-coordinated Pt atoms that it can break Pt-Pt bonds and spontaneously form steps on the surface. It is argued that adsorption-induced step formation may be a general effect, in particular at high gas pressures and temperatures....

  12. Step sites in syngas catalysis

    DEFF Research Database (Denmark)

    Rostrup-Nielsen, J.; Nørskov, Jens Kehlet

    2006-01-01

    Step sites play an important role in many catalytic reactions. This paper reviews recent results on metal catalysts for syngas reactions with emphasis on steam reforming. Modern characterization techniques (STEM, HREM...) and theoretical calculations (DFT) has allowed a more quantitative explanat......Step sites play an important role in many catalytic reactions. This paper reviews recent results on metal catalysts for syngas reactions with emphasis on steam reforming. Modern characterization techniques (STEM, HREM...) and theoretical calculations (DFT) has allowed a more quantitative...... explanation of the impact of step sites on catalyst activity and side reactions such as carbon formation. This leads to a discussion of principles for catalyst promotion....

  13. Bidirectional Modulation of Recognition Memory.

    Science.gov (United States)

    Ho, Jonathan W; Poeta, Devon L; Jacobson, Tara K; Zolnik, Timothy A; Neske, Garrett T; Connors, Barry W; Burwell, Rebecca D

    2015-09-30

    Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30-40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30-40 Hz was not effective in increasing exploration of novel images. Stimulation at 10-15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. Significance statement: Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that stimulation of

  14. Cognitive object recognition system (CORS)

    Science.gov (United States)

    Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

    2010-04-01

    We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

  15. An audiovisual emotion recognition system

    Science.gov (United States)

    Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

    2007-12-01

    Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

  16. 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.

  17. The primary steps of photosynthesis

    International Nuclear Information System (INIS)

    Fleming, G.R.; Van Grondelle, R.

    1996-01-01

    The two important initial steps of photosynthesis-electron transfer and energy transfer occur with great speed and efficiency. New techniques in laser optics and genetic engineering age helping us to understand why. (author). 24 refs. 8 figs

  18. 7 Steps to Aging Well

    Science.gov (United States)

    ... Issue Past Issues Special Section 7 Steps to Aging Well Past Issues / Winter 2007 Table of Contents ... Exercise: A Guide from the National Institute on Aging is a publication from NIA that has strength, ...

  19. Rough-fuzzy pattern recognition applications in bioinformatics and medical imaging

    CERN Document Server

    Maji, Pradipta

    2012-01-01

    Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems dev

  20. Recognition and characterization of unstructured environmental sounds

    Science.gov (United States)

    Chu, Selina

    2011-12-01

    Environmental sounds are what we hear everyday, or more generally sounds that surround us ambient or background audio. Humans utilize both vision and hearing to respond to their surroundings, a capability still quite limited in machine processing. The first step toward achieving multimodal input applications is the ability to process unstructured audio and recognize audio scenes (or environments). Such ability would have applications in content analysis and mining of multimedia data or improving robustness in context aware applications through multi-modality, such as in assistive robotics, surveillances, or mobile device-based services. The goal of this thesis is on the characterization of unstructured environmental sounds for understanding and predicting the context surrounding of an agent or device. Most research on audio recognition has focused primarily on speech and music. Less attention has been paid to the challenges and opportunities for using audio to characterize unstructured audio. My research focuses on investigating challenging issues in characterizing unstructured environmental audio and to develop novel algorithms for modeling the variations of the environment. The first step in building a recognition system for unstructured auditory environment was to investigate on techniques and audio features for working with such audio data. We begin by performing a study that explore suitable features and the feasibility of designing an automatic environment recognition system using audio information. In my initial investigation to explore the feasibility of designing an automatic environment recognition system using audio information, I have found that traditional recognition and feature extraction for audio were not suitable for environmental sound, as they lack any type of structures, unlike those of speech and music which contain formantic and harmonic structures, thus dispelling the notion that traditional speech and music recognition techniques can simply

  1. On speech recognition during anaesthesia

    DEFF Research Database (Denmark)

    Alapetite, Alexandre

    2007-01-01

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

  2. a Two-Step Classification Approach to Distinguishing Similar Objects in Mobile LIDAR Point Clouds

    Science.gov (United States)

    He, H.; Khoshelham, K.; Fraser, C.

    2017-09-01

    Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

  3. A TWO-STEP CLASSIFICATION APPROACH TO DISTINGUISHING SIMILAR OBJECTS IN MOBILE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    H. He

    2017-09-01

    Full Text Available Nowadays, lidar is widely used in cultural heritage documentation, urban modeling, and driverless car technology for its fast and accurate 3D scanning ability. However, full exploitation of the potential of point cloud data for efficient and automatic object recognition remains elusive. Recently, feature-based methods have become very popular in object recognition on account of their good performance in capturing object details. Compared with global features describing the whole shape of the object, local features recording the fractional details are more discriminative and are applicable for object classes with considerable similarity. In this paper, we propose a two-step classification approach based on point feature histograms and the bag-of-features method for automatic recognition of similar objects in mobile lidar point clouds. Lamp post, street light and traffic sign are grouped as one category in the first-step classification for their inter similarity compared with tree and vehicle. A finer classification of the lamp post, street light and traffic sign based on the result of the first-step classification is implemented in the second step. The proposed two-step classification approach is shown to yield a considerable improvement over the conventional one-step classification approach.

  4. 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

  5. Acoustic modeling for emotion recognition

    CERN Document Server

    Anne, Koteswara Rao; Vankayalapati, Hima Deepthi

    2015-01-01

     This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications – gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.

  6. 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

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

    Science.gov (United States)

    Barsics, Catherine; Brédart, Serge

    2010-11-01

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

  8. Micro-Recognition - Erving Goffman as Recognition Thinker

    DEFF Research Database (Denmark)

    Jacobsen, Michael Hviid; Kristiansen, Søren

    2009-01-01

    and civil inattention guide the conduct of people in many of their face-to-face encounters with each other. This article therefore shows how Goffman may in fact supplement many of the most fashionable and celebrated contemporary recognition theories as advanced by e.g. Nancy Fraser, Charles Taylor or Axel...

  9. Face recognition : implementation of face recognition on AMIGO

    NARCIS (Netherlands)

    Geelen, M.J.A.J.; Molengraft, van de M.J.G.; Elfring, J.

    2011-01-01

    In this (traineeship)report two possible methods of face recognition were presented. The first method describes how to detect and recognize faces by using the SURF algorithm. This algorithm finally was not used for recognizing faces, with the reason that the Eigenface algorithm was an already tested

  10. Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification

    Directory of Open Access Journals (Sweden)

    Maulidia Rahmah Hidayah

    2017-05-01

    Full Text Available The current topic that is interesting as a solution of the impact of public service improvement toward vehicle is License Plate Recognition (LPR, but it still needs to develop the research of LPR method. Some of the previous researchs showed that K-Nearest Neighbour (KNN succeed in car license plate recognition. The Objectives of this research was to determine the implementation and accuracy of Otsu Method toward license plate recognition. The method of this research was Otsu method to extract the characteristics and image of the plate into binary image and KNN as recognition classification method of each character. The development of the license plate recognition program by using Otsu method and classification of KNN is following the steps of pattern recognition, such as input and sensing, pre-processing, extraction feature Otsu method binary, segmentation, KNN classification method and post-processing by calculating the level of accuracy. The study showed that this program can recognize by 82% from 100 test plate with 93,75% of number recognition accuracy and 91,92% of letter recognition accuracy. 

  11. Inertial Sensor-Based Gait Recognition: A Review

    Science.gov (United States)

    Sprager, Sebastijan; Juric, Matjaz B.

    2015-01-01

    With the recent development of microelectromechanical systems (MEMS), inertial sensors have become widely used in the research of wearable gait analysis due to several factors, such as being easy-to-use and low-cost. Considering the fact that each individual has a unique way of walking, inertial sensors can be applied to the problem of gait recognition where assessed gait can be interpreted as a biometric trait. Thus, inertial sensor-based gait recognition has a great potential to play an important role in many security-related applications. Since inertial sensors are included in smart devices that are nowadays present at every step, inertial sensor-based gait recognition has become very attractive and emerging field of research that has provided many interesting discoveries recently. This paper provides a thorough and systematic review of current state-of-the-art in this field of research. Review procedure has revealed that the latest advanced inertial sensor-based gait recognition approaches are able to sufficiently recognise the users when relying on inertial data obtained during gait by single commercially available smart device in controlled circumstances, including fixed placement and small variations in gait. Furthermore, these approaches have also revealed considerable breakthrough by realistic use in uncontrolled circumstances, showing great potential for their further development and wide applicability. PMID:26340634

  12. Probing binding hot spots at protein-RNA recognition sites.

    Science.gov (United States)

    Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

    2016-01-29

    We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Human Activity Recognition in a Car with Embedded Devices

    Directory of Open Access Journals (Sweden)

    Danilo Burbano

    2015-11-01

    Full Text Available Detection and prediction of drowsiness is key for the implementation of intelligent vehicles aimed to prevent highway crashes. There are several approaches for such solution. In thispaper the computer vision approach will be analysed, where embedded devices (e.g.videocameras are used along with machine learning and pattern recognition techniques for implementing suitable solutions for detecting driver fatigue. Most of the research in computer vision systems focused on the analysis of blinks, this is a notable solution when it is combined with additional patterns like yawing or head motion for the recognition of drowsiness. The first step in this approach is the face recognition, where AdaBoost algorithm shows accurate results for the feature extraction, whereas regarding the detection of drowsiness the data-driven classifiers such as Support Vector Machine (SVM yields remarkable results. One underlying component for implementing a computer vision technology for detection of drowsiness is a database of spontaneous images from the Facial Action Coding System (FACS, where the classifier can be trained accordingly. This paper introduces a straightforward prototype for detection of drowsiness, where the Viola-Jones method is used for face recognition and cascade classifier is used for the detection of a contiguous sequence of eyes closed, which a reconsidered as drowsiness.

  14. Iris Recognition Using Feature Extraction of Box Counting Fractal Dimension

    Science.gov (United States)

    Khotimah, C.; Juniati, D.

    2018-01-01

    Biometrics is a science that is now growing rapidly. Iris recognition is a biometric modality which captures a photo of the eye pattern. The markings of the iris are distinctive that it has been proposed to use as a means of identification, instead of fingerprints. Iris recognition was chosen for identification in this research because every human has a special feature that each individual is different and the iris is protected by the cornea so that it will have a fixed shape. This iris recognition consists of three step: pre-processing of data, feature extraction, and feature matching. Hough transformation is used in the process of pre-processing to locate the iris area and Daugman’s rubber sheet model to normalize the iris data set into rectangular blocks. To find the characteristics of the iris, it was used box counting method to get the fractal dimension value of the iris. Tests carried out by used k-fold cross method with k = 5. In each test used 10 different grade K of K-Nearest Neighbor (KNN). The result of iris recognition was obtained with the best accuracy was 92,63 % for K = 3 value on K-Nearest Neighbor (KNN) method.

  15. Microsoft® Office Access™ 2007 Step by Step

    CERN Document Server

    Lambert, Steve; Lambert, Joan

    2009-01-01

    Experience learning made easy-and quickly teach yourself how to build database solutions with Access 2007. With Step By Step, you set the pace-building and practicing the skills you need, just when you need them! Build databases from scratch or from templatesExchange data with other databases and Office documentsCreate forms to simplify data entryUse filters and queries to find and analyze informationDesign rich reports that help make your data meaningfulHelp prevent data corruption and unauthorized access Your all-in-one learning experience includes: Files for building skills and practic

  16. Microsoft Windows Sharepoint Services 3.0 Step by Step

    CERN Document Server

    Londer, Olga; Bleeker, Todd; Coventry, Penelope

    2007-01-01

    Experience learning made easy-and quickly teach yourself how to use Windows SharePoint Services to enable effective team collaboration. With Step By Step, you set the pace-building and practicing the skills you need, just when you need them! Build your own SharePoint site with easy-to-use templatesCreate lists and libraries to store informationAdd discussion boards, wikis, and blogsSet up Document and Meeting Workspaces for easy collaborationShare calendars, contacts, and data from Microsoft Office programsCustomize your pages with Web Parts Your all-in-one learning experience includes: Fi

  17. Linear, Step by Step Managerial Performance, versus Exponential Performance

    Directory of Open Access Journals (Sweden)

    George MOLDOVEANU

    2011-04-01

    Full Text Available The paper proposes the transition from the potential management concept, which its authors approached by determining its dimension (Roşca, Moldoveanu, 2009b, to the linear, step by step performance concept, as an objective result of management process. In this way, we “answer” the theorists and practitioners, who support exponential management performance. The authors, as detractors of the exponential performance, are influenced by the current crisis (Roşca, Moldoveanu, 2009a, by the lack of organizational excellence in many companies, particularly in Romanian ones and also reaching “the finality” in the evolved companies, developed into an uncontrollable speed.

  18. Microsoft Office SharePoint Designer 2007 Step by Step

    CERN Document Server

    Coventry, Penelope

    2008-01-01

    The smart way to learn Office SharePoint Designer 2007-one step at a time! Work at your own pace through the easy numbered steps, practice files on CD, helpful hints, and troubleshooting tips to master the fundamentals of building customized SharePoint sites and applications. You'll learn how to work with Windows® SharePoint Services 3.0 and Office SharePoint Server 2007 to create Web pages complete with Cascading Style Sheets, Lists, Libraries, and customized Web parts. Then, make your site really work for you by adding data sources, including databases, XML data and Web services, and RSS fe

  19. A step-by-step methodology for enterprise interoperability projects

    Science.gov (United States)

    Chalmeta, Ricardo; Pazos, Verónica

    2015-05-01

    Enterprise interoperability is one of the key factors for enhancing enterprise competitiveness. Achieving enterprise interoperability is an extremely complex process which involves different technological, human and organisational elements. In this paper we present a framework to help enterprise interoperability. The framework has been developed taking into account the three domains of interoperability: Enterprise Modelling, Architecture and Platform and Ontologies. The main novelty of the framework in comparison to existing ones is that it includes a step-by-step methodology that explains how to carry out an enterprise interoperability project taking into account different interoperability views, like business, process, human resources, technology, knowledge and semantics.

  20. One step beyond: Different step-to-step transitions exist during continuous contact brachiation in siamangs

    Directory of Open Access Journals (Sweden)

    Fana Michilsens

    2012-02-01

    In brachiation, two main gaits are distinguished, ricochetal brachiation and continuous contact brachiation. During ricochetal brachiation, a flight phase exists and the body centre of mass (bCOM describes a parabolic trajectory. For continuous contact brachiation, where at least one hand is always in contact with the substrate, we showed in an earlier paper that four step-to-step transition types occur. We referred to these as a ‘point’, a ‘loop’, a ‘backward pendulum’ and a ‘parabolic’ transition. Only the first two transition types have previously been mentioned in the existing literature on gibbon brachiation. In the current study, we used three-dimensional video and force analysis to describe and characterize these four step-to-step transition types. Results show that, although individual preference occurs, the brachiation strides characterized by each transition type are mainly associated with speed. Yet, these four transitions seem to form a continuum rather than four distinct types. Energy recovery and collision fraction are used as estimators of mechanical efficiency of brachiation and, remarkably, these parameters do not differ between strides with different transition types. All strides show high energy recoveries (mean  = 70±11.4% and low collision fractions (mean  = 0.2±0.13, regardless of the step-to-step transition type used. We conclude that siamangs have efficient means of modifying locomotor speed during continuous contact brachiation by choosing particular step-to-step transition types, which all minimize collision fraction and enhance energy recovery.

  1. High accuracy step gauge interferometer

    Science.gov (United States)

    Byman, V.; Jaakkola, T.; Palosuo, I.; Lassila, A.

    2018-05-01

    Step gauges are convenient transfer standards for the calibration of coordinate measuring machines. A novel interferometer for step gauge calibrations implemented at VTT MIKES is described. The four-pass interferometer follows Abbe’s principle and measures the position of the inductive probe attached to a measuring head. The measuring head of the instrument is connected to a balanced boom above the carriage by a piezo translation stage. A key part of the measuring head is an invar structure on which the inductive probe and the corner cubes of the measuring arm of the interferometer are attached. The invar structure can be elevated so that the probe is raised without breaking the laser beam. During probing, the bending of the probe and the interferometer readings are recorded and the measurement face position is extrapolated to zero force. The measurement process is fully automated and the face positions of the steps can be measured up to a length of 2 m. Ambient conditions are measured continuously and the refractive index of air is compensated for. Before measurements the step gauge is aligned with an integrated 2D coordinate measuring system. The expanded uncertainty of step gauge calibration is U=\\sqrt{{{(64 nm)}2}+{{(88× {{10}-9}L)}2}} .

  2. FIRST STEP towards ICF commercialization

    International Nuclear Information System (INIS)

    Saylor, W.W.; Pendergrass, J.H.; Dudziak, D.J.

    1984-01-01

    Production of tritium for weapons and fusion R and D programs and successful development of Inertial Confinement Fusion (ICF) technologies are important national goals. A conceptual design for an ICF facility to meet these goals is presented. FIRST STEP (Fusion, Inertial, Reduced-Requirements Systems Test for Special Nuclear Material, Tritium, and Energy Production) is a concept for a plant to produce SNM, tritium, and energy while serving as a test bed for ICF technology development. A credible conceptual design for an ICF SNM and tritium production facility that competes favorably with fission technology on the bases of cost, production quality, and safety was sought. FIRST STEP is also designed to be an engineering test facility that integrates systems required for an ICF power plant and that is intermediate in scale between proof-of-principle experiment and commercial power plant. FIRST STEP driver and pellet performance requirements are moderate and represent reasonable intermediate goals in an R and D plan for ICF commercialization. Repetition rate requirements for FIRST STEP are similar to those of commercial size plants and FIRST STEP can be used to integrate systems under realistic ICF conditions

  3. Target recognition by wavelet transform

    International Nuclear Information System (INIS)

    Li Zhengdong; He Wuliang; Zheng Xiaodong; Cheng Jiayuan; Peng Wen; Pei Chunlan; Song Chen

    2002-01-01

    Wavelet transform has an important character of multi-resolution power, which presents pyramid structure, and this character coincides the way by which people distinguish object from coarse to fineness and from large to tiny. In addition to it, wavelet transform benefits to reducing image noise, simplifying calculation, and embodying target image characteristic point. A method of target recognition by wavelet transform is provided

  4. Face recognition, a landmarks tale

    NARCIS (Netherlands)

    Beumer, G.M.

    2009-01-01

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

  5. Mobile Visual Recognition on Smartphones

    Directory of Open Access Journals (Sweden)

    Zhenwen Gui

    2013-01-01

    Full Text Available This paper addresses the recognition of large-scale outdoor scenes on smartphones by fusing outputs of inertial sensors and computer vision techniques. The main contributions can be summarized as follows. Firstly, we propose an ORD (overlap region divide method to plot image position area, which is fast enough to find the nearest visiting area and can also reduce the search range compared with the traditional approaches. Secondly, the vocabulary tree-based approach is improved by introducing GAGCC (gravity-aligned geometric consistency constraint. Our method involves no operation in the high-dimensional feature space and does not assume a global transform between a pair of images. Thus, it substantially reduces the computational complexity and memory usage, which makes the city scale image recognition feasible on the smartphone. Experiments on a collected database including 0.16 million images show that the proposed method demonstrates excellent recognition performance, while maintaining the average recognition time about 1 s.

  6. Data complexity in pattern recognition

    CERN Document Server

    Kam Ho Tin

    2006-01-01

    Machines capable of automatic pattern recognition have many fascinating uses. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. This book looks at data complexity and its role in shaping the theories and techniques in different disciplines

  7. The Army word recognition system

    Science.gov (United States)

    Hadden, David R.; Haratz, David

    1977-01-01

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

  8. Speech recognition from spectral dynamics

    Indian Academy of Sciences (India)

    Some of the history of gradual infusion of the modulation spectrum concept into Automatic recognition of speech (ASR) comes next, pointing to the relationship of modulation spectrum processing to wellaccepted ASR techniques such as dynamic speech features or RelAtive SpecTrAl (RASTA) filtering. Next, the frequency ...

  9. Speech recognition implementation in radiology

    International Nuclear Information System (INIS)

    White, Keith S.

    2005-01-01

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

  10. Color Textons for Texture Recognition

    NARCIS (Netherlands)

    Burghouts, G.J.; Geusebroek, J.M.

    2006-01-01

    Texton models have proven to be very discriminative for the recognition of grayvalue images taken from rough textures. To further improve the discriminative power of the distinctive texton models of Varma and Zisserman (VZ model) (IJCV, vol. 62(1), pp. 61-81, 2005), we propose two schemes to exploit

  11. Output Interference in Recognition Memory

    Science.gov (United States)

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

    2011-01-01

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

  12. Matching score based face recognition

    NARCIS (Netherlands)

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

    2006-01-01

    Accurate face registration is of vital importance to the performance of a face recognition algorithm. We propose a new method: matching score based face registration, which searches for optimal alignment by maximizing the matching score output of a classifier as a function of the different

  13. Towards automatic forensic face recognition

    NARCIS (Netherlands)

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

    2011-01-01

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

  14. Research on test of product based on spatial sampling criteria and variable step sampling mechanism

    Science.gov (United States)

    Li, Ruihong; Han, Yueping

    2014-09-01

    This paper presents an effective approach for online testing the assembly structures inside products using multiple views technique and X-ray digital radiography system based on spatial sampling criteria and variable step sampling mechanism. Although there are some objects inside one product to be tested, there must be a maximal rotary step for an object within which the least structural size to be tested is predictable. In offline learning process, Rotating the object by the step and imaging it and so on until a complete cycle is completed, an image sequence is obtained that includes the full structural information for recognition. The maximal rotary step is restricted by the least structural size and the inherent resolution of the imaging system. During online inspection process, the program firstly finds the optimum solutions to all different target parts in the standard sequence, i.e., finds their exact angles in one cycle. Aiming at the issue of most sizes of other targets in product are larger than that of the least structure, the paper adopts variable step-size sampling mechanism to rotate the product specific angles with different steps according to different objects inside the product and match. Experimental results show that the variable step-size method can greatly save time compared with the traditional fixed-step inspection method while the recognition accuracy is guaranteed.

  15. How many steps/day are enough? for adults

    Directory of Open Access Journals (Sweden)

    Rowe David A

    2011-07-01

    MVPA that also include estimates of habitual activity levels equate to 7,100 to 11,000 steps/day. A direct estimate of minimal amounts of MVPA accumulated in the course of objectively monitored free-living behaviour is 7,000-8,000 steps/day. A scale that spans a wide range of incremental increases in steps/day and is congruent with public health recognition that "some physical activity is better than none," yet still incorporates step-based translations of recommended amounts of time in MVPA may be useful in research and practice. The full range of users (researchers to practitioners to the general public of objective monitoring instruments that provide step-based outputs require good reference data and evidence-based recommendations to be able to design effective health messages congruent with public health physical activity guidelines, guide behaviour change, and ultimately measure, track, and interpret steps/day.

  16. From raw material to dish: pasta quality step by step.

    Science.gov (United States)

    Sicignano, Angelo; Di Monaco, Rossella; Masi, Paolo; Cavella, Silvana

    2015-10-01

    Pasta is a traditional Italian cereal-based food that is popular worldwide because of its convenience, versatility, sensory and nutritional value. The aim of this review is to present a step-by-step guide to facilitate the understanding of the most important events that can affect pasta characteristics, directing the reader to the appropriate production steps. Owing to its unique flavor, color, composition and rheological properties, durum wheat semolina is the best raw material for pasta production. Although pasta is traditionally made from only two ingredients, sensory quality and chemical/physical characteristics of the final product may vary greatly. Starting from the same ingredients, there are a lot of different events in each step of pasta production that can result in the development of varieties of pasta with different characteristics. In particular, numerous studies have demonstrated the importance of temperature and humidity conditions of the pasta drying operation as well as the significance of the choice of raw material and operating conditions on pasta quality. © 2015 Society of Chemical Industry.

  17. Step by step parallel programming method for molecular dynamics code

    International Nuclear Information System (INIS)

    Orii, Shigeo; Ohta, Toshio

    1996-07-01

    Parallel programming for a numerical simulation program of molecular dynamics is carried out with a step-by-step programming technique using the two phase method. As a result, within the range of a certain computing parameters, it is found to obtain parallel performance by using the level of parallel programming which decomposes the calculation according to indices of do-loops into each processor on the vector parallel computer VPP500 and the scalar parallel computer Paragon. It is also found that VPP500 shows parallel performance in wider range computing parameters. The reason is that the time cost of the program parts, which can not be reduced by the do-loop level of the parallel programming, can be reduced to the negligible level by the vectorization. After that, the time consuming parts of the program are concentrated on less parts that can be accelerated by the do-loop level of the parallel programming. This report shows the step-by-step parallel programming method and the parallel performance of the molecular dynamics code on VPP500 and Paragon. (author)

  18. Object recognition memory in zebrafish.

    Science.gov (United States)

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

    2016-01-01

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

  19. Step-by-step phacoemulsification training program for ophthalmology residents

    Directory of Open Access Journals (Sweden)

    Wang Yulan

    2013-01-01

    Full Text Available Aims: The aim was to analyze the learning curve of phacoemulsification (phaco performed by residents without experience in performing extra-capsular cataract extraction (ECCE in a step-by-step training program (SBSTP. Materials and Methods: Consecutive surgical records of phaco performed from March 2009 to Sept 2011 by four residents without previous ECCE experience were retrospectively reviewed. The completion rate of the first 30 procedures by each resident was calculated. The main intraoperative phaco parameter records for the first 30 surgeries by each resident were compared with those for their last 30 surgeries. Intraoperative complications in the residents′ procedures were also recorded and analyzed. Results: A total of 1013 surgeries were performed by residents. The completion rate for the first 30 phaco procedures was 79.2 μ 5.8%. The main reasons for halting the procedure were as follows: Anterior capsule tear, inability to crack the nucleus, and posterior capsular rupture during phaco or cortex removal. Cumulative dissipated energy of phaco power used during the surgeries was significantly less in the last 30 cases compared with the first 30 cases (30.10 μ 17.58 vs. 55.41 μ 37.59, P = 0.021. Posterior capsular rupture rate was 2.5 μ 1.2% in total (10.8 μ 4.2% in the first 30 cases and 1.7 μ 1.9% in the last 30 cases, P = 0.008; a statistically significant difference. Conclusion:The step-by-step training program might be a necessary process for a resident to transit from dependence to a self-supported operator. It is also an essential middle step between wet lab training to performing the entire phaco procedure on the patient both effectively and safely.

  20. Rotation, scale, and translation invariant pattern recognition using feature extraction

    Science.gov (United States)

    Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

    1997-03-01

    A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.

  1. 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.

  2. An Edge-Based Macao License Plate Recognition System

    Directory of Open Access Journals (Sweden)

    Chi-Man Pun

    2011-04-01

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

  3. The interplay of sequence conservation and T cell immune recognition

    DEFF Research Database (Denmark)

    Bresciani, Anne Gøther; Sette, Alessandro; Greenbaum, Jason

    2014-01-01

    examined the hypothesis that conservation of a peptide in bacteria that are part of the healthy human microbiome leads to a reduced level of immunogenicity due to tolerization of T cells to the commensal bacteria. This was done by comparing experimentally characterized T cell epitope recognition data from...... the Immune Epitope Database with their conservation in the human microbiome. Indeed, we did see a lower immunogenicity for conserved peptides conserved. While many aspects how this conservation comparison is done require further optimization, this is a first step towards a better understanding T cell...... recognition of peptides in bacterial pathogens is influenced by their conservation in commensal bacteria. If the further work proves that this approach is successful, the degree of overlap of a peptide with the human proteome or microbiome could be added to the arsenal of tools available to assess peptide...

  4. The own-age face recognition bias is task dependent.

    Science.gov (United States)

    Proietti, Valentina; Macchi Cassia, Viola; Mondloch, Catherine J

    2015-08-01

    The own-age bias (OAB) in face recognition (more accurate recognition of own-age than other-age faces) is robust among young adults but not older adults. We investigated the OAB under two different task conditions. In Experiment 1 young and older adults (who reported more recent experience with own than other-age faces) completed a match-to-sample task with young and older adult faces; only young adults showed an OAB. In Experiment 2 young and older adults completed an identity detection task in which we manipulated the identity strength of target and distracter identities by morphing each face with an average face in 20% steps. Accuracy increased with identity strength and facial age influenced older adults' (but not younger adults') strategy, but there was no evidence of an OAB. Collectively, these results suggest that the OAB depends on task demands and may be absent when searching for one identity. © 2014 The British Psychological Society.

  5. Time step MOTA thermostat simulation

    International Nuclear Information System (INIS)

    Guthrie, G.L.

    1978-09-01

    The report details the logic, program layout, and operating procedures for the time-step MOTA (Materials Open Test Assembly) thermostat simulation program known as GYRD. It will enable prospective users to understand the operation of the program, run it, and interpret the results. The time-step simulation analysis was the approach chosen to determine the maximum value gain that could be used to minimize steady temperature offset without risking undamped thermal oscillations. The advantage of the GYRD program is that it directly shows hunting, ringing phenomenon, and similar events. Programs BITT and CYLB are faster, but do not directly show ringing time

  6. A mechanism for leader stepping

    Science.gov (United States)

    Ebert, U.; Carlson, B. E.; Koehn, C.

    2013-12-01

    The stepping of negative leaders is well observed, but not well understood. A major problem consists of the fact that the streamer corona is typically invisible within a thunderstorm, but determines the evolution of a leader. Motivated by recent observations of streamer and leader formation in the laboratory by T.M.P. Briels, S. Nijdam, P. Kochkin, A.P.J. van Deursen et al., by recent simulations of these processes by J. Teunissen, A. Sun et al., and by our theoretical understanding of the process, we suggest how laboratory phenomena can be extrapolated to lightning leaders to explain the stepping mechanism.

  7. A FRACTAL JUSTIFICATION OF THE NORMALIZATION STEP FOR ONLINE HANDWRITING RECOGNITION

    NARCIS (Netherlands)

    Vincent, N.; Dorizzi, B.

    2004-01-01

    n this paper is presented an example of the use of fractal approaches in the field of online handwriting processing. The adaptation of the box counting method to the computation of online handwriting fractal dimension is presented. The influence of different parameters is studied. This allows

  8. Efficient CEPSTRAL Normalization for Robust Speech Recognition

    National Research Council Canada - National Science Library

    Liu, Fu-Hua; Stern, Richard M; Huang, Xuedong; Acero, Alejandro

    1993-01-01

    In this paper we describe and compare the performance of a series of cepstrum-based procedures that enable the CMU SPHINX-II speech recognition system to maintain a high level of recognition accuracy...

  9. Data structures, computer graphics, and pattern recognition

    CERN Document Server

    Klinger, A; Kunii, T L

    1977-01-01

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

  10. Recognition of an Independent Self-Consciousness

    DEFF Research Database (Denmark)

    Bjerre, Henrik Jøker

    2009-01-01

    Hegel's concept in the Phenomenology of the Spirit of the "recognition of an independent self-consciousness" is investigated as a point of separation for contemporary philosophy of recognition. I claim that multiculturalism and the theories of recognition (such as Axel Honneth's) based on empiric...... psychology neglect or deny crucial metaphysical aspects of the Hegelian legacy. Instead, I seek to point at an additional, "spiritual", level of recognition, based on the concept of the subject in Lacanian psychoanalysis....

  11. Case-Based Policy and Goal Recognition

    Science.gov (United States)

    2015-09-30

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

  12. Driver training in steps (DTS).

    NARCIS (Netherlands)

    2010-01-01

    For some years now, it has been possible in the Netherlands to follow a Driver Training in Steps (DTS) as well as the regular driver training. The DTS is a structured training method with clear training objectives which are categorized in four modules. Although the DTS is considerably better than

  13. Stepping out: dare to step forward, step back, or just stand still and breathe.

    Science.gov (United States)

    Waisman, Mary Sue

    2012-01-01

    It is important to step out and make a difference. We have one of the most unique and diverse professions that allows for diversity in thought and practice, permitting each of us to grow in our unique niches and make significant contributions. I was frightened to 'step out' to go to culinary school at the age of 46, but it changed forever the way I look at my profession and I have since experienced the most enjoyable and innovative career. There are also times when it is important to 'step back' to relish the roots of our profession; to help bring food back into nutrition; to translate all of our wonderful science into a language of food that Canadians understand. We all need to take time to 'just stand still and breathe': to celebrate our accomplishments, reflect on our actions, ensure we are heading toward our vision, keep the profession vibrant and relevant, and cherish one another.

  14. Hidden neural networks: application to speech recognition

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1998-01-01

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

  15. One-Step Protein Conjugation to Upconversion Nanoparticles.

    Science.gov (United States)

    Lu, Jie; Chen, Yinghui; Liu, Deming; Ren, Wei; Lu, Yiqing; Shi, Yu; Piper, James; Paulsen, Ian; Jin, Dayong

    2015-10-20

    The emerging upconversion nanoparticles offer a fascinating library of ultrasensitive luminescent probes for a range of biotechnology applications from biomarker discovery to single molecule tracking, early disease diagnosis, deep tissue imaging, and drug delivery and therapies. The effective bioconjugation of inorganic nanoparticles to the molecule-specific proteins, free of agglomeration, nonspecific binding, or biomolecule deactivation, is crucial for molecular recognition of target molecules or cells. The current available protocols require multiple steps which can lead to low probe stability, specificity, and reproducibility. Here we report a simple and rapid protein bioconjugation method based on a one-step ligand exchange using the DNAs as the linker. Our method benefits from the robust DNA-protein conjugates as well as from multiple ions binding capability. Protein can be preconjugated via an amino group at the 3' end of a synthetic DNA molecule, so that the 5' end phosphoric acid group and multiple phosphate oxygen atoms in the phosphodiester bonds are exposed to replace the oleic acid ligands on the surface of upconversion nanoparticles due to their stronger chelating capability to lanthanides. We demonstrated that our method can efficiently pull out the upconversion nanoparticles from organic solvent into an aqueous phase. The upconversion nanoparticles then become hydrophilic, stable, and specific biomolecules recognition. This allows us to successfully functionalize the upconversion nanoparticles with horseradish peroxidise (HRP) for catalytic colorimetric assay and for streptavidin (SA)-biotin immunoassays.

  16. 2-Step IMAT and 2-Step IMRT in three dimensions

    International Nuclear Information System (INIS)

    Bratengeier, Klaus

    2005-01-01

    In two dimensions, 2-Step Intensity Modulated Arc Therapy (2-Step IMAT) and 2-Step Intensity Modulated Radiation Therapy (IMRT) were shown to be powerful methods for the optimization of plans with organs at risk (OAR) (partially) surrounded by a target volume (PTV). In three dimensions, some additional boundary conditions have to be considered to establish 2-Step IMAT as an optimization method. A further aim was to create rules for ad hoc adaptations of an IMRT plan to a daily changing PTV-OAR constellation. As a test model, a cylindrically symmetric PTV-OAR combination was used. The centrally placed OAR can adapt arbitrary diameters with different gap widths toward the PTV. Along the rotation axis the OAR diameter can vary, the OAR can even vanish at some axis positions, leaving a circular PTV. The width and weight of the second segment were the free parameters to optimize. The objective function f to minimize was the root of the integral of the squared difference of the dose in the target volume and a reference dose. For the problem, two local minima exist. Therefore, as a secondary criteria, the magnitude of hot and cold spots were taken into account. As a result, the solution with a larger segment width was recommended. From plane to plane for varying radii of PTV and OAR and for different gaps between them, different sets of weights and widths were optimal. Because only one weight for one segment shall be used for all planes (respectively leaf pairs), a strategy for complex three-dimensional (3-D) cases was established to choose a global weight. In a second step, a suitable segment width was chosen, minimizing f for this global weight. The concept was demonstrated in a planning study for a cylindrically symmetric example with a large range of different radii of an OAR along the patient axis. The method is discussed for some classes of tumor/organ at risk combinations. Noncylindrically symmetric cases were treated exemplarily. The product of width and weight of

  17. 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.

  18. Energetics of highly kinked step edges

    NARCIS (Netherlands)

    Zandvliet, Henricus J.W.

    2010-01-01

    We have determined the step edge free energy, the step edge stiffness and dimensionless inverse step edge stiffness of the highly kinked < 010> oriented step on a (001) surface of a simple square lattice within the framework of a solid-on-solid model. We have found an exact expression for the step

  19. A comparison of 1D and 2D LSTM architectures for the recognition of handwritten Arabic

    Science.gov (United States)

    Yousefi, Mohammad Reza; Soheili, Mohammad Reza; Breuel, Thomas M.; Stricker, Didier

    2015-01-01

    In this paper, we present an Arabic handwriting recognition method based on recurrent neural network. We use the Long Short Term Memory (LSTM) architecture, that have proven successful in different printed and handwritten OCR tasks. Applications of LSTM for handwriting recognition employ the two-dimensional architecture to deal with the variations in both vertical and horizontal axis. However, we show that using a simple pre-processing step that normalizes the position and baseline of letters, we can make use of 1D LSTM, which is faster in learning and convergence, and yet achieve superior performance. In a series of experiments on IFN/ENIT database for Arabic handwriting recognition, we demonstrate that our proposed pipeline can outperform 2D LSTM networks. Furthermore, we provide comparisons with 1D LSTM networks trained with manually crafted features to show that the automatically learned features in a globally trained 1D LSTM network with our normalization step can even outperform such systems.

  20. Recognition of Action as a Bayesian Parameter Estimation Problem over Time

    DEFF Research Database (Denmark)

    Krüger, Volker

    2007-01-01

    In this paper we will discuss two problems related to action recognition: The first problem is the one of identifying in a surveillance scenario whether a person is walking or running and in what rough direction. The second problem is concerned with the recovery of action primitives from observed...... complex actions. Both problems will be discussed within a statistical framework. Bayesian propagation over time offers a framework to treat likelihood observations at each time step and the dynamics between the time steps in a unified manner. The first problem will be approached as a patter recognition...... of the Bayesian framework for action recognition and round up our discussion....

  1. Subject independent facial expression recognition with robust face detection using a convolutional neural network.

    Science.gov (United States)

    Matsugu, Masakazu; Mori, Katsuhiko; Mitari, Yusuke; Kaneda, Yuji

    2003-01-01

    Reliable detection of ordinary facial expressions (e.g. smile) despite the variability among individuals as well as face appearance is an important step toward the realization of perceptual user interface with autonomous perception of persons. We describe a rule-based algorithm for robust facial expression recognition combined with robust face detection using a convolutional neural network. In this study, we address the problem of subject independence as well as translation, rotation, and scale invariance in the recognition of facial expression. The result shows reliable detection of smiles with recognition rate of 97.6% for 5600 still images of more than 10 subjects. The proposed algorithm demonstrated the ability to discriminate smiling from talking based on the saliency score obtained from voting visual cues. To the best of our knowledge, it is the first facial expression recognition model with the property of subject independence combined with robustness to variability in facial appearance.

  2. The automaticity of emotion recognition.

    Science.gov (United States)

    Tracy, Jessica L; Robins, Richard W

    2008-02-01

    Evolutionary accounts of emotion typically assume that humans evolved to quickly and efficiently recognize emotion expressions because these expressions convey fitness-enhancing messages. The present research tested this assumption in 2 studies. Specifically, the authors examined (a) how quickly perceivers could recognize expressions of anger, contempt, disgust, embarrassment, fear, happiness, pride, sadness, shame, and surprise; (b) whether accuracy is improved when perceivers deliberate about each expression's meaning (vs. respond as quickly as possible); and (c) whether accurate recognition can occur under cognitive load. Across both studies, perceivers quickly and efficiently (i.e., under cognitive load) recognized most emotion expressions, including the self-conscious emotions of pride, embarrassment, and shame. Deliberation improved accuracy in some cases, but these improvements were relatively small. Discussion focuses on the implications of these findings for the cognitive processes underlying emotion recognition.

  3. Individual Recognition in Ant Queens

    DEFF Research Database (Denmark)

    D'Ettorre, Patrizia; Heinze, Jürgen

    2005-01-01

    Personal relationships are the cornerstone of vertebrate societies, but insect societies are either too large for individual recognition, or their members were assumed to lack the necessary cognitive abilities 1 and 2 . This paradigm has been challenged by the recent discovery that paper wasps...... recognize each other's unique facial color patterns [3] . Individual recognition is advantageous when dominance hierarchies control the partitioning of work and reproduction 2 and 4 . Here, we show that unrelated founding queens of the ant Pachycondyla villosa use chemical cues to recognize each other...... individually. Aggression was significantly lower in pairs of queens that had previously interacted than in pairs with similar social history but no experience with one another. Moreover, subordinates discriminated familiar and unfamiliar dominants in choice experiments in which physical contact, but not odor...

  4. Motion Primitives for Action Recognition

    DEFF Research Database (Denmark)

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

    2007-01-01

    the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize......The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent...... different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognition rates of 88.7% and 85.5%, respectively....

  5. Physics of Automatic Target Recognition

    CERN Document Server

    Sadjadi, Firooz

    2007-01-01

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

  6. Symbol Recognition using Spatial Relations

    OpenAIRE

    K.C., Santosh; Lamiroy, Bart; Wendling, Laurent

    2012-01-01

    International audience; In this paper, we present a method for symbol recognition based on the spatio-structural description of a 'vocabulary' of extracted visual elementary parts. It is applied to symbols in electrical wiring diagrams. The method consists of first identifying vocabulary elements into different groups based on their types (e.g., circle, corner ). We then compute spatial relations between the possible pairs of labelled vocabulary types which are further used as a basis for bui...

  7. 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.

  8. Detection of basic steps of a horse "step, trot, gallop" inertial sensors and using artificial neural networks

    Directory of Open Access Journals (Sweden)

    Jaime Eduardo Andrade Ramírez

    2015-12-01

    Full Text Available Through this article the development of a system capable of recognizing the basic steps of a horse in a natural environment is shown. This development is focused on artificial intelligence, where using the processing of a PC, reference algorithms are implemented to treatment and recognition of signs of equine movements captured by inertial sensors. This process is used Fast Fourier transform and artificial neural networks in the software component, the electronic implementation includes the use of the board Enpic14® and Zig-Bee protocol for communicating portable device located on the horses and the computer. The result is a recognition system equine basic steps for identification and characterization of livestock ready for target practice mounted at the National School of Carabineros "ESCAR". This work is developed by the research group in software and Facatativá "GISTFA" technologies University of Cundinamarca in partnership with the research group of the National School of Carabineros "Alfonso Lopez" ESCAR-DINAENro.COL0061592 under the research project "Design of a simulator for shooting lessons mounted police national school" Alfonso Lopez", national police approved in 2014

  9. The DELPHI Silicon Tracker in the global pattern recognition

    CERN Document Server

    Elsing, M

    2000-01-01

    ALEPH and DELPHI were the first experiments operating a silicon vertex detector at LEP. During the past 10 years of data taking the DELPHI Silicon Tracker was upgraded three times to follow the different tracking requirements for LEP 1 and LEP 2 as well as to improve the tracking performance. Several steps in the development of the pattern recognition software were done in order to understand and fully exploit the silicon tracker information. This article gives an overview of the final algorithms and concepts of the track reconstruction using the Silicon Tracker in DELPHI.

  10. A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Kamronn, Simon Due; Paquet, Ulrich

    2017-01-01

    This paper takes a step towards temporal reasoning in a dynamically changing video, not in the pixel space that constitutes its frames, but in a latent space that describes the non-linear dynamics of the objects in its world. We introduce the Kalman variational auto-encoder, a framework...... for unsupervised learning of sequential data that disentangles two latent representations: an object’s representation, coming from a recognition model, and a latent state describing its dynamics. As a result, the evolution of the world can be imagined and missing data imputed, both without the need to generate...

  11. The DELPHI Silicon Tracker in the global pattern recognition

    International Nuclear Information System (INIS)

    Elsing, M.

    2000-01-01

    ALEPH and DELPHI were the first experiments operating a silicon vertex detector at LEP. During the past 10 years of data taking the DELPHI Silicon Tracker was upgraded three times to follow the different tracking requirements for LEP 1 and LEP 2 as well as to improve the tracking performance. Several steps in the development of the pattern recognition software were done in order to understand and fully exploit the silicon tracker information. This article gives an overview of the final algorithms and concepts of the track reconstruction using the Silicon Tracker in DELPHI

  12. Visual recognition of permuted words

    Science.gov (United States)

    Rashid, Sheikh Faisal; Shafait, Faisal; Breuel, Thomas M.

    2010-02-01

    In current study we examine how letter permutation affects in visual recognition of words for two orthographically dissimilar languages, Urdu and German. We present the hypothesis that recognition or reading of permuted and non-permuted words are two distinct mental level processes, and that people use different strategies in handling permuted words as compared to normal words. A comparison between reading behavior of people in these languages is also presented. We present our study in context of dual route theories of reading and it is observed that the dual-route theory is consistent with explanation of our hypothesis of distinction in underlying cognitive behavior for reading permuted and non-permuted words. We conducted three experiments in lexical decision tasks to analyze how reading is degraded or affected by letter permutation. We performed analysis of variance (ANOVA), distribution free rank test, and t-test to determine the significance differences in response time latencies for two classes of data. Results showed that the recognition accuracy for permuted words is decreased 31% in case of Urdu and 11% in case of German language. We also found a considerable difference in reading behavior for cursive and alphabetic languages and it is observed that reading of Urdu is comparatively slower than reading of German due to characteristics of cursive script.

  13. DNA recognition by synthetic constructs.

    Science.gov (United States)

    Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L

    2011-09-05

    The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Gender recognition from vocal source

    Science.gov (United States)

    Sorokin, V. N.; Makarov, I. S.

    2008-07-01

    Efficiency of automatic recognition of male and female voices based on solving the inverse problem for glottis area dynamics and for waveform of the glottal airflow volume velocity pulse is studied. The inverse problem is regularized through the use of analytical models of the voice excitation pulse and of the dynamics of the glottis area, as well as the model of one-dimensional glottal airflow. Parameters of these models and spectral parameters of the volume velocity pulse are considered. The following parameters are found to be most promising: the instant of maximum glottis area, the maximum derivative of the area, the slope of the spectrum of the glottal airflow volume velocity pulse, the amplitude ratios of harmonics of this spectrum, and the pitch. On the plane of the first two main components in the space of these parameters, an almost twofold decrease in the classification error relative to that for the pitch alone is attained. The male voice recognition probability is found to be 94.7%, and the female voice recognition probability is 95.9%.

  15. Quadcopter Control Using Speech Recognition

    Science.gov (United States)

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

    2018-04-01

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

  16. Multithread Face Recognition in Cloud

    Directory of Open Access Journals (Sweden)

    Dakshina Ranjan Kisku

    2016-01-01

    Full Text Available Faces are highly challenging and dynamic objects that are employed as biometrics evidence in identity verification. Recently, biometrics systems have proven to be an essential security tools, in which bulk matching of enrolled people and watch lists is performed every day. To facilitate this process, organizations with large computing facilities need to maintain these facilities. To minimize the burden of maintaining these costly facilities for enrollment and recognition, multinational companies can transfer this responsibility to third-party vendors who can maintain cloud computing infrastructures for recognition. In this paper, we showcase cloud computing-enabled face recognition, which utilizes PCA-characterized face instances and reduces the number of invariant SIFT points that are extracted from each face. To achieve high interclass and low intraclass variances, a set of six PCA-characterized face instances is computed on columns of each face image by varying the number of principal components. Extracted SIFT keypoints are fused using sum and max fusion rules. A novel cohort selection technique is applied to increase the total performance. The proposed protomodel is tested on BioID and FEI face databases, and the efficacy of the system is proven based on the obtained results. We also compare the proposed method with other well-known methods.

  17. Non Audio-Video gesture recognition system

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  18. Famous face recognition, face matching, and extraversion.

    Science.gov (United States)

    Lander, Karen; Poyarekar, Siddhi

    2015-01-01

    It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.

  19. Physical Human Activity Recognition Using Wearable Sensors

    Directory of Open Access Journals (Sweden)

    Ferhat Attal

    2015-12-01

    Full Text Available This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle. Three main steps describe the activity recognition process: sensors’ placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN, Support Vector Machines (SVM, Gaussian Mixture Models (GMM, and Random Forest (RF as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM and Hidden Markov Model (HMM, are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject.

  20. Physical Human Activity Recognition Using Wearable Sensors.

    Science.gov (United States)

    Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

    2015-12-11

    This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors' placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject.

  1. Step 2: Know Your Diabetes ABCs

    Science.gov (United States)

    ... please turn JavaScript on. Feature: Type 2 Diabetes Step 2: Know Your Diabetes ABCs Past Issues / Fall ... 2 Diabetes" Articles Diabetes Is Serious But Manageable / Step 1: Learn About Diabetes / Step 2: Know Your ...

  2. The coevolution of recognition and social behavior.

    Science.gov (United States)

    Smead, Rory; Forber, Patrick

    2016-05-26

    Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation.

  3. Step-By-Step: Life Cycle Radioactive Waste Management

    International Nuclear Information System (INIS)

    2014-01-01

    Radioactive waste is an unavoidable by-product when nuclear technologies are used for electricity production and for beneficial practices in medicine, agriculture, research and industry. When the radioactivity of the waste is above a certain threshold, the waste requires special disposal methods. Through extensive research, standards and approaches have been developed for safely and securely preparing for and managing radioactive waste disposal. In the course of its journey from the point of generation to disposal, radioactive waste undergoes a number of predisposal management treatment steps to transform it into a safe, stable and manageable form suitable for transport, storage and disposal

  4. Blogging business step-by-step startup guide

    CERN Document Server

    magazine, Entrepreneur

    2014-01-01

    This kit includes: Essential industry and business-specific startup steps with worksheets, calculators, checklists and more. Entrepreneur Editors' Start Your Own Business, a guide to starting any business and surviving the first three years. Downloadable, customizable business letters, sales letters, and other sample documents. Entrepreneur's Small Business Legal Toolkit. Blogs are still one of the internet's fastest-growing phenomena–and one of the best and easiest ways to make money online. Packed with the latest blog tools, tricks, and up-and-coming trends, this fully revised edition teache

  5. The Main Cognitive Model of Visual Recognition: Contour Recognition

    OpenAIRE

    Chen, YongHong

    2017-01-01

    In this paper, we will study the following pattern recognition problem: Every pattern is a 3-dimensional graph, its surface can be split up into some regions, every region is composed of the pixels with the approximately same colour value and the approximately same depth value that is distance to eyes, and there may also be some contours, e.g., literal contours, on a surface of every pattern. For this problem we reveal the inherent laws. Moreover, we establish a cognitive model to reflect the...

  6. Robotic retroperitoneal partial nephrectomy: a step-by-step guide.

    Science.gov (United States)

    Ghani, Khurshid R; Porter, James; Menon, Mani; Rogers, Craig

    2014-08-01

    To describe a step-by-step guide for successful implementation of the retroperitoneal approach to robotic partial nephrectomy (RPN) PATIENTS AND METHODS: The patient is placed in the flank position and the table fully flexed to increase the space between the 12th rib and iliac crest. Access to the retroperitoneal space is obtained using a balloon-dilating device. Ports include a 12-mm camera port, two 8-mm robotic ports and a 12-mm assistant port placed in the anterior axillary line cephalad to the anterior superior iliac spine, and 7-8 cm caudal to the ipsilateral robotic port. Positioning and port placement strategies for successful technique include: (i) Docking robot directly over the patient's head parallel to the spine; (ii) incision for camera port ≈1.9 cm (1 fingerbreadth) above the iliac crest, lateral to the triangle of Petit; (iii) Seldinger technique insertion of kidney-shaped balloon dilator into retroperitoneal space; (iv) Maximising distance between all ports; (v) Ensuring camera arm is placed in the outer part of the 'sweet spot'. The retroperitoneal approach to RPN permits direct access to the renal hilum, no need for bowel mobilisation and excellent visualisation of posteriorly located tumours. © 2014 The Authors. BJU International © 2014 BJU International.

  7. Molecular recognition on a cavitand-functionalized silicon surface.

    Science.gov (United States)

    Biavardi, Elisa; Favazza, Maria; Motta, Alessandro; Fragalà, Ignazio L; Massera, Chiara; Prodi, Luca; Montalti, Marco; Melegari, Monica; Condorelli, Guglielmo G; Dalcanale, Enrico

    2009-06-03

    A Si(100) surface featuring molecular recognition properties was obtained by covalent functionalization with a tetraphosphonate cavitand (Tiiii), able to complex positively charged species. Tiiii cavitand was grafted onto the Si by photochemical hydrosilylation together with 1-octene as a spatial spectator. The recognition properties of the Si-Tiiii surface were demonstrated through two independent analytical techniques, namely XPS and fluorescence spectroscopy, during the course of reversible complexation-guest exchange-decomplexation cycles with specifically designed ammonium and pyridinium salts. Control experiments employing a Si(100) surface functionalized with a structurally similar, but complexation inactive, tetrathiophosphonate cavitand (TSiiii) demonstrated no recognition events. This provides evidence for the complexation properties of the Si-Tiiii surface, ruling out the possibility of nonspecific interactions between the substrate and the guests. The residual Si-O(-) terminations on the surface replace the guests' original counterions, thus stabilizing the complex ion pairs. These results represent a further step toward the control of self-assembly of complex supramolecular architectures on surfaces.

  8. A multi-approach feature extractions for iris recognition

    Science.gov (United States)

    Sanpachai, H.; Settapong, M.

    2014-04-01

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

  9. Source Separation via Spectral Masking for Speech Recognition Systems

    Directory of Open Access Journals (Sweden)

    Gustavo Fernandes Rodrigues

    2012-12-01

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

  10. Palm vein recognition based on directional empirical mode decomposition

    Science.gov (United States)

    Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei

    2014-04-01

    Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.

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

    Science.gov (United States)

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

    2011-05-01

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

  12. Molecular mechanism of ERK dephosphorylation by striatal-enriched protein tyrosine phosphatase (STEP)

    Science.gov (United States)

    Li, Hui; Li, Kang-shuai; Su, Jing; Chen, Lai-Zhong; Xu, Yun-Fei; Wang, Hong-Mei; Gong, Zheng; Cui, Guo-Ying; Yu, Xiao; Wang, Kai; Yao, Wei; Xin, Tao; Li, Min-Yong; Xiao, Kun-Hong; An, Xiao-fei; Huo, Yuqing; Xu, Zhi-gang; Sun, Jin-Peng; Pang, Qi

    2013-01-01

    Striatal-enriched tyrosine phosphatase (STEP) is an important regulator of neuronal synaptic plasticity, and its abnormal level or activity contributes to cognitive disorders. One crucial downstream effector and direct substrate of STEP is extracellular signal-regulated protein kinase (ERK), which has important functions in spine stabilisation and action potential transmission. The inhibition of STEP activity toward phospho-ERK has the potential to treat neuronal diseases, but the detailed mechanism underlying the dephosphorylation of phospho-ERK by STEP is not known. Therefore, we examined STEP activity toward pNPP, phospho-tyrosine-containing peptides, and the full-length phospho-ERK protein using STEP mutants with different structural features. STEP was found to be a highly efficient ERK tyrosine phosphatase that required both its N-terminal regulatory region and key residues in its active site. Specifically, both KIM and KIS of STEP were required for ERK interaction. In addition to the N-terminal KIS region, S245, hydrophobic residues L249/L251, and basic residues R242/R243 located in the KIM region were important in controlling STEP activity toward phospho-ERK. Further kinetic experiments revealed subtle structural differences between STEP and HePTP that affected the interactions of their KIMs with ERK. Moreover, STEP recognised specific positions of a phospho-ERK peptide sequence through its active site, and the contact of STEP F311 with phospho-ERK V205 and T207 were crucial interactions. Taken together, our results not only provide the information for interactions between ERK and STEP, but will also help in the development of specific strategies to target STEP-ERK recognition, which could serve as a potential therapy for neurological disorders. PMID:24117863

  13. COMMERCIAL FUND, RECOGNITION AND ASSESSMENT

    Directory of Open Access Journals (Sweden)

    VIOREL TRIF

    2010-01-01

    Full Text Available The importance of the immaterial investments within companies nowadays urges the specialists in accounting to find the ways to present more in the elements. In their studies researchers face the controversy reinvestments, as an asset in the balance sheet or an expense in the profit or loss account. The main goal of this paper is to analyze the difficulties in commercial fund. In the first part we will analyze various definitions of the problems concerning the commercial fund’s recognition and assessment. The paper also suggests that investments are really social and economic problems.

  14. Introduction to radar target recognition

    CERN Document Server

    Tait, P

    2006-01-01

    This new text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems. It is based on the fundamental scientific principles of high resolution radar, and explains how the techniques can be used in real systems, taking into account the characteristics of practical radar system designs and component limitations. It also addresses operational aspects, such as how high resolution modes would fit in with other functions such as detection and tracking. Mathematics is kept to a minimum and the complex techniques and issues are

  15. Comparing word and face recognition

    DEFF Research Database (Denmark)

    Robotham, Ro Julia; Starrfelt, Randi

    2017-01-01

    included, as a control, which makes designing experiments all the more challenging. Three main strategies have been used to overcome this problem, each of which has limitations: 1) Compare performances on typical tests of the three stimulus types (e.g., a Face Memory Test, an Object recognition test...... this framework to classify tests and experiments aiming to compare processing across these categories, it becomes apparent that core differences in characteristics (visual and semantic) between the stimuli make the problem of designing comparable tests an insoluble conundrum. By analyzing the experimental...

  16. Psychophysiological indices of recognition memory

    OpenAIRE

    Heaver, Becky

    2012-01-01

    It has recently been found that during recognition memory tests participants’ pupils dilate more when they view old items compared to novel items. This thesis sought to replicate this novel ‘‘Pupil Old/New Effect’’ (PONE) and to determine its relationship to implicit and explicit mnemonic processes, the veracity of participants’ responses, and the analogous Event-Related Potential (ERP) old/new effect. Across 9 experiments, pupil-size was measured with a video-based eye-tracker during a varie...

  17. Steps in Researching the Music in Therapy

    DEFF Research Database (Denmark)

    Bonde, Lars Ole

    2007-01-01

    The chapter introduces a generic flowchart + step-by-step guide for microanalysis of music (compositions and improvisations) in music therapy.......The chapter introduces a generic flowchart + step-by-step guide for microanalysis of music (compositions and improvisations) in music therapy....

  18. Exemplar Based Recognition of Visual Shapes

    DEFF Research Database (Denmark)

    Olsen, Søren I.

    2005-01-01

    This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoint....... The matching is insensitive to rotations, limited scalings and small deformations. The recognition is robust to noise, background clutter and partial occlusion. Recognition is possible from few training images and improve with the number of training images.......This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoints...

  19. Document recognition serving people with disabilities

    Science.gov (United States)

    Fruchterman, James R.

    2007-01-01

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

  20. Lateral step initiation behavior in older adults

    OpenAIRE

    Sparto, Patrick J; Jennings, J Richard; Furman, Joseph M; Redfern, Mark S

    2013-01-01

    Older adults have varied postural responses during induced and voluntary lateral stepping. The purpose of the research was to quantify the occurrence of different stepping strategies during lateral step initiation in older adults and to relate the stepping responses to retrospective history of falls. Seventy community-ambulating older adults (mean age 76 y, range 70–94 y) performed voluntary lateral steps as quickly as possible to the right or left in response to a visual cue, in a blocked de...

  1. System of breast cancer recognition

    International Nuclear Information System (INIS)

    Rozhkova, N.I.

    1984-01-01

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

  2. Longitudinal study of fingerprint recognition.

    Science.gov (United States)

    Yoon, Soweon; Jain, Anil K

    2015-07-14

    Human identification by fingerprints is based on the fundamental premise that ridge patterns from distinct fingers are different (uniqueness) and a fingerprint pattern does not change over time (persistence). Although the uniqueness of fingerprints has been investigated by developing statistical models to estimate the probability of error in comparing two random samples of fingerprints, the persistence of fingerprints has remained a general belief based on only a few case studies. In this study, fingerprint match (similarity) scores are analyzed by multilevel statistical models with covariates such as time interval between two fingerprints in comparison, subject's age, and fingerprint image quality. Longitudinal fingerprint records of 15,597 subjects are sampled from an operational fingerprint database such that each individual has at least five 10-print records over a minimum time span of 5 y. In regard to the persistence of fingerprints, the longitudinal analysis on a single (right index) finger demonstrates that (i) genuine match scores tend to significantly decrease when time interval between two fingerprints in comparison increases, whereas the change in impostor match scores is negligible; and (ii) fingerprint recognition accuracy at operational settings, nevertheless, tends to be stable as the time interval increases up to 12 y, the maximum time span in the dataset. However, the uncertainty of temporal stability of fingerprint recognition accuracy becomes substantially large if either of the two fingerprints being compared is of poor quality. The conclusions drawn from 10-finger fusion analysis coincide with the conclusions from single-finger analysis.

  3. Ordinal measures for iris recognition.

    Science.gov (United States)

    Sun, Zhenan; Tan, Tieniu

    2009-12-01

    Images of a human iris contain rich texture information useful for identity authentication. A key and still open issue in iris recognition is how best to represent such textural information using a compact set of features (iris features). In this paper, we propose using ordinal measures for iris feature representation with the objective of characterizing qualitative relationships between iris regions rather than precise measurements of iris image structures. Such a representation may lose some image-specific information, but it achieves a good trade-off between distinctiveness and robustness. We show that ordinal measures are intrinsic features of iris patterns and largely invariant to illumination changes. Moreover, compactness and low computational complexity of ordinal measures enable highly efficient iris recognition. Ordinal measures are a general concept useful for image analysis and many variants can be derived for ordinal feature extraction. In this paper, we develop multilobe differential filters to compute ordinal measures with flexible intralobe and interlobe parameters such as location, scale, orientation, and distance. Experimental results on three public iris image databases demonstrate the effectiveness of the proposed ordinal feature models.

  4. Dynamic Features for Iris Recognition.

    Science.gov (United States)

    da Costa, R M; Gonzaga, A

    2012-08-01

    The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.

  5. Entity recognition from clinical texts via recurrent neural network.

    Science.gov (United States)

    Liu, Zengjian; Yang, Ming; Wang, Xiaolong; Chen, Qingcai; Tang, Buzhou; Wang, Zhe; Xu, Hua

    2017-07-05

    Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health information (PHI), widely exist in clinical texts. Recognizing these entities has become a hot topic in clinical natural language processing (NLP), and a large number of traditional machine learning methods, such as support vector machine and conditional random field, have been deployed to recognize entities from clinical texts in the past few years. In recent years, recurrent neural network (RNN), one of deep learning methods that has shown great potential on many problems including named entity recognition, also has been gradually used for entity recognition from clinical texts. In this paper, we comprehensively investigate the performance of LSTM (long-short term memory), a representative variant of RNN, on clinical entity recognition and protected health information recognition. The LSTM model consists of three layers: input layer - generates representation of each word of a sentence; LSTM layer - outputs another word representation sequence that captures the context information of each word in this sentence; Inference layer - makes tagging decisions according to the output of LSTM layer, that is, outputting a label sequence. Experiments conducted on corpora of the 2010, 2012 and 2014 i2b2 NLP challenges show that LSTM achieves highest micro-average F1-scores of 85.81% on the 2010 i2b2 medical concept extraction, 92.29% on the 2012 i2b2 clinical event detection, and 94.37% on the 2014 i2b2 de-identification, which is considerably competitive with other state-of-the-art systems. LSTM that requires no hand-crafted feature has great potential on entity recognition from clinical texts. It outperforms traditional machine learning methods that suffer from fussy feature engineering. A possible future direction is how to integrate knowledge

  6. Early recognition of technological opportunities. Realization and perspectives

    International Nuclear Information System (INIS)

    Stegelmann, H.U.; Peters, H.P.; Stein, G.; Muench, E.

    1988-03-01

    In cooperation with the American consulting company Arthur D. Little, a number of procedures, including evaluation of literature data banks, expert interviews and expert workshops, were tried. A three-step concept was finally developed involving identification of candidate technologies (identification), collection of information on these candidates (exploration), ultimately leading to an assessment of the candidate technologies (evaluation). Such a procedure basically enables long-term observation of the scientific policy decisions. This information may serve to identify the deficits and strength of the German scientific system in comparison to that of other countries. Such a system permits the survey and documentation of scientists' subjective expectations on the trends of technology developments and the associated economic and other social consequences. It became apparent that this concept should not raise expectations too high and that it is not essentially different from the advisory instruments already employed today (advisory councils, expert consultants), but rather that these established procedures are merely systematized and supplemented by further information sources (e.g. data banks). In implementing this study two central sets of problems were identified which must be overcome: The early recognition of opportunities is in the long run based on analysts infiltrating the existing network of specialist scientists and examining the information in circulation there with respect to the aims of early recognition so that access to this network is a decisive requirement for an institutionalization of early recognition; incentive systems must be created motivating scientists to become actively involved in the early recognition of technological opportunities. (orig./HP) [de

  7. On techniques for angle compensation in nonideal iris recognition.

    Science.gov (United States)

    Schuckers, Stephanie A C; Schmid, Natalia A; Abhyankar, Aditya; Dorairaj, Vivekanand; Boyce, Christopher K; Hornak, Lawrence A

    2007-10-01

    The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a distance. In this paper, we describe two nonideal iris recognition systems and analyze their performance. The word "nonideal" is used in the sense of compensating for off-angle occluded iris images. The system is designed to process nonideal iris images in two steps: 1) compensation for off-angle gaze direction and 2) processing and encoding of the rotated iris image. Two approaches are presented to account for angular variations in the iris images. In the first approach, we use Daugman's integrodifferential operator as an objective function to estimate the gaze direction. After the angle is estimated, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. The encoding technique developed for a frontal image is based on the application of the global independent component analysis. The second approach uses an angular deformation calibration model. The angular deformations are modeled, and calibration parameters are calculated. The proposed method consists of a closed-form solution, followed by an iterative optimization procedure. The images are projected on the plane closest to the base calibrated plane. Biorthogonal wavelets are used for encoding to perform iris recognition. We use a special dataset of the off-angle iris images to quantify the performance of the designed systems. A series of receiver operating characteristics demonstrate various effects on the performance of the nonideal-iris-based recognition system.

  8. ASERA: A spectrum eye recognition assistant for quasar spectra

    Science.gov (United States)

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

    2013-11-01

    Spectral type recognition is an important and fundamental step of large sky survey projects in the data reduction for further scientific research, like parameter measurement and statistic work. It tends out to be a huge job to manually inspect the low quality spectra produced from the massive spectroscopic survey, where the automatic pipeline may not provide confident type classification results. In order to improve the efficiency and effectiveness of spectral classification, we develop a semi-automated toolkit named ASERA, ASpectrum Eye Recognition Assistant. The main purpose of ASERA is to help the user in quasar spectral recognition and redshift measurement. Furthermore it can also be used to recognize various types of spectra of stars, galaxies and AGNs (Active Galactic Nucleus). It is an interactive software allowing the user to visualize observed spectra, superimpose template spectra from the Sloan Digital Sky Survey (SDSS), and interactively access related spectral line information. It is an efficient and user-friendly toolkit for the accurate classification of spectra observed by LAMOST (the Large Sky Area Multi-object Fiber Spectroscopic Telescope). The toolkit is available in two modes: a Java standalone application and a Java applet. ASERA has a few functions, such as wavelength and flux scale setting, zoom in and out, redshift estimation, spectral line identification, which helps user to improve the spectral classification accuracy especially for low quality spectra and reduce the labor of eyeball check. The function and performance of this tool is displayed through the recognition of several quasar spectra and a late type stellar spectrum from the LAMOST Pilot survey. Its future expansion capabilities are discussed.

  9. Chiral recognition in separation science: an overview.

    Science.gov (United States)

    Scriba, Gerhard K E

    2013-01-01

    Chiral recognition phenomena play an important role in nature as well as analytical separation sciences. In separation sciences such as chromatography and capillary electrophoresis, enantiospecific interactions between the enantiomers of an analyte and the chiral selector are required in order to observe enantioseparations. Due to the large structural variety of chiral selectors applied, different mechanisms and structural features contribute to the chiral recognition process. This chapter briefly illustrates the current models of the enantiospecific recognition on the structural basics of various chiral selectors.

  10. Employee Recognition and Performance: A Field Experiment

    OpenAIRE

    Bradler, Christiane; Dur, Robert; Neckermann, Susanne; Non, Arjan

    2014-01-01

    This discussion paper led to a publication in 'Management Science' . This paper reports the results from a controlled field experiment designed to investigate the causal effect of unannounced, public recognition on employee performance. We hired more than 300 employees to work on a three-hour data-entry task. In a random sample of work groups, workers unexpectedly received recognition after two hours of work. We find that recognition increases subsequent performance substantially, and particu...

  11. Artificial Neural Network Based Optical Character Recognition

    OpenAIRE

    Vivek Shrivastava; Navdeep Sharma

    2012-01-01

    Optical Character Recognition deals in recognition and classification of characters from an image. For the recognition to be accurate, certain topological and geometrical properties are calculated, based on which a character is classified and recognized. Also, the Human psychology perceives characters by its overall shape and features such as strokes, curves, protrusions, enclosures etc. These properties, also called Features are extracted from the image by means of spatial pixel-...

  12. A Bayesian classifier for symbol recognition

    OpenAIRE

    Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick

    2007-01-01

    URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...

  13. Object feature extraction and recognition model

    International Nuclear Information System (INIS)

    Wan Min; Xiang Rujian; Wan Yongxing

    2001-01-01

    The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained

  14. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  15. Dynamic Programming Algorithms in Speech Recognition

    Directory of Open Access Journals (Sweden)

    Titus Felix FURTUNA

    2008-01-01

    Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.

  16. SURVEY OF BIOMETRIC SYSTEMS USING IRIS RECOGNITION

    OpenAIRE

    S.PON SANGEETHA; DR.M.KARNAN

    2014-01-01

    The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...

  17. Context reinstatement in recognition: memory and beyond

    OpenAIRE

    Hanczakowski, M; Zawadzka, K; Coote, L

    2014-01-01

    Context effects in recognition tests are twofold. First, presenting familiar contexts at a test leads to an attribution of context familiarity to a recognition probe, which has been dubbed ‘context-dependent recognition’. Second, reinstating the exact study context for a particular target in a recognition test cues recollection of an item-context association, resulting in ‘context-dependent discrimination’. Here we investigated how these two context effects are expressed in metacognitive moni...

  18. Pedestrian recognition using automotive radar sensors

    OpenAIRE

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

    2012-01-01

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

  19. Biomechanical influences on balance recovery by stepping.

    Science.gov (United States)

    Hsiao, E T; Robinovitch, S N

    1999-10-01

    Stepping represents a common means for balance recovery after a perturbation to upright posture. Yet little is known regarding the biomechanical factors which determine whether a step succeeds in preventing a fall. In the present study, we developed a simple pendulum-spring model of balance recovery by stepping, and used this to assess how step length and step contact time influence the effort (leg contact force) and feasibility of balance recovery by stepping. We then compared model predictions of step characteristics which minimize leg contact force to experimentally observed values over a range of perturbation strengths. At all perturbation levels, experimentally observed step execution times were higher than optimal, and step lengths were smaller than optimal. However, the predicted increase in leg contact force associated with these deviations was substantial only for large perturbations. Furthermore, increases in the strength of the perturbation caused subjects to take larger, quicker steps, which reduced their predicted leg contact force. We interpret these data to reflect young subjects' desire to minimize recovery effort, subject to neuromuscular constraints on step execution time and step length. Finally, our model predicts that successful balance recovery by stepping is governed by a coupling between step length, step execution time, and leg strength, so that the feasibility of balance recovery decreases unless declines in one capacity are offset by enhancements in the others. This suggests that one's risk for falls may be affected more by small but diffuse neuromuscular impairments than by larger impairment in a single motor capacity.

  20. End-Stop Exemplar Based Recognition

    DEFF Research Database (Denmark)

    Olsen, Søren I.

    2003-01-01

    An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring int...... interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion....

  1. Repetition and lag effects in movement recognition.

    Science.gov (United States)

    Hall, C R; Buckolz, E

    1982-03-01

    Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

  2. Man machine interface based on speech recognition

    International Nuclear Information System (INIS)

    Jorge, Carlos A.F.; Aghina, Mauricio A.C.; Mol, Antonio C.A.; Pereira, Claudio M.N.A.

    2007-01-01

    This work reports the development of a Man Machine Interface based on speech recognition. The system must recognize spoken commands, and execute the desired tasks, without manual interventions of operators. The range of applications goes from the execution of commands in an industrial plant's control room, to navigation and interaction in virtual environments. Results are reported for isolated word recognition, the isolated words corresponding to the spoken commands. For the pre-processing stage, relevant parameters are extracted from the speech signals, using the cepstral analysis technique, that are used for isolated word recognition, and corresponds to the inputs of an artificial neural network, that performs recognition tasks. (author)

  3. Fusing Facial Features for Face Recognition

    Directory of Open Access Journals (Sweden)

    Jamal Ahmad Dargham

    2012-06-01

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

  4. Face Recognition and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Swapnil Vitthal Tathe

    2017-07-01

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

  5. The structure of stepped surfaces

    International Nuclear Information System (INIS)

    Algra, A.J.

    1981-01-01

    The state-of-the-art of Low Energy Ion Scattering (LEIS) as far as multiple scattering effects are concerned, is discussed. The ion fractions of lithium, sodium and potassium scattered from a copper (100) surface have been measured as a function of several experimental parameters. The ratio of the intensities of the single and double scattering peaks observed in ion scattering spectroscopy has been determined and ion scattering spectroscopy applied in the multiple scattering mode is used to determine the structure of a stepped Cu(410) surface. The average relaxation of the (100) terraces of this surface appears to be very small. The adsorption of oxygen on this surface has been studied with LEIS and it is indicated that oxygen absorbs dissociatively. (C.F.)

  6. A step toward nuclear sanity

    International Nuclear Information System (INIS)

    Gottfried, K.; Long, F.

    1988-01-01

    This paper reports that Reykjavik formally ended as a diplomatic failure, but it has begun an overdue revolution in perceptions. At long last, both superpowers have the in concrete terms that vastly smaller nuclear arsenals would make them safer. Implicitly, they are saying that nuclear weapons are not useful weapons. Those insights are a prerequisite to nuclear sanity. The United States has proposed to eliminate all strategic ballistic missiles, on land and submarines, in two five-year steps. During that period, we (and presumably the Soviet Union) would develop missile defenses to be deployed in ten years. The first part of this plan makes excellent sense. Ballistic missiles explode on their targets ten to thirty minutes after launch. Today's huge and accurate missile arsenals have forced both superpowers to adopt a hair-trigger stance: they might launch missiles simply on warning of attack

  7. Steps towards an evolutionary physics

    CERN Document Server

    Tiezzi, E

    2006-01-01

    If thermodynamics is to physics as logic is to philosophy, recent theoretical advancements lend new coherence to the marvel and dynamism of life on Earth. Enzo Tiezzi's "Steps Towards an Evolutionary Physics" is a primer and guide, to those who would to stand on the shoulders of giants to attain this view: Heisenberg, Planck, Bateson, Varela, and Prigogine as well as notable contemporary scientists. The adventure of such a free and enquiring spirit thrives not so much on answers as on new questions. The book offers a new gestalt on the uncertainty principle and concept of probability. A wide range of examples, enigmas, and paradoxes lead one's imagination on an exquisite dance. Among the applications are: songs and shapes of nature, oscillatory reactions, orientors, goal functions and configurations of processes, and "dissipative structures and the city". Ecodynamics is a new science, which proposes a cross-fertilization between Charles Darwin and Ilya Prigogine. As an enigma in thermodynamics, Entropy forms ...

  8. Boris push with spatial stepping

    International Nuclear Information System (INIS)

    Penn, G; Stoltz, P H; Cary, J R; Wurtele, J

    2003-01-01

    The Boris push is commonly used in plasma physics simulations because of its speed and stability. It is second-order accurate, requires only one field evaluation per time step, and has good conservation properties. However, for accelerator simulations it is convenient to propagate particles in z down a changing beamline. A 'spatial Boris push' algorithm has been developed which is similar to the Boris push but uses a spatial coordinate as the independent variable, instead of time. This scheme is compared to the fourth-order Runge-Kutta algorithm, for two simplified muon beam lattices: a uniform solenoid field, and a 'FOFO' lattice where the solenoid field varies sinusoidally along the axis. Examination of the canonical angular momentum, which should be conserved in axisymmetric systems, shows that the spatial Boris push improves accuracy over long distances

  9. The devil you know: The effect of brand recognition and product ratings on consumer choice

    Directory of Open Access Journals (Sweden)

    Volker Thoma

    2013-01-01

    Full Text Available Previous research on the role of recognition in decision-making in inferential choice has focussed on the Recognition Heuristic (RH, which proposes that in situations where recognition is predictive of a decision criterion, recognized objects will be chosen over unrecognized ones, regardless of any other available relevant information. In the current study we examine the role of recognition in preferential choice, in which subjects had to choose one of a pair of consumer objects that were presented with quality ratings (positive, neutral, and negative. The results showed that subjects' choices were largely based on recognition, as the famous brand was preferred even when additional star ratings rendered it as less attractive. However, the additional information did affect the proportion of chosen famous items, in particular in the cases when star ratings for the recognised brand were negative. This condition also resulted in longer response times compared to neutral and positive conditions. Thus, the current data do not point to a simple compensatory mechanism in preferential choice: although choice is affected by additional information, it seems that recognition is employed as an initial important first step in the decision-making process.

  10. Preimages for Step-Reduced SHA-2

    DEFF Research Database (Denmark)

    Aoki, Kazumaro; Guo, Jian; Matusiewicz, Krystian

    2009-01-01

    In this paper, we present preimage attacks on up to 43-step SHA-256 (around 67% of the total 64 steps) and 46-step SHA-512 (around 57.5% of the total 80 steps), which significantly increases the number of attacked steps compared to the best previously published preimage attack working for 24 steps....... The time complexities are 2^251.9, 2^509 for finding pseudo-preimages and 2^254.9, 2^511.5 compression function operations for full preimages. The memory requirements are modest, around 2^6 words for 43-step SHA-256 and 46-step SHA-512. The pseudo-preimage attack also applies to 43-step SHA-224 and SHA-384...

  11. Linking pedestrian flow characteristics with stepping locomotion

    Science.gov (United States)

    Wang, Jiayue; Boltes, Maik; Seyfried, Armin; Zhang, Jun; Ziemer, Verena; Weng, Wenguo

    2018-06-01

    While properties of human traffic flow are described by speed, density and flow, the locomotion of pedestrian is based on steps. To relate characteristics of human locomotor system with properties of human traffic flow, this paper aims to connect gait characteristics like step length, step frequency, swaying amplitude and synchronization with speed and density and thus to build a ground for advanced pedestrian models. For this aim, observational and experimental study on the single-file movement of pedestrians at different densities is conducted. Methods to measure step length, step frequency, swaying amplitude and step synchronization are proposed by means of trajectories of the head. Mathematical models for the relations of step length or frequency and speed are evaluated. The problem how step length and step duration are influenced by factors like body height and density is investigated. It is shown that the effect of body height on step length and step duration changes with density. Furthermore, two different types of step in-phase synchronization between two successive pedestrians are observed and the influence of step synchronization on step length is examined.

  12. Hand gesture recognition by analysis of codons

    Science.gov (United States)

    Ramachandra, Poornima; Shrikhande, Neelima

    2007-09-01

    The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) [2]. The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.

  13. Impact of Sliding Window Length in Indoor Human Motion Modes and Pose Pattern Recognition Based on Smartphone Sensors

    Directory of Open Access Journals (Sweden)

    Gaojing Wang

    2018-06-01

    Full Text Available Human activity recognition (HAR is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applied to HAR. Data segmentation using a sliding window is a basic step during the HAR procedure, wherein the window length directly affects recognition performance. However, the window length is generally randomly selected without systematic study. In this study, we examined the impact of window length on smartphone sensor-based human motion and pose pattern recognition. With data collected from smartphone sensors, we tested a range of window lengths on five popular machine-learning methods: decision tree, support vector machine, K-nearest neighbor, Gaussian naïve Bayesian, and adaptive boosting. From the results, we provide recommendations for choosing the appropriate window length. Results corroborate that the influence of window length on the recognition of motion modes is significant but largely limited to pose pattern recognition. For motion mode recognition, a window length between 2.5–3.5 s can provide an optimal tradeoff between recognition performance and speed. Adaptive boosting outperformed the other methods. For pose pattern recognition, 0.5 s was enough to obtain a satisfactory result. In addition, all of the tested methods performed well.

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

    Directory of Open Access Journals (Sweden)

    Jiangyi Qin

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

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

    Science.gov (United States)

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

    2015-01-01

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

  16. System for automatic crate recognition

    Directory of Open Access Journals (Sweden)

    Radovan Kukla

    2012-01-01

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

  17. Recognition of Handwriting from Electromyography

    Science.gov (United States)

    Linderman, Michael; Lebedev, Mikhail A.; Erlichman, Joseph S.

    2009-01-01

    Handwriting – one of the most important developments in human culture – is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals – the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear. PMID:19707562

  18. Action Recognition using Motion Primitives

    DEFF Research Database (Denmark)

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

    the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize......The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent...... different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognizing rates of 88.7% and 85.5%, respectively....

  19. New methods in iris recognition.

    Science.gov (United States)

    Daugman, John

    2007-10-01

    This paper presents the following four advances in iris recognition: 1) more disciplined methods for detecting and faithfully modeling the iris inner and outer boundaries with active contours, leading to more flexible embedded coordinate systems; 2) Fourier-based methods for solving problems in iris trigonometry and projective geometry, allowing off-axis gaze to be handled by detecting it and "rotating" the eye into orthographic perspective; 3) statistical inference methods for detecting and excluding eyelashes; and 4) exploration of score normalizations, depending on the amount of iris data that is available in images and the required scale of database search. Statistical results are presented based on 200 billion iris cross-comparisons that were generated from 632500 irises in the United Arab Emirates database to analyze the normalization issues raised in different regions of receiver operating characteristic curves.

  20. Further insight into self-face recognition in schizophrenia patients: Why ambiguity matters.

    Science.gov (United States)

    Bortolon, Catherine; Capdevielle, Delphine; Salesse, Robin N; Raffard, Stephane

    2016-03-01

    Although some studies reported specifically self-face processing deficits in patients with schizophrenia disorder (SZ), it remains unclear whether these deficits rather reflect a more global face processing deficit. Contradictory results are probably due to the different methodologies employed and the lack of control of other confounding factors. Moreover, no study has so far evaluated possible daily life self-face recognition difficulties in SZ. Therefore, our primary objective was to investigate self-face recognition in patients suffering from SZ compared to healthy controls (HC) using an "objective measure" (reaction time and accuracy) and a "subjective measure" (self-report of daily self-face recognition difficulties). Twenty-four patients with SZ and 23 HC performed a self-face recognition task and completed a questionnaire evaluating daily difficulties in self-face recognition. Recognition task material consisted in three different faces (the own, a famous and an unknown) being morphed in steps of 20%. Results showed that SZ were overall slower than HC regardless of the face identity, but less accurate only for the faces containing 60%-40% morphing. Moreover, SZ and HC reported a similar amount of daily problems with self/other face recognition. No significant correlations were found between objective and subjective measures (p > 0.05). The small sample size and relatively mild severity of psychopathology does not allow us to generalize our results. These results suggest that: (1) patients with SZ are as capable of recognizing their own face as HC, although they are susceptible to ambiguity; (2) there are far less self recognition deficits in schizophrenia patients than previously postulated. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Self-Recognition in Autistic Children.

    Science.gov (United States)

    Dawson, Geraldine; McKissick, Fawn Celeste

    1984-01-01

    Fifteen autistic children (four to six years old) were assessed for visual self-recognition ability, as well as for object permanence and gestural imitation. It was found that 13 of 15 autistic children showed evidence of self-recognition. Consistent relationships were suggested between self-cognition and object permanence but not between…

  2. Progesterone impairs social recognition in male rats.

    Science.gov (United States)

    Bychowski, Meaghan E; Auger, Catherine J

    2012-04-01

    The influence of progesterone in the brain and on the behavior of females is fairly well understood. However, less is known about the effect of progesterone in the male system. In male rats, receptors for progesterone are present in virtually all vasopressin (AVP) immunoreactive cells in the bed nucleus of the stria terminalis (BST) and the medial amygdala (MeA). This colocalization functions to regulate AVP expression, as progesterone and/or progestin receptors (PR)s suppress AVP expression in these same extrahypothalamic regions in the brain. These data suggest that progesterone may influence AVP-dependent behavior. While AVP is implicated in numerous behavioral and physiological functions in rodents, AVP appears essential for social recognition of conspecifics. Therefore, we examined the effects of progesterone on social recognition. We report that progesterone plays an important role in modulating social recognition in the male brain, as progesterone treatment leads to a significant impairment of social recognition in male rats. Moreover, progesterone appears to act on PRs to impair social recognition, as progesterone impairment of social recognition is blocked by a PR antagonist, RU-486. Social recognition is also impaired by a specific progestin agonist, R5020. Interestingly, we show that progesterone does not interfere with either general memory or olfactory processes, suggesting that progesterone seems critically important to social recognition memory. These data provide strong evidence that physiological levels of progesterone can have an important impact on social behavior in male rats. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. 77 FR 9590 - Recognition and Accreditation

    Science.gov (United States)

    2012-02-17

    ..., or social service purpose? 5. Discussion of withdrawal of recognition. Are the current procedures for withdrawal of recognition for an organization effective? See 8 CFR 1292.2(c). If not, how can the process be... services in order to ensure that they are serving a non-profit, religious, charitable, or social service...

  4. View based approach to forensic face recognition

    NARCIS (Netherlands)

    Dutta, A.; van Rootseler, R.T.A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    Face recognition is a challenging problem for surveillance view images commonly encountered in a forensic face recognition case. One approach to deal with a non-frontal test image is to synthesize the corresponding frontal view image and compare it with frontal view reference images. However, it is

  5. Wood Variety Recognition on Mobile Devices

    Czech Academy of Sciences Publication Activity Database

    Vácha, Pavel; Haindl, Michal

    2013-01-01

    Roč. 2013, č. 93 (2013), s. 52-52 ISSN 0926-4981 R&D Projects: GA ČR GA102/08/0593 Institutional support: RVO:67985556 Keywords : wood recognition * Markov random fields Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2013/RO/vacha-wood variety recognition on mobile devices.pdf

  6. Recognition without Awareness: Encoding and Retrieval Factors

    Science.gov (United States)

    Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

    2015-01-01

    The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

  7. Physiological arousal in processing recognition information

    Directory of Open Access Journals (Sweden)

    Guy Hochman

    2010-07-01

    Full Text Available The recognition heuristic (RH; Goldstein and Gigerenzer, 2002 suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.

  8. Syllable Transposition Effects in Korean Word Recognition

    Science.gov (United States)

    Lee, Chang H.; Kwon, Youan; Kim, Kyungil; Rastle, Kathleen

    2015-01-01

    Research on the impact of letter transpositions in visual word recognition has yielded important clues about the nature of orthographic representations. This study investigated the impact of syllable transpositions on the recognition of Korean multisyllabic words. Results showed that rejection latencies in visual lexical decision for…

  9. Using Maintenance Rehearsal to Explore Recognition Memory

    Science.gov (United States)

    Humphreys, Michael S.; Maguire, Angela M.; McFarlane, Kimberley A.; Burt, Jennifer S.; Bolland, Scott W.; Murray, Krista L.; Dunn, Ryan

    2010-01-01

    We examined associative and item recognition using the maintenance rehearsal paradigm. Our intent was to control for mnemonic strategies; to produce a low, graded level of learning; and to provide evidence of the role of attention in long-term memory. An advantage for low-frequency words emerged in both associative and item recognition at very low…

  10. Sleep Enhances Explicit Recollection in Recognition Memory

    Science.gov (United States)

    Drosopoulos, Spyridon; Wagner, Ullrich; Born, Jan

    2005-01-01

    Recognition memory is considered to be supported by two different memory processes, i.e., the explicit recollection of information about a previous event and an implicit process of recognition based on a contextual sense of familiarity. Both types of memory supposedly rely on distinct memory systems. Sleep is known to enhance the consolidation of…

  11. Object Recognition Memory and the Rodent Hippocampus

    Science.gov (United States)

    Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.

    2010-01-01

    In rodents, the novel object recognition task (NOR) has become a benchmark task for assessing recognition memory. Yet, despite its widespread use, a consensus has not developed about which brain structures are important for task performance. We assessed both the anterograde and retrograde effects of hippocampal lesions on performance in the NOR…

  12. Color descriptors for object category recognition

    NARCIS (Netherlands)

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

    2008-01-01

    Category recognition is important to access visual information on the level of objects. A common approach is to compute image descriptors first and then to apply machine learning to achieve category recognition from annotated examples. As a consequence, the choice of image descriptors is of great

  13. Effects of Instructions on False Recognition.

    Science.gov (United States)

    Mueller, John H.; And Others

    Four experiments were conducted to examine the effects of various processing instructions on the rate of false recognition. The continuous single-item procedure was used, and false recognitions of four types were examined: synonyms, antonyms, nonsemantic associates, and homonyms. The instructions encouraged subjects to think of associates, usages…

  14. Infants' Delayed Recognition Memory and Forgetting

    Science.gov (United States)

    Fagan, Joseph F., III

    1973-01-01

    Infants 21- to 25-weeks-old devoted more visual fixation to novel than familiar stimuli on immediate and delayed recognition tests. The experiments confirm the existence of long-term recognition memory for pictorial stimuli in the early months of life. (DP)

  15. A New Database for Speaker Recognition

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2005-01-01

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

  16. Face recognition in the thermal infrared domain

    Science.gov (United States)

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

    2017-10-01

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

  17. Pattern recognition methods in air pollution control

    Energy Technology Data Exchange (ETDEWEB)

    Tauber, S

    1978-01-01

    The use of pattern recognition methods for predicting air pollution developments is discussed. Computer analysis of historical pollution data allows comparison in graphical form. An example of crisis prediction for carbon monoxide concentrations, using the pattern recognition method of analysis, is presented. Results of the analysis agreed well with actual CO conditions. (6 graphs, 4 references, 1 table)

  18. Adult Word Recognition and Visual Sequential Memory

    Science.gov (United States)

    Holmes, V. M.

    2012-01-01

    Two experiments were conducted investigating the role of visual sequential memory skill in the word recognition efficiency of undergraduate university students. Word recognition was assessed in a lexical decision task using regularly and strangely spelt words, and nonwords that were either standard orthographically legal strings or items made from…

  19. Voice Recognition in Face-Blind Patients

    Science.gov (United States)

    Liu, Ran R.; Pancaroglu, Raika; Hills, Charlotte S.; Duchaine, Brad; Barton, Jason J. S.

    2016-01-01

    Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia. PMID:25349193

  20. The recognition heuristic: A decade of research

    Directory of Open Access Journals (Sweden)

    Gerd Gigerenzer

    2011-02-01

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

  1. Steps to Advanced CANDU 600

    International Nuclear Information System (INIS)

    Oh, Yongshick; Brooks, G. L.

    1988-01-01

    The CANDU nuclear power system was developed from merging of AECL heavy water reactor technology with Ontario Hydro electrical power station expertise. The original four units of Ontario Hydro's Pickering Generating Station are the first full-scale commercial application of the CANDU system. AECL and Ontario Hydro then moved to the next evolutionary step, a more advanced larger scale design for four units at the Bruce Generating Station. CANDU 600 followed as a single unit nuclear electric power station design derived from an amalgam of features of the multiple unit Pickering and Bruce designs. The design of the CANDU 600 nuclear steam supply system is based on the Pickering design with improvements derived from the Bruce design. For example, most CANDU 600 auxiliary systems are based on Bruce systems, whereas the fuel handling system is based on the Pickering system. Four CANDU 600 units are in operation, and five are under construction in Romania. For the additional four units at Pickering Generating Station 'B', Ontario Hydro selected a replica of the Pickering 'A' design with limited design changes to maintain a high level of standardization across all eight units. Ontario Hydro applied a similar policy for the additional four units at Bruce Generating Station 'B'. For the four unit Darlington station, Ontario Hydro selected a design based on Bruce with improvements derived from operating experience, the CANDU 600 design and development programs

  2. Multi-step direct reactions

    International Nuclear Information System (INIS)

    Koning, A.J.

    1992-07-01

    In recent years a variety of statistical theories has been developed concerning multistep direct (MSD) nuclear reactions. In addition, dominant in applications is a whole class of semiclassical models that may be subsumed under the heading of 'generalized exciton models'; these are basically MSD-type extensions on top of compound-like concepts. In this report the relation between their underlying statistical MSD-postulates are highlighted. A command framework is sketched that enables to generate the various MSD theories through assigning statistical properties to different parts of the nuclear Hamiltonian. Then it is shown that distinct forms of nuclear randomness are embodied in the mentioned theories. All these theories appear to be very similar at a qualitative level. In order to explain the high energy-tails and forward-peaked angular distribution typical for particles emitted in MSD reactions, it is imagined that the incident continuum particle stepwise looses its energy and direction in a sequence of collisions, thereby creating new particle-hole pairs in the target system. At each step emission may take place. The statistical aspect comes in because many continuum states are involved in the process. These are supposed to display chaotic behavior, the associated randomness assumption giving rise to important simplifications in the expression for MSD emission cross sections. This picture suggests that mentioned MSD models can be interpreted as a variant of essentially one and the same theory. 113 refs.; 25 figs.; 9 tabs

  3. Invariant Face recognition Using Infrared Images

    International Nuclear Information System (INIS)

    Zahran, E.G.

    2012-01-01

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

  4. Critical flux determination by flux-stepping

    DEFF Research Database (Denmark)

    Beier, Søren; Jonsson, Gunnar Eigil

    2010-01-01

    In membrane filtration related scientific literature, often step-by-step determined critical fluxes are reported. Using a dynamic microfiltration device, it is shown that critical fluxes determined from two different flux-stepping methods are dependent upon operational parameters such as step...... length, step height, and.flux start level. Filtrating 8 kg/m(3) yeast cell suspensions by a vibrating 0.45 x 10(-6) m pore size microfiltration hollow fiber module, critical fluxes from 5.6 x 10(-6) to 1.2 x 10(-5) m/s have been measured using various step lengths from 300 to 1200 seconds. Thus......, such values are more or less useless in itself as critical flux predictors, and constant flux verification experiments have to be conducted to check if the determined critical fluxes call predict sustainable flux regimes. However, it is shown that using the step-by-step predicted critical fluxes as start...

  5. Degraded character recognition based on gradient pattern

    Science.gov (United States)

    Babu, D. R. Ramesh; Ravishankar, M.; Kumar, Manish; Wadera, Kevin; Raj, Aakash

    2010-02-01

    Degraded character recognition is a challenging problem in the field of Optical Character Recognition (OCR). The performance of an optical character recognition depends upon printed quality of the input documents. Many OCRs have been designed which correctly identifies the fine printed documents. But, very few reported work has been found on the recognition of the degraded documents. The efficiency of the OCRs system decreases if the input image is degraded. In this paper, a novel approach based on gradient pattern for recognizing degraded printed character is proposed. The approach makes use of gradient pattern of an individual character for recognition. Experiments were conducted on character image that is either digitally written or a degraded character extracted from historical documents and the results are found to be satisfactory.

  6. Flexible Piezoelectric Sensor-Based Gait Recognition

    Directory of Open Access Journals (Sweden)

    Youngsu Cha

    2018-02-01

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

  7. State Toleration, Religious Recognition and Equality

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2013-01-01

    In debates about multiculturalism, it is widely claimed that ‘toleration is not enough’ and that we need to go ‘beyond toleration’ to some form of politics of recognition in order to satisfactorily address contemporary forms of cultural diversity (e.g. the presence in Europe of Muslim minorities...... a conceptual question of whether the relation between states and minorities can be categoriseized in terms of recognition or toleration, but about a normative question of whether and how toleration and recognition secures equality. When toleration is inadequate, this is often because it institutionaliseizes...... and upholds specific inequalities. But politics of recognition may equally well institute inequalities, and in such cases unequal recognition may not be preferable to toleration....

  8. Activity recognition from minimal distinguishing subsequence mining

    Science.gov (United States)

    Iqbal, Mohammad; Pao, Hsing-Kuo

    2017-08-01

    Human activity recognition is one of the most important research topics in the era of Internet of Things. To separate different activities given sensory data, we utilize a Minimal Distinguishing Subsequence (MDS) mining approach to efficiently find distinguishing patterns among different activities. We first transform the sensory data into a series of sensor triggering events and operate the MDS mining procedure afterwards. The gap constraints are also considered in the MDS mining. Given the multi-class nature of most activity recognition tasks, we modify the MDS mining approach from a binary case to a multi-class one to fit the need for multiple activity recognition. We also study how to select the best parameter set including the minimal and the maximal support thresholds in finding the MDSs for effective activity recognition. Overall, the prediction accuracy is 86.59% on the van Kasteren dataset which consists of four different activities for recognition.

  9. Recognition of names of eminent psychologists.

    Science.gov (United States)

    Duncan, C P

    1976-10-01

    Faculty members, graduate students, undergraduate majors, and introductory psychology students checked those names they recognized in the list of 228 deceased psychologists, rated for eminence, provided by Annin, Boring, and Watson. Mean percentage recognition was less than 50% for the 128 American psychologists, and less than 25% for the 100 foreign psychologists, by the faculty subjects. The other three groups of subjects gave even lower recognition scores. Recognition was probably also influenced by recency; median year of death of the American psychologists was 1955, of the foreign psychologists, 1943. High recognition (defined as recognition by 80% or more of the faculty group) was achieved by only 34 psychologists, almost all of them American. These highly recognized psychologists also had high eminence ratings, but there was an equal number of psychologists with high eminence ratings that were poorly recognized.

  10. Step dynamics and terrace-width distribution on flame-annealed gold films: The effect of step-step interaction

    International Nuclear Information System (INIS)

    Shimoni, Nira; Ayal, Shai; Millo, Oded

    2000-01-01

    Dynamics of atomic steps and the terrace-width distribution within step bunches on flame-annealed gold films are studied using scanning tunneling microscopy. The distribution is narrower than commonly observed for vicinal planes and has a Gaussian shape, indicating a short-range repulsive interaction between the steps, with an apparently large interaction constant. The dynamics of the atomic steps, on the other hand, appear to be influenced, in addition to these short-range interactions, also by a longer-range attraction of steps towards step bunches. Both types of interactions promote self-ordering of terrace structures on the surface. When current is driven through the films a step-fingering instability sets in, reminiscent of the Bales-Zangwill instability

  11. Ten steps to successful software process improvement

    Science.gov (United States)

    Kandt, R. K.

    2003-01-01

    This paper identifies ten steps for managing change that address organizational and cultural issues. Four of these steps are critical, that if not done, will almost guarantee failure. This ten-step program emphasizes the alignment of business goals, change process goals, and the work performed by the employees of an organization.

  12. 7 CFR 65.230 - Production step.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 3 2010-01-01 2010-01-01 false Production step. 65.230 Section 65.230 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards..., PEANUTS, AND GINSENG General Provisions Definitions § 65.230 Production step. Production step means, in...

  13. Apply lightweight recognition algorithms in optical music recognition

    Science.gov (United States)

    Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet

    2015-02-01

    The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical M ∗ N cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.

  14. Traffic safety and step-by-step driving licence for young people

    DEFF Research Database (Denmark)

    Tønning, Charlotte; Agerholm, Niels

    2017-01-01

    presents a review of safety effects from step-by-step driving licence schemes. Most of the investigated schemes consist of a step-by-step driving licence with Step 1) various tests and education, Step 2) a period where driving is only allowed together with an experienced driver and Step 3) driving without...... companion is allowed but with various restrictions and, in some cases, additional driving education and tests. In general, a step-by-step driving licence improves traffic safety even though the young people are permitted to drive a car earlier on. The effects from driving with an experienced driver vary......Young novice car drivers are much more accident-prone than other drivers - up to 10 times that of their parents' generation. A central solution to improve the traffic safety for this group is implementation of a step-by-step driving licence. A number of countries have introduced a step...

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

    Directory of Open Access Journals (Sweden)

    Zhao Yibing

    2014-01-01

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

  16. Enhanced bag of words using multilevel k-means for human activity recognition

    Directory of Open Access Journals (Sweden)

    Motasem Elshourbagy

    2016-07-01

    Full Text Available This paper aims to enhance the bag of features in order to improve the accuracy of human activity recognition. In this paper, human activity recognition process consists of four stages: local space time features detection, feature description, bag of features representation, and SVMs classification. The k-means step in the bag of features is enhanced by applying three levels of clustering: clustering per video, clustering per action class, and clustering for the final code book. The experimental results show that the proposed method of enhancement reduces the time and memory requirements, and enables the use of all training data in the k-means clustering algorithm. The evaluation of accuracy of action classification on two popular datasets (KTH and Weizmann has been performed. In addition, the proposed method improves the human activity recognition accuracy by 5.57% on the KTH dataset using the same detector, descriptor, and classifier.

  17. THE DESIGN OF KNOWLEDGE BASE FOR SURFACE RELATIONS BASED PART RECOGNITION APPROACH

    Directory of Open Access Journals (Sweden)

    Adem ÇİÇEK

    2007-01-01

    Full Text Available In this study, a new knowledge base for an expert system used in part recognition algorithm has been designed. Parts are recognized by the computer program by comparing face adjacency relations and attributes belonging to each part represented in the rules in the knowledge base developed with face adjacency relations and attributes generated from STEP file of the part. Besides, rule writing process has been quite simplified by generating the rules represented in the knowledge base with an automatic rule writing module developed within the system. With the knowledge base and automatic rule writing module used in the part recognition system, simple, intermediate and complex parts can be recognized by a part recognition program.

  18. Infant visual attention and object recognition.

    Science.gov (United States)

    Reynolds, Greg D

    2015-05-15

    This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

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

    2009-01-01

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

  20. 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.

  1. Implicit recognition based on lateralized perceptual fluency.

    Science.gov (United States)

    Vargas, Iliana M; Voss, Joel L; Paller, Ken A

    2012-02-06

    In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this "implicit recognition" results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

  2. Textual emotion recognition for enhancing enterprise computing

    Science.gov (United States)

    Quan, Changqin; Ren, Fuji

    2016-05-01

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

  3. Window Size Impact in Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Oresti Banos

    2014-04-01

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

  4. [Face recognition in patients with schizophrenia].

    Science.gov (United States)

    Doi, Hirokazu; Shinohara, Kazuyuki

    2012-07-01

    It is well known that patients with schizophrenia show severe deficiencies in social communication skills. These deficiencies are believed to be partly derived from abnormalities in face recognition. However, the exact nature of these abnormalities exhibited by schizophrenic patients with respect to face recognition has yet to be clarified. In the present paper, we review the main findings on face recognition deficiencies in patients with schizophrenia, particularly focusing on abnormalities in the recognition of facial expression and gaze direction, which are the primary sources of information of others' mental states. The existing studies reveal that the abnormal recognition of facial expression and gaze direction in schizophrenic patients is attributable to impairments in both perceptual processing of visual stimuli, and cognitive-emotional responses to social information. Furthermore, schizophrenic patients show malfunctions in distributed neural regions, ranging from the fusiform gyrus recruited in the structural encoding of facial stimuli, to the amygdala which plays a primary role in the detection of the emotional significance of stimuli. These findings were obtained from research in patient groups with heterogeneous characteristics. Because previous studies have indicated that impairments in face recognition in schizophrenic patients might vary according to the types of symptoms, it is of primary importance to compare the nature of face recognition deficiencies and the impairments of underlying neural functions across sub-groups of patients.

  5. PATTER, Pattern Recognition Data Analysis

    International Nuclear Information System (INIS)

    Cox, L.C. Jr.; Bender, C.F.

    1986-01-01

    1 - Description of program or function: PATTER is an interactive program with extensive facilities for modeling analytical processes and solving complex data analysis problems using statistical methods, spectral analysis, and pattern recognition techniques. PATTER addresses the type of problem generally stated as follows: given a set of objects and a list of measurements made on these objects, is it possible to find or predict a property of the objects which is not directly measurable but is known to define some unknown relationship? When employed intelligently, PATTER will act upon a data set in such a way it becomes apparent if useful information, beyond that already discerned, is contained in the data. 2 - Method of solution: In order to solve the general problem, PATTER contains preprocessing techniques to produce new variables that are related to the values of the measurements which may reduce the number of variables and/or reveal useful information about the 'obscure' property; display techniques to represent the variable space in some way that can be easily projected onto a two- or three-dimensional plot for human observation to see if any significant clustering of points occurs; and learning techniques based on both unsupervised and supervised methods, to extract as much information from the data as possible so that the optimum solution can be found

  6. DCT-based iris recognition.

    Science.gov (United States)

    Monro, Donald M; Rakshit, Soumyadip; Zhang, Dexin

    2007-04-01

    This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. The feature extraction capabilities of the DCT are optimized on the two largest publicly available iris image data sets, 2,156 images of 308 eyes from the CASIA database and 2,955 images of 150 eyes from the Bath database. On this data, we achieve 100 percent Correct Recognition Rate (CRR) and perfect Receiver-Operating Characteristic (ROC) Curves with no registered false accepts or rejects. Individual feature bit and patch position parameters are optimized for matching through a product-of-sum approach to Hamming distance calculation. For verification, a variable threshold is applied to the distance metric and the False Acceptance Rate (FAR) and False Rejection Rate (FRR) are recorded. A new worst-case metric is proposed for predicting practical system performance in the absence of matching failures, and the worst case theoretical Equal Error Rate (EER) is predicted to be as low as 2.59 x 10(-4) on the available data sets.

  7. Recurrent processing during object recognition

    Directory of Open Access Journals (Sweden)

    Randall C. O'Reilly

    2013-04-01

    Full Text Available How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of of naturally-occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain's visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time.

  8. Radioligand Recognition of Insecticide Targets.

    Science.gov (United States)

    Casida, John E

    2018-04-04

    Insecticide radioligands allow the direct recognition and analysis of the targets and mechanisms of toxic action critical to effective and safe pest control. These radioligands are either the insecticides themselves or analogs that bind at the same or coupled sites. Preferred radioligands and their targets, often in both insects and mammals, are trioxabicyclooctanes for the γ-aminobutyric acid (GABA) receptor, avermectin for the glutamate receptor, imidacloprid for the nicotinic receptor, ryanodine and chlorantraniliprole for the ryanodine receptor, and rotenone or pyridaben for NADH + ubiquinone oxidoreductase. Pyrethroids and other Na + channel modulator insecticides are generally poor radioligands due to lipophilicity and high nonspecific binding. For target site validation, the structure-activity relationships competing with the radioligand in the binding assays should be the same as that for insecticidal activity or toxicity except for rapidly detoxified or proinsecticide analogs. Once the radioligand assay is validated for relevance, it will often help define target site modifications on selection of resistant pest strains, selectivity between insects and mammals, and interaction with antidotes and other chemicals at modulator sites. Binding assays also serve for receptor isolation and photoaffinity labeling to characterize the interactions involved.

  9. Single-Molecule View of Small RNA-Guided Target Search and Recognition.

    Science.gov (United States)

    Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

    2018-05-20

    Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

  10. Robust recognition via information theoretic learning

    CERN Document Server

    He, Ran; Yuan, Xiaotong; Wang, Liang

    2014-01-01

    This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

  11. Gait recognition based on integral outline

    Science.gov (United States)

    Ming, Guan; Fang, Lv

    2017-02-01

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

  12. Participation, Recognition and the Democratic Doxa

    DEFF Research Database (Denmark)

    Harrits, Gitte Sommer

    2006-01-01

    to the exclusionary effects of norms of citizenship, i.e. the exclusionfrom within, and suggest the recognition of group differences. This paper tries to suggest, how a Bourdieu-perspective can help bridge the gap of dichotomies such as individual/group, universalism/particularism and rights/recognition. The paper...... suggest that a democratisation of the political doxa, involving the recognition of differences in political habitus and (most importantly) practices is necessary to oppose the tendencies of exclusion and to further a widespread empowerment of citizens in late modern societies, without this turing...

  13. Improved pattern recognition systems by hybrid methods

    International Nuclear Information System (INIS)

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

    1978-12-01

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

  14. Robust speaker recognition in noisy environments

    CERN Document Server

    Rao, K Sreenivasa

    2014-01-01

    This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.

  15. Cortical Networks for Visual Self-Recognition

    Science.gov (United States)

    Sugiura, Motoaki

    This paper briefly reviews recent developments regarding the brain mechanisms of visual self-recognition. A special cognitive mechanism for visual self-recognition has been postulated based on behavioral and neuropsychological evidence, but its neural substrate remains controversial. Recent functional imaging studies suggest that multiple cortical mechanisms play self-specific roles during visual self-recognition, reconciling the existing controversy. Respective roles for the left occipitotemporal, right parietal, and frontal cortices in symbolic, visuospatial, and conceptual aspects of self-representation have been proposed.

  16. Cortical networks for visual self-recognition

    International Nuclear Information System (INIS)

    Sugiura, Motoaki

    2007-01-01

    This paper briefly reviews recent developments regarding the brain mechanisms of visual self-recognition. A special cognitive mechanism for visual self-recognition has been postulated based on behavioral and neuropsychological evidence, but its neural substrate remains controversial. Recent functional imaging studies suggest that multiple cortical mechanisms play self-specific roles during visual self-recognition, reconciling the existing controversy. Respective roles for the left occipitotemporal, right parietal, and frontal cortices in symbolic, visuospatial, and conceptual aspects of self-representation have been proposed. (author)

  17. Pattern recognition and classification an introduction

    CERN Document Server

    Dougherty, Geoff

    2012-01-01

    The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

  18. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open......CV library is used for signal processing. We conclude that the approach presented here is a viable solution to pattern recognition problems. Since it requires no network connection, it shows promise in fields such as wildlife research....

  19. Robustness-related issues in speaker recognition

    CERN Document Server

    Zheng, Thomas Fang

    2017-01-01

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

  20. A LITERATURE SURVEY ON VARIOUS ILLUMINATION NORMALIZATION TECHNIQUES FOR FACE RECOGNITION WITH FUZZY K NEAREST NEIGHBOUR CLASSIFIER

    Directory of Open Access Journals (Sweden)

    A. Thamizharasi

    2015-05-01

    Full Text Available The face recognition is popular in video surveillance, social networks and criminal identifications nowadays. The performance of face recognition would be affected by variations in illumination, pose, aging and partial occlusion of face by Wearing Hats, scarves and glasses etc. The illumination variations are still the challenging problem in face recognition. The aim is to compare the various illumination normalization techniques. The illumination normalization techniques include: Log transformations, Power Law transformations, Histogram equalization, Adaptive histogram equalization, Contrast stretching, Retinex, Multi scale Retinex, Difference of Gaussian, DCT, DCT Normalization, DWT, Gradient face, Self Quotient, Multi scale Self Quotient and Homomorphic filter. The proposed work consists of three steps. First step is to preprocess the face image with the above illumination normalization techniques; second step is to create the train and test database from the preprocessed face images and third step is to recognize the face images using Fuzzy K nearest neighbor classifier. The face recognition accuracy of all preprocessing techniques is compared using the AR face database of color images.

  1. Development of pattern recognition algorithms for the central drift chamber of the Belle II detector

    Energy Technology Data Exchange (ETDEWEB)

    Trusov, Viktor

    2016-11-04

    In this thesis, the development of one of the pattern recognition algorithms for the Belle II experiment based on conformal and Legendre transformations is presented. In order to optimize the performance of the algorithm (CPU time and efficiency) specialized processing steps have been introduced. To show achieved results, Monte-Carlo based efficiency measurements of the tracking algorithms in the Central Drift Chamber (CDC) has been done.

  2. Step-grandparenthood in the United States.

    Science.gov (United States)

    Yahirun, Jenjira J; Park, Sung S; Seltzer, Judith A

    2018-01-18

    This study provides new information about the demography of step-grandparenthood in the United States. Specifically, we examine the prevalence of step-grandparenthood across birth cohorts and for socioeconomic and racial/ethnic groups. We also examine lifetime exposure to the step-grandparent role. Using data from the Panel Study of Income Dynamics and the Health and Retirement Study, we use percentages to provide first estimates of step-grandparenthood and to describe demographic and socioeconomic variation in who is a step-grandparent. We use life tables to estimate the exposure to step-grandparenthood. The share of step-grandparents is increasing across birth cohorts. However, individuals without a college education and non-Whites are more likely to become step-grandparents. Exposure to the step-grandparent role accounts for approximately 15% of total grandparent years at age 65 for women and men. A growing body of research finds that grandparents are increasingly instrumental in the lives of younger generations. However, the majority of this work assumes that these ties are biological, with little attention paid to the role of family complexity across three generations. Understanding the demographics of step-grandparenthood sheds light on the family experiences of an overlooked, but growing segment of the older adult population in the United States. © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  3. Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Qi Jia

    2015-03-01

    Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

  4. Glutathione--hydroxyl radical interaction: a theoretical study on radical recognition process.

    Directory of Open Access Journals (Sweden)

    Béla Fiser

    Full Text Available Non-reactive, comparative (2 × 1.2 μs molecular dynamics simulations were carried out to characterize the interactions between glutathione (GSH, host molecule and hydroxyl radical (OH(•, guest molecule. From this analysis, two distinct steps were identified in the recognition process of hydroxyl radical by glutathione: catching and steering, based on the interactions between the host-guest molecules. Over 78% of all interactions are related to the catching mechanism via complex formation between anionic carboxyl groups and the OH radical, hence both terminal residues of GSH serve as recognition sites. The glycine residue has an additional role in the recognition of OH radical, namely the steering. The flexibility of the Gly residue enables the formation of further interactions of other parts of glutathione (e.g. thiol, α- and β-carbons with the lone electron pair of the hydroxyl radical. Moreover, quantum chemical calculations were carried out on selected GSH/OH(• complexes and on appropriate GSH conformers to describe the energy profile of the recognition process. The relative enthalpy and the free energy changes of the radical recognition of the strongest complexes varied from -42.4 to -27.8 kJ/mol and from -21.3 to 9.8 kJ/mol, respectively. These complexes, containing two or more intermolecular interactions, would be the starting configurations for the hydrogen atom migration to quench the hydroxyl radical via different reaction channels.

  5. MicroRNAs: Processing, Maturation, Target Recognition and Regulatory Functions

    Science.gov (United States)

    Shukla, Girish C.; Singh, Jagjit; Barik, Sailen

    2012-01-01

    The remarkable discovery of small noncoding microRNAs (miRNAs) and their role in posttranscriptional gene regulation have revealed another fine-tuning step in the expression of genetic information. A large number of cellular pathways, which act in organismal development and are important in health and disease, appear to be modulated by miRNAs. At the molecular level, miRNAs restrain the production of proteins by affecting the stability of their target mRNA and/or by down-regulating their translation. This review attempts to offer a snapshot of aspects of miRNA coding, processing, target recognition and function in animals. Our goal here is to provide the readers with a thought-provoking and mechanistic introduction to the miRNA world rather than with a detailed encyclopedia. PMID:22468167

  6. Business model for sensor-based fall recognition systems.

    Science.gov (United States)

    Fachinger, Uwe; Schöpke, Birte

    2014-01-01

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

  7. Arabic sign language recognition based on HOG descriptor

    Science.gov (United States)

    Ben Jmaa, Ahmed; Mahdi, Walid; Ben Jemaa, Yousra; Ben Hamadou, Abdelmajid

    2017-02-01

    We present in this paper a new approach for Arabic sign language (ArSL) alphabet recognition using hand gesture analysis. This analysis consists in extracting a histogram of oriented gradient (HOG) features from a hand image and then using them to generate an SVM Models. Which will be used to recognize the ArSL alphabet in real-time from hand gesture using a Microsoft Kinect camera. Our approach involves three steps: (i) Hand detection and localization using a Microsoft Kinect camera, (ii) hand segmentation and (iii) feature extraction using Arabic alphabet recognition. One each input image first obtained by using a depth sensor, we apply our method based on hand anatomy to segment hand and eliminate all the errors pixels. This approach is invariant to scale, to rotation and to translation of the hand. Some experimental results show the effectiveness of our new approach. Experiment revealed that the proposed ArSL system is able to recognize the ArSL with an accuracy of 90.12%.

  8. A Horizontal Tilt Correction Method for Ship License Numbers Recognition

    Science.gov (United States)

    Liu, Baolong; Zhang, Sanyuan; Hong, Zhenjie; Ye, Xiuzi

    2018-02-01

    An automatic ship license numbers (SLNs) recognition system plays a significant role in intelligent waterway transportation systems since it can be used to identify ships by recognizing the characters in SLNs. Tilt occurs frequently in many SLNs because the monitors and the ships usually have great vertical or horizontal angles, which decreases the accuracy and robustness of a SLNs recognition system significantly. In this paper, we present a horizontal tilt correction method for SLNs. For an input tilt SLN image, the proposed method accomplishes the correction task through three main steps. First, a MSER-based characters’ center-points computation algorithm is designed to compute the accurate center-points of the characters contained in the input SLN image. Second, a L 1- L 2 distance-based straight line is fitted to the computed center-points using M-estimator algorithm. The tilt angle is estimated at this stage. Finally, based on the computed tilt angle, an affine transformation rotation is conducted to rotate and to correct the input SLN horizontally. At last, the proposed method is tested on 200 tilt SLN images, the proposed method is proved to be effective with a tilt correction rate of 80.5%.

  9. Track-based event recognition in a realistic crowded environment

    Science.gov (United States)

    van Huis, Jasper R.; Bouma, Henri; Baan, Jan; Burghouts, Gertjan J.; Eendebak, Pieter T.; den Hollander, Richard J. M.; Dijk, Judith; van Rest, Jeroen H.

    2014-10-01

    Automatic detection of abnormal behavior in CCTV cameras is important to improve the security in crowded environments, such as shopping malls, airports and railway stations. This behavior can be characterized at different time scales, e.g., by small-scale subtle and obvious actions or by large-scale walking patterns and interactions between people. For example, pickpocketing can be recognized by the actual snatch (small scale), when he follows the victim, or when he interacts with an accomplice before and after the incident (longer time scale). This paper focusses on event recognition by detecting large-scale track-based patterns. Our event recognition method consists of several steps: pedestrian detection, object tracking, track-based feature computation and rule-based event classification. In the experiment, we focused on single track actions (walk, run, loiter, stop, turn) and track interactions (pass, meet, merge, split). The experiment includes a controlled setup, where 10 actors perform these actions. The method is also applied to all tracks that are generated in a crowded shopping mall in a selected time frame. The results show that most of the actions can be detected reliably (on average 90%) at a low false positive rate (1.1%), and that the interactions obtain lower detection rates (70% at 0.3% FP). This method may become one of the components that assists operators to find threatening behavior and enrich the selection of videos that are to be observed.

  10. Simultaneous Versus Sequential Presentation in Testing Recognition Memory for Faces.

    Science.gov (United States)

    Finley, Jason R; Roediger, Henry L; Hughes, Andrea D; Wahlheim, Christopher N; Jacoby, Larry L

    2015-01-01

    Three experiments examined the issue of whether faces could be better recognized in a simul- taneous test format (2-alternative forced choice [2AFC]) or a sequential test format (yes-no). All experiments showed that when target faces were present in the test, the simultaneous procedure led to superior performance (area under the ROC curve), whether lures were high or low in similarity to the targets. However, when a target-absent condition was used in which no lures resembled the targets but the lures were similar to each other, the simultaneous procedure yielded higher false alarm rates (Experiments 2 and 3) and worse overall performance (Experi- ment 3). This pattern persisted even when we excluded responses that participants opted to withhold rather than volunteer. We conclude that for the basic recognition procedures used in these experiments, simultaneous presentation of alternatives (2AFC) generally leads to better discriminability than does sequential presentation (yes-no) when a target is among the alterna- tives. However, our results also show that the opposite can occur when there is no target among the alternatives. An important future step is to see whether these patterns extend to more realistic eyewitness lineup procedures. The pictures used in the experiment are available online at http://www.press.uillinois.edu/journals/ajp/media/testing_recognition/.

  11. Use of designed sequences in protein structure recognition.

    Science.gov (United States)

    Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

    2018-05-09

    Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

  12. Efficient iris recognition by characterizing key local variations.

    Science.gov (United States)

    Ma, Li; Tan, Tieniu; Wang, Yunhong; Zhang, Dexin

    2004-06-01

    Unlike other biometrics such as fingerprints and face, the distinct aspect of iris comes from randomly distributed features. This leads to its high reliability for personal identification, and at the same time, the difficulty in effectively representing such details in an image. This paper describes an efficient algorithm for iris recognition by characterizing key local variations. The basic idea is that local sharp variation points, denoting the appearing or vanishing of an important image structure, are utilized to represent the characteristics of the iris. The whole procedure of feature extraction includes two steps: 1) a set of one-dimensional intensity signals is constructed to effectively characterize the most important information of the original two-dimensional image; 2) using a particular class of wavelets, a position sequence of local sharp variation points in such signals is recorded as features. We also present a fast matching scheme based on exclusive OR operation to compute the similarity between a pair of position sequences. Experimental results on 2255 iris images show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.

  13. Entity recognition in the biomedical domain using a hybrid approach.

    Science.gov (United States)

    Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

    2017-11-09

    This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

  14. The Improvement of Behavior Recognition Accuracy of Micro Inertial Accelerometer by Secondary Recognition Algorithm

    Directory of Open Access Journals (Sweden)

    Yu Liu

    2014-05-01

    Full Text Available Behaviors of “still”, “walking”, “running”, “jumping”, “upstairs” and “downstairs” can be recognized by micro inertial accelerometer of low cost. By using the features as inputs to the well-trained BP artificial neural network which is selected as classifier, those behaviors can be recognized. But the experimental results show that the recognition accuracy is not satisfactory. This paper presents secondary recognition algorithm and combine it with BP artificial neural network to improving the recognition accuracy. The Algorithm is verified by the Android mobile platform, and the recognition accuracy can be improved more than 8 %. Through extensive testing statistic analysis, the recognition accuracy can reach 95 % through BP artificial neural network and the secondary recognition, which is a reasonable good result from practical point of view.

  15. Learned image representations for visual recognition

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo

    This thesis addresses the problem of extracting image structures for representing images effectively in order to solve visual recognition tasks. Problems from diverse research areas (medical imaging, material science and food processing) have motivated large parts of the methodological development...

  16. Image-based automatic recognition of larvae

    Science.gov (United States)

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

    2010-08-01

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

  17. Hybrid Speaker Recognition Using Universal Acoustic Model

    Science.gov (United States)

    Nishimura, Jun; Kuroda, Tadahiro

    We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

  18. Gesture recognition for an exergame prototype

    NARCIS (Netherlands)

    Gacem, Brahim; Vergouw, Robert; Verbiest, Harm; Cicek, Emrullah; Kröse, Ben; van Oosterhout, Tim; Bakkes, S.C.J.

    2011-01-01

    We will demonstrate a prototype exergame aimed at the serious domain of elderly fitness. The exergame incorporates straightforward means to gesture recognition, and utilises a Kinect camera to obtain 2.5D sensory data of the human user.

  19. Kin-informative recognition cues in ants

    DEFF Research Database (Denmark)

    Nehring, Volker; Evison, Sophie E F; Santorelli, Lorenzo A

    2011-01-01

    behaviour is thought to be rare in one of the classic examples of cooperation--social insect colonies--because the colony-level costs of individual selfishness select against cues that would allow workers to recognize their closest relatives. In accord with this, previous studies of wasps and ants have...... found little or no kin information in recognition cues. Here, we test the hypothesis that social insects do not have kin-informative recognition cues by investigating the recognition cues and relatedness of workers from four colonies of the ant Acromyrmex octospinosus. Contrary to the theoretical...... prediction, we show that the cuticular hydrocarbons of ant workers in all four colonies are informative enough to allow full-sisters to be distinguished from half-sisters with a high accuracy. These results contradict the hypothesis of non-heritable recognition cues and suggest that there is more potential...

  20. Automatic recognition of printed Oriya script

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    Some studies have been reported on Tamil, Telugu and. Gurmukhi scripts ..... leaf node, giving rise to recognition errors. The contribution of these ... As a native speaker of Oriya, Anil Chand gave us useful advice about the script. P. Sashank.

  1. Support vector machine for automatic pain recognition

    Science.gov (United States)

    Monwar, Md Maruf; Rezaei, Siamak

    2009-02-01

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

  2. Novel Techniques for Dialectal Arabic Speech Recognition

    CERN Document Server

    Elmahdy, Mohamed; Minker, Wolfgang

    2012-01-01

    Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and M...

  3. Combat Systems Department Employee Recognition System

    National Research Council Canada - National Science Library

    1996-01-01

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

  4. CERN receives prestigious Milestone recognition from IEEE

    CERN Multimedia

    2005-01-01

    At a ceremony at CERN, Mr W. Cleon Anderson, President of the Institute of Electrical and Electronics Engineers (IEEE) formally a Milestone plaque in recognition of the invention of electronic particle detectors at CERN

  5. Picture languages formal models for picture recognition

    CERN Document Server

    Rosenfeld, Azriel

    1979-01-01

    Computer Science and Applied Mathematics: Picture Languages: Formal Models for Picture Recognition treats pictorial pattern recognition from the formal standpoint of automata theory. This book emphasizes the capabilities and relative efficiencies of two types of automata-array automata and cellular array automata, with respect to various array recognition tasks. The array automata are simple processors that perform sequences of operations on arrays, while the cellular array automata are arrays of processors that operate on pictures in a highly parallel fashion, one processor per picture element. This compilation also reviews a collection of results on two-dimensional sequential and parallel array acceptors. Some of the analogous one-dimensional results and array grammars and their relation to acceptors are likewise covered in this text. This publication is suitable for researchers, professionals, and specialists interested in pattern recognition and automata theory.

  6. New technique for number-plate recognition

    Science.gov (United States)

    Guo, Jie; Shi, Peng-Fei

    2001-09-01

    This paper presents an alternative algorithm for number plate recognition. The algorithm consists of three modules. Respectively, they are number plate location module, character segmentation module and character recognition module. Number plate location module extracts the number plate from the detected car image by analyzing the color and the texture properties. Different from most license plate location methods, the algorithm has fewer limits to the car size, the car position in the image and the image background. Character segmentation module applies connected region algorithm both to eliminate noise points and to segment characters. Touching characters and broken characters can be processed correctly. Character recognition module recognizes characters with HHIC (Hierarchical Hybrid Integrated Classifier). The system has been tested with 100 images obtained from crossroad and parking lot, etc, where the cars have different size, position, background and illumination. Successful recognition rate is about 92%. The average processing time is 1.2 second.

  7. Modulation of pathogen recognition by autophagy

    Directory of Open Access Journals (Sweden)

    Ji Eun eOh

    2012-03-01

    Full Text Available Autophagy is an ancient biological process for maintaining cellular homeostasis by degradation of long-lived cytosolic proteins and organelles. Recent studies demonstrated that autophagy is availed by immune cells to regulate innate immunity. On the one hand, cells exert direct effector function by degrading intracellular pathogens; on the other hand, autophagy modulates pathogen recognition and downstream signaling for innate immune responses. Pathogen recognition via pattern recognition receptors induces autophagy. The function of phagocytic cells is enhanced by recruitment of autophagy-related proteins. Moreover, autophagy acts as a delivery system for viral replication complexes to migrate to the endosomal compartments where virus sensing occurs. In another case, key molecules of the autophagic pathway have been found to negatively regulate immune signaling, thus preventing aberrant activation of cytokine production and consequent immune responses. In this review, we focus on the recent advances in the role of autophagy in pathogen recognition and modulation of innate immune responses.

  8. An Application for Descriptive Nearness: Iris Recognition

    Directory of Open Access Journals (Sweden)

    Polat Kadirhan

    2017-12-01

    Full Text Available Near Set Theory has various applications in the literature. In this paper, using the concept descriptive nearness, we show how to perform iris recognition. This process has a few algorithms given via Mathematica Script Language.

  9. Identifying significant environmental features using feature recognition.

    Science.gov (United States)

    2015-10-01

    The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

  10. RGB-D-T based Face Recognition

    DEFF Research Database (Denmark)

    Nikisins, Olegs; Nasrollahi, Kamal; Greitans, Modris

    2014-01-01

    Facial images are of critical importance in many real-world applications from gaming to surveillance. The current literature on facial image analysis, from face detection to face and facial expression recognition, are mainly performed in either RGB, Depth (D), or both of these modalities. But......, such analyzes have rarely included Thermal (T) modality. This paper paves the way for performing such facial analyzes using synchronized RGB-D-T facial images by introducing a database of 51 persons including facial images of different rotations, illuminations, and expressions. Furthermore, a face recognition...... algorithm has been developed to use these images. The experimental results show that face recognition using such three modalities provides better results compared to face recognition in any of such modalities in most of the cases....

  11. Temporal visual cues aid speech recognition

    DEFF Research Database (Denmark)

    Zhou, Xiang; Ross, Lars; Lehn-Schiøler, Tue

    2006-01-01

    of audio to generate an artificial talking-face video and measured word recognition performance on simple monosyllabic words. RESULTS: When presenting words together with the artificial video we find that word recognition is improved over purely auditory presentation. The effect is significant (p......BACKGROUND: It is well known that under noisy conditions, viewing a speaker's articulatory movement aids the recognition of spoken words. Conventionally it is thought that the visual input disambiguates otherwise confusing auditory input. HYPOTHESIS: In contrast we hypothesize...... that it is the temporal synchronicity of the visual input that aids parsing of the auditory stream. More specifically, we expected that purely temporal information, which does not convey information such as place of articulation may facility word recognition. METHODS: To test this prediction we used temporal features...

  12. Automatic modulation recognition of communication signals

    CERN Document Server

    Azzouz, Elsayed Elsayed

    1996-01-01

    Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a cr...

  13. Does cortisol modulate emotion recognition and empathy?

    Science.gov (United States)

    Duesenberg, Moritz; Weber, Juliane; Schulze, Lars; Schaeuffele, Carmen; Roepke, Stefan; Hellmann-Regen, Julian; Otte, Christian; Wingenfeld, Katja

    2016-04-01

    Emotion recognition and empathy are important aspects in the interaction and understanding of other people's behaviors and feelings. The Human environment comprises of stressful situations that impact social interactions on a daily basis. Aim of the study was to examine the effects of the stress hormone cortisol on emotion recognition and empathy. In this placebo-controlled study, 40 healthy men and 40 healthy women (mean age 24.5 years) received either 10mg of hydrocortisone or placebo. We used the Multifaceted Empathy Test to measure emotional and cognitive empathy. Furthermore, we examined emotion recognition from facial expressions, which contained two emotions (anger and sadness) and two emotion intensities (40% and 80%). We did not find a main effect for treatment or sex on either empathy or emotion recognition but a sex × emotion interaction on emotion recognition. The main result was a four-way-interaction on emotion recognition including treatment, sex, emotion and task difficulty. At 40% task difficulty, women recognized angry faces better than men in the placebo condition. Furthermore, in the placebo condition, men recognized sadness better than anger. At 80% task difficulty, men and women performed equally well in recognizing sad faces but men performed worse compared to women with regard to angry faces. Apparently, our results did not support the hypothesis that increases in cortisol concentration alone influence empathy and emotion recognition in healthy young individuals. However, sex and task difficulty appear to be important variables in emotion recognition from facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. 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...

  15. Neural-Network Object-Recognition Program

    Science.gov (United States)

    Spirkovska, L.; Reid, M. B.

    1993-01-01

    HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

  16. Aggregating Local Descriptors for Epigraphs Recognition

    OpenAIRE

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

    2014-01-01

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

  17. Fingerprint Recognition Using Minutia Score Matching

    OpenAIRE

    J, Ravi.; Raja, K. B.; R, Venugopal. K.

    2010-01-01

    The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae ...

  18. Person Recognition in Social Media Photos

    OpenAIRE

    Oh, Seong Joon; Benenson, Rodrigo; Fritz, Mario; Schiele, Bernt

    2017-01-01

    People nowadays share large parts of their personal lives through social media. Being able to automatically recognise people in personal photos may greatly enhance user convenience by easing photo album organisation. For human identification task, however, traditional focus of computer vision has been face recognition and pedestrian re-identification. Person recognition in social media photos sets new challenges for computer vision, including non-cooperative subjects (e.g. backward viewpoints...

  19. Bilingual Language Switching: Production vs. Recognition

    Science.gov (United States)

    Mosca, Michela; de Bot, Kees

    2017-01-01

    This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing. PMID:28638361

  20. 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.

  1. Implicit Recognition Based on Lateralized Perceptual Fluency

    OpenAIRE

    Vargas, Iliana M.; Voss, Joel L.; Paller, Ken A.

    2012-01-01

    In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention enc...

  2. Recognition of dementia in hospitalized older adults.

    Science.gov (United States)

    Maslow, Katie; Mezey, Mathy

    2008-01-01

    Many hospital patients with dementia have no documented dementia diagnosis. In some cases, this is because they have never been diagnosed. Recognition of Dementia in Hospitalized Older Adults proposes several approaches that hospital nurses can use to increase recognition of dementia. This article describes the Try This approaches, how to implement them, and how to incorporate them into a hospital's current admission procedures. For a free online video demonstrating the use of these approaches, go to http://links.lww.com/A216.

  3. On-device mobile speech recognition

    OpenAIRE

    Mustafa, MK

    2016-01-01

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

  4. The micro-step motor controller

    International Nuclear Information System (INIS)

    Hong, Kwang Pyo; Lee, Chang Hee; Moon, Myung Kook; Choi, Bung Hun; Choi, Young Hyun; Cheon, Jong Gu

    2004-11-01

    The developed micro-step motor controller can handle 4 axes stepping motor drivers simultaneously and provide high power bipolar driving mechanism with constant current mode. It can be easily controlled by manual key functions and the motor driving status is displayed by the front panel VFD. Due to the development of several kinds of communication and driving protocol, PC can operate even several micro-step motor controllers at once by multi-drop connection

  5. Multi-step contrast sensitivity gauge

    Science.gov (United States)

    Quintana, Enrico C; Thompson, Kyle R; Moore, David G; Heister, Jack D; Poland, Richard W; Ellegood, John P; Hodges, George K; Prindville, James E

    2014-10-14

    An X-ray contrast sensitivity gauge is described herein. The contrast sensitivity gauge comprises a plurality of steps of varying thicknesses. Each step in the gauge includes a plurality of recesses of differing depths, wherein the depths are a function of the thickness of their respective step. An X-ray image of the gauge is analyzed to determine a contrast-to-noise ratio of a detector employed to generate the image.

  6. Step-wise stimulated martensitic transformations

    International Nuclear Information System (INIS)

    Airoldi, G.; Riva, G.

    1991-01-01

    NiTi alloys, widely known both for their shape memory properties and for unusual pseudoelastic behaviour, are now on the forefront attention for step-wise induced memory processes, thermal or stress stimulated. Literature results related to step-wise stimulated martensite (direct transformation) are examined and contrasted with step-wise thermal stimulated parent phase (reverse transformation). Hypothesis are given to explain the key characters of both transformations, a thermodynamic model from first principles being till now lacking

  7. Microprocessor-based stepping motor driver

    International Nuclear Information System (INIS)

    Halbig, J.K.; Klosterbuer, S.F.

    1979-09-01

    The Pion Generation for Medical Irradiations (PIGMI) program at the Los Alamos Scientific Laboratory requires a versatile stepping motor driver to do beam diagnostic measurements. A driver controlled by a microprocessor that can move eight stepping motors simultaneously was designed. The driver can monitor and respond to clockwise- and counterclockwise-limit switches, and it can monitor a 0- to 10-V dc position signal. The software controls start and stop ramping and maximum stepping rates. 2 figures, 1 table

  8. Steps and dislocations in cubic lyotropic crystals

    International Nuclear Information System (INIS)

    Leroy, S; Pieranski, P

    2006-01-01

    It has been shown recently that lyotropic systems are convenient for studies of faceting, growth or anisotropic surface melting of crystals. All these phenomena imply the active contribution of surface steps and bulk dislocations. We show here that steps can be observed in situ and in real time by means of a new method combining hygroscopy with phase contrast. First results raise interesting issues about the consequences of bicontinuous topology on the structure and dynamical behaviour of steps and dislocations

  9. Implicit Recognition Based on Lateralized Perceptual Fluency

    Directory of Open Access Journals (Sweden)

    Iliana M. Vargas

    2012-02-01

    Full Text Available In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

  10. An Introduction to Face Recognition Technology

    Directory of Open Access Journals (Sweden)

    Shang-Hung Lin

    2000-01-01

    Full Text Available Recently face recognition is attracting much attention in the society of network multimedia information access.  Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because "people" are the center of attention in a lot of video.  Network access control via face recognition not only makes hackers virtually impossible to steal one's "password", but also increases the user-friendliness in human-computer interaction.  Indexing and/or retrieving video data based on the appearances of particular persons will be useful for users such as news reporters, political scientists, and moviegoers.  For the applications of videophone and teleconferencing, the assistance of face recognition also provides a more efficient coding scheme.  In this paper, we give an introductory course of this new information processing technology.  The paper shows the readers the generic framework for the face recognition system, and the variants that are frequently encountered by the face recognizer.  Several famous face recognition algorithms, such as eigenfaces and neural networks, will also be explained.

  11. Emotion recognition in Chinese people with schizophrenia.

    Science.gov (United States)

    Chan, Chetwyn C H; Wong, Raymond; Wang, Kai; Lee, Tatia M C

    2008-01-15

    This study examined whether people with paranoid or nonparanoid schizophrenia would show emotion-recognition deficits, both facial and prosodic. Furthermore, this study examined the neuropsychological predictors of emotion-recognition ability in people with schizophrenia. Participants comprised 86 people, of whom: 43 were people diagnosed with schizophrenia and 43 were controls. The 43 clinical participants were placed in either the paranoid group (n=19) or the nonparanoid group (n=24). Each participant was administered the Facial Emotion Recognition task and the Prosodic Recognition task, together with other neuropsychological measures of attention and visual perception. People suffering from nonparanoid schizophrenia were found to have deficits in both facial and prosodic emotion recognition, after correction for the differences in the intelligence and depression scores between the two groups. Furthermore, spatial perception was observed to be the best predictor of facial emotion identification in individuals with nonparanoid schizophrenia, whereas attentional processing control predicted both prosodic emotion identification and discrimination in nonparanoid schizophrenia patients. Our findings suggest that patients with schizophrenia in remission may still suffer from impairment of certain aspects of emotion recognition.

  12. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  13. Hierarchical Context Modeling for Video Event Recognition.

    Science.gov (United States)

    Wang, Xiaoyang; Ji, Qiang

    2016-10-11

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

  14. The hierarchical brain network for face recognition.

    Science.gov (United States)

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  15. Oxytocin improves emotion recognition for older males.

    Science.gov (United States)

    Campbell, Anna; Ruffman, Ted; Murray, Janice E; Glue, Paul

    2014-10-01

    Older adults (≥60 years) perform worse than young adults (18-30 years) when recognizing facial expressions of emotion. The hypothesized cause of these changes might be declines in neurotransmitters that could affect information processing within the brain. In the present study, we examined the neuropeptide oxytocin that functions to increase neurotransmission. Research suggests that oxytocin benefits the emotion recognition of less socially able individuals. Men tend to have lower levels of oxytocin and older men tend to have worse emotion recognition than older women; therefore, there is reason to think that older men will be particularly likely to benefit from oxytocin. We examined this idea using a double-blind design, testing 68 older and 68 young adults randomly allocated to receive oxytocin nasal spray (20 international units) or placebo. Forty-five minutes afterward they completed an emotion recognition task assessing labeling accuracy for angry, disgusted, fearful, happy, neutral, and sad faces. Older males receiving oxytocin showed improved emotion recognition relative to those taking placebo. No differences were found for older females or young adults. We hypothesize that oxytocin facilitates emotion recognition by improving neurotransmission in the group with the worst emotion recognition. Copyright © 2014 Elsevier Inc. All rights reserved.

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

    International Nuclear Information System (INIS)

    Dupeyrat, Benoit

    1981-01-01

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

  17. Smart Steps to Sustainability 2.0

    Science.gov (United States)

    Smart Steps to Sustainability provides small business owners and managers with practical advice and tools to implementsustainable and environmentally-preferable business practices that go beyond compliance.

  18. Rotation-invariant neural pattern recognition system with application to coin recognition.

    Science.gov (United States)

    Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

    1992-01-01

    In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

  19. Role of step stiffness and kinks in the relaxation of vicinal (001) with zigzag [110] steps

    Science.gov (United States)

    Mahjoub, B.; Hamouda, Ajmi BH.; Einstein, TL.

    2017-08-01

    We present a kinetic Monte Carlo study of the relaxation dynamics and steady state configurations of 〈110〉 steps on a vicinal (001) simple cubic surface. This system is interesting because 〈110〉 (fully kinked) steps have different elementary excitation energetics and favor step diffusion more than 〈100〉 (nominally straight) steps. In this study we show how this leads to different relaxation dynamics as well as to different steady state configurations, including that 2-bond breaking processes are rate determining for 〈110〉 steps in contrast to 3-bond breaking processes for 〈100〉-steps found in previous work [Surface Sci. 602, 3569 (2008)]. The analysis of the terrace-width distribution (TWD) shows a significant role of kink-generation-annihilation processes during the relaxation of steps: the kinetic of relaxation, toward the steady state, is much faster in the case of 〈110〉-zigzag steps, with a higher standard deviation of the TWD, in agreement with a decrease of step stiffness due to orientation. We conclude that smaller step stiffness leads inexorably to faster step dynamics towards the steady state. The step-edge anisotropy slows the relaxation of steps and increases the strength of step-step effective interactions.

  20. Sintering uranium oxide using a preheating step

    International Nuclear Information System (INIS)

    Jensen, N.J.; Nivas, Y.; Packard, D.R.

    1977-01-01

    Compacted pellets of uranium oxide or uranium oxide with one or more additives are heated in a kiln in a process having a preheating step, a sintering step, a reduction step, and a cooling step in a controlled atmosphere. The process is practiced to give a range of temperature and atmosphere conditions for obtaining optimum fluoride removal from the compacted pellets along with optimum sintering in a single process. The preheating step of this process is conducted in a temperature range of about 600 0 to about 900 0 C and the pellets are held for at least twenty min, and preferably about 60 min, in an atmosphere having a composition in the range of about 10 to about 75 vol % hydrogen with the balance being carbon dioxide. The sintering step is conducted at a temperature in the range of about 900 0 C to 1500 0 C in the presence of an atmosphere having a composition in the range of about 0.5 to about 90 vol % hydrogen with the balance being carbon dioxide. The reduction step reduces the oxygen to metal ratio of the pellets to a range of about 1.98 to 2.10:1 and this is accomplished by gradually cooling the pellets for about 30 to about 120 min from the temperature of the sintering step to about 1100 0 C in an atmosphere of about 10 to 90 vol % hydrogen with the balance being carbon dioxide. Thereafter the pellets are cooled to about 100 0 C under a protective atmosphere, and in one preferred practice the same atmosphere used in the reduction step is used in the cooling step. The preheating, sintering and reduction steps may also be conducted with their respective atmospheres having an initial additional component of water vapor and the water vapor can comprise up to about 20 vol %

  1. Microcomputer-based stepping-motor controller

    International Nuclear Information System (INIS)

    Johnson, K.

    1983-04-01

    A microcomputer-controlled stepping motor is described. A Motorola MC68701 microcomputer unit is interfaced to a Cybernetic CY500 stored-program controller that outputs through Motorola input/output isolation modules to the stepping motor. A complex multifunction controller with enhanced capabilities is thus available with a minimum number of parts

  2. Step-Up DC-DC converters

    DEFF Research Database (Denmark)

    Forouzesh, Mojtaba; Siwakoti, Yam P.; Gorji, Saman A.

    2017-01-01

    on the general law and framework of the development of next-generation step-up dc-dc converters, this paper aims to comprehensively review and classify various step-up dc-dc converters based on their characteristics and voltage-boosting techniques. In addition, the advantages and disadvantages of these voltage...

  3. Step-wise refolding of recombinant proteins.

    Science.gov (United States)

    Tsumoto, Kouhei; Arakawa, Tsutomu; Chen, Linda

    2010-04-01

    Protein refolding is still on trial-and-error basis. Here we describe step-wise dialysis refolding, in which denaturant concentration is altered in step-wise fashion. This technology controls the folding pathway by adjusting the concentrations of the denaturant and other solvent additives to induce sequential folding or disulfide formation.

  4. Phonon scattering in graphene over substrate steps

    DEFF Research Database (Denmark)

    Sevincli, Haldun; Brandbyge, Mads

    2014-01-01

    We calculate the effect on phonon transport of substrate-induced bends in graphene. We consider bending induced by an abrupt kink in the substrate, and provide results for different step-heights and substrate interaction strengths. We find that individual substrate steps reduce thermal conductance...

  5. Random Walks with Anti-Correlated Steps

    OpenAIRE

    Wagner, Dirk; Noga, John

    2005-01-01

    We conjecture the expected value of random walks with anti-correlated steps to be exactly 1. We support this conjecture with 2 plausibility arguments and experimental data. The experimental analysis includes the computation of the expected values of random walks for steps up to 22. The result shows the expected value asymptotically converging to 1.

  6. Steps in Performing a Communication Audit.

    Science.gov (United States)

    Sincoff, Michael Z.; And Others

    This paper develops the step-by-step processes necessary to conduct a communication audit in order to determine the communication effectiveness of an organization. The authors stress the responsibilities of both the audit team and the organization's top management as they interact during progressive phases of the audit. Emphasis is placed on…

  7. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

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

    2009-01-01

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

  8. Step patterns on vicinal reconstructed surfaces

    Science.gov (United States)

    Vilfan, Igor

    1996-04-01

    Step patterns on vicinal (2 × 1) reconstructed surfaces of noble metals Au(110) and Pt(110), miscut towards the (100) orientation, are investigated. The free energy of the reconstructed surface with a network of crossing opposite steps is calculated in the strong chirality regime when the steps cannot make overhangs. It is explained why the steps are not perpendicular to the direction of the miscut but form in equilibrium a network of crossing steps which make the surface to look like a fish skin. The network formation is the consequence of competition between the — predominantly elastic — energy loss and entropy gain. It is in agreement with recent scanning tunnelling microscopy observations on vicinal Au(110) and Pt(110) surfaces.

  9. The recognition heuristic : A review of theory and tests

    OpenAIRE

    Pachur, T.; Todd, P.; Gigerenzer, G.; Schooler, L.; Goldstein, D.

    2011-01-01

    The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) th...

  10. Accurate forced-choice recognition without awareness of memory retrieval

    OpenAIRE

    Voss, Joel L.; Baym, Carol L.; Paller, Ken A.

    2008-01-01

    Recognition confidence and the explicit awareness of memory retrieval commonly accompany accurate responding in recognition tests. Memory performance in recognition tests is widely assumed to measure explicit memory, but the generality of this assumption is questionable. Indeed, whether recognition in nonhumans is always supported by explicit memory is highly controversial. Here we identified circumstances wherein highly accurate recognition was unaccompanied by hallmark features of explicit ...

  11. Recognition of Prior Learning, Self-Realisation and Identity within Axel Honneth's Theory of Recognition

    Science.gov (United States)

    Sandberg, Fredrik; Kubiak, Chris

    2013-01-01

    This paper argues for the significance of Axel Honneth's theory of recognition for understanding recognition of prior learning (RPL). Case studies of the experiences of RPL by paraprofessional workers in health and social care in the UK and Sweden are used to explicate this significance. The results maintain that there are varying conditions of…

  12. A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

    Science.gov (United States)

    Sassenrath, Claudia; Sassenberg, Kai; Ray, Devin G; Scheiter, Katharina; Jarodzka, Halszka

    2014-01-01

    Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits). A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition.

  13. L2 Word Recognition: Influence of L1 Orthography on Multi-Syllabic Word Recognition

    Science.gov (United States)

    Hamada, Megumi

    2017-01-01

    L2 reading research suggests that L1 orthographic experience influences L2 word recognition. Nevertheless, the findings on multi-syllabic words in English are still limited despite the fact that a vast majority of words are multi-syllabic. The study investigated whether L1 orthography influences the recognition of multi-syllabic words, focusing on…

  14. What Types of Visual Recognition Tasks Are Mediated by the Neural Subsystem that Subserves Face Recognition?

    Science.gov (United States)

    Brooks, Brian E.; Cooper, Eric E.

    2006-01-01

    Three divided visual field experiments tested current hypotheses about the types of visual shape representation tasks that recruit the cognitive and neural mechanisms underlying face recognition. Experiment 1 found a right hemisphere advantage for subordinate but not basic-level face recognition. Experiment 2 found a right hemisphere advantage for…

  15. A Spatially Constrained Multi-autoencoder Approach for Multivariate Geochemical Anomaly Recognition

    Science.gov (United States)

    Lirong, C.; Qingfeng, G.; Renguang, Z.; Yihui, X.

    2017-12-01

    Separating and recognizing geochemical anomalies from the geochemical background is one of the key tasks in geochemical exploration. Many methods have been developed, such as calculating the mean ±2 standard deviation, and fractal/multifractal models. In recent years, deep autoencoder, a deep learning approach, have been used for multivariate geochemical anomaly recognition. While being able to deal with the non-normal distributions of geochemical concentrations and the non-linear relationships among them, this self-supervised learning method does not take into account the spatial heterogeneity of geochemical background and the uncertainty induced by the randomly initialized weights of neurons, leading to ineffective recognition of weak anomalies. In this paper, we introduce a spatially constrained multi-autoencoder (SCMA) approach for multivariate geochemical anomaly recognition, which includes two steps: spatial partitioning and anomaly score computation. The first step divides the study area into multiple sub-regions to segregate the geochemical background, by grouping the geochemical samples through K-means clustering, spatial filtering, and spatial constraining rules. In the second step, for each sub-region, a group of autoencoder neural networks are constructed with an identical structure but different initial weights on neurons. Each autoencoder is trained using the geochemical samples within the corresponding sub-region to learn the sub-regional geochemical background. The best autoencoder of a group is chosen as the final model for the corresponding sub-region. The anomaly score at each location can then be calculated as the euclidean distance between the observed concentrations and reconstructed concentrations of geochemical elements.The experiments using the geochemical data and Fe deposits in the southwestern Fujian province of China showed that our SCMA approach greatly improved the recognition of weak anomalies, achieving the AUC of 0.89, compared

  16. Learning a Mid-Level Representation for Multiview Action Recognition

    Directory of Open Access Journals (Sweden)

    Cuiwei Liu

    2018-01-01

    Full Text Available Recognizing human actions in videos is an active topic with broad commercial potentials. Most of the existing action recognition methods are supposed to have the same camera view during both training and testing. And thus performances of these single-view approaches may be severely influenced by the camera movement and variation of viewpoints. In this paper, we address the above problem by utilizing videos simultaneously recorded from multiple views. To this end, we propose a learning framework based on multitask random forest to exploit a discriminative mid-level representation for videos from multiple cameras. In the first step, subvolumes of continuous human-centered figures are extracted from original videos. In the next step, spatiotemporal cuboids sampled from these subvolumes are characterized by multiple low-level descriptors. Then a set of multitask random forests are built upon multiview cuboids sampled at adjacent positions and construct an integrated mid-level representation for multiview subvolumes of one action. Finally, a random forest classifier is employed to predict the action category in terms of the learned representation. Experiments conducted on the multiview IXMAS action dataset illustrate that the proposed method can effectively recognize human actions depicted in multiview videos.

  17. Social appraisal influences recognition of emotions.

    Science.gov (United States)

    Mumenthaler, Christian; Sander, David

    2012-06-01

    The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. 2012 APA, all rights reserved

  18. Can corrective feedback improve recognition memory?

    Science.gov (United States)

    Kantner, Justin; Lindsay, D Stephen

    2010-06-01

    An understanding of the effects of corrective feedback on recognition memory can inform both recognition theory and memory training programs, but few published studies have investigated the issue. Although the evidence to date suggests that feedback does not improve recognition accuracy, few studies have directly examined its effect on sensitivity, and fewer have created conditions that facilitate a feedback advantage by encouraging controlled processing at test. In Experiment 1, null effects of feedback were observed following both deep and shallow encoding of categorized study lists. In Experiment 2, feedback robustly influenced response bias by allowing participants to discern highly uneven base rates of old and new items, but sensitivity remained unaffected. In Experiment 3, a false-memory procedure, feedback failed to attenuate false recognition of critical lures. In Experiment 4, participants were unable to use feedback to learn a simple category rule separating old items from new items, despite the fact that feedback was of substantial benefit in a nearly identical categorization task. The recognition system, despite a documented ability to utilize controlled strategic or inferential decision-making processes, appears largely impenetrable to a benefit of corrective feedback.

  19. AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    K. Meena

    2013-11-01

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

  20. Recall and recognition hypermnesia for Socratic stimuli.

    Science.gov (United States)

    Kazén, Miguel; Solís-Macías, Víctor M

    2016-01-01

    In two experiments, we investigate hypermnesia, net memory improvements with repeated testing of the same material after a single study trial. In the first experiment, we found hypermnesia across three trials for the recall of word solutions to Socratic stimuli (dictionary-like definitions of concepts) replicating Erdelyi, Buschke, and Finkelstein and, for the first time using these materials, for their recognition. In the second experiment, we had two "yes/no" recognition groups, a Socratic stimuli group presented with concrete and abstract verbal materials and a word-only control group. Using signal detection measures, we found hypermnesia for concrete Socratic stimuli-and stable performance for abstract stimuli across three recognition tests. The control group showed memory decrements across tests. We interpret these findings with the alternative retrieval pathways (ARP) hypothesis, contrasting it with alternative theories of hypermnesia, such as depth of processing, generation and retrieve-recognise. We conclude that recognition hypermnesia for concrete Socratic stimuli is a reliable phenomenon, which we found in two experiments involving both forced-choice and yes/no recognition procedures.

  1. Visual word recognition across the adult lifespan.

    Science.gov (United States)

    Cohen-Shikora, Emily R; Balota, David A

    2016-08-01

    The current study examines visual word recognition in a large sample (N = 148) across the adult life span and across a large set of stimuli (N = 1,187) in three different lexical processing tasks (pronunciation, lexical decision, and animacy judgment). Although the focus of the present study is on the influence of word frequency, a diverse set of other variables are examined as the word recognition system ages and acquires more experience with language. Computational models and conceptual theories of visual word recognition and aging make differing predictions for age-related changes in the system. However, these have been difficult to assess because prior studies have produced inconsistent results, possibly because of sample differences, analytic procedures, and/or task-specific processes. The current study confronts these potential differences by using 3 different tasks, treating age and word variables as continuous, and exploring the influence of individual differences such as vocabulary, vision, and working memory. The primary finding is remarkable stability in the influence of a diverse set of variables on visual word recognition across the adult age spectrum. This pattern is discussed in reference to previous inconsistent findings in the literature and implications for current models of visual word recognition. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  2. 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.

  3. Contemporary deep recurrent learning for recognition

    Science.gov (United States)

    Iftekharuddin, K. M.; Alam, M.; Vidyaratne, L.

    2017-05-01

    Large-scale feed-forward neural networks have seen intense application in many computer vision problems. However, these networks can get hefty and computationally intensive with increasing complexity of the task. Our work, for the first time in literature, introduces a Cellular Simultaneous Recurrent Network (CSRN) based hierarchical neural network for object detection. CSRN has shown to be more effective to solving complex tasks such as maze traversal and image processing when compared to generic feed forward networks. While deep neural networks (DNN) have exhibited excellent performance in object detection and recognition, such hierarchical structure has largely been absent in neural networks with recurrency. Further, our work introduces deep hierarchy in SRN for object recognition. The simultaneous recurrency results in an unfolding effect of the SRN through time, potentially enabling the design of an arbitrarily deep network. This paper shows experiments using face, facial expression and character recognition tasks using novel deep recurrent model and compares recognition performance with that of generic deep feed forward model. Finally, we demonstrate the flexibility of incorporating our proposed deep SRN based recognition framework in a humanoid robotic platform called NAO.

  4. Exposure effects on music preference and recognition.

    Science.gov (United States)

    Peretz, I; Gaudreau, D; Bonnel, A M

    1998-09-01

    In three experiments, the effects of exposure to melodies on their subsequent liking and recognition were explored. In each experiment, the subjects first listened to a set of familiar and unfamiliar melodies in a study phase. In the subsequent test phase, the melodies were repeated, along with a set of distractors matched in familiarity. Half the subjects were required to rate their liking of each melody, and half had to identify the melodies they had heard earlier in the study phase. Repetition of the studied melodies was found to increase liking of the unfamiliar melodies in the affect task and to be best for detection of familiar melodies in the recognition task (Experiments 1, 2, and 3). These memory effects were found to fade at different time delays between study and test in the affect and recognition tasks, with the latter leading to the most persistent effects (Experiment 2). Both study-to-test changes in melody timbre and manipulation of study tasks had a marked impact on recognition and little influence on liking judgments (Experiment 3). Thus, all manipulated variables were found to dissociate the memory effects in the two tasks. The results are consistent with the view that memory effects in the affect and recognition tasks pertain to the implicit and explicit forms of memory, respectively. Part of the results are, however, at variance with the literature on implicit and explicit memory in the auditory domain. Attribution of these differences to the use of musical material is discussed.

  5. Food brand recognition and BMI in preschoolers.

    Science.gov (United States)

    Harrison, Kristen; Moorman, Jessica; Peralta, Mericarmen; Fayhee, Kally

    2017-07-01

    Children's food brand recognition predicts health-related outcomes such as preference for obesogenic foods and increased risk for overweight. However, it is uncertain to what degree food brand recognition acts as a proxy for other factors such as parental education and income, child vocabulary, child age, child race/ethnicity, parent healthy eating guidance, child commercial TV viewing, and child dietary intake, all of which may influence or be influenced by food brand recognition. U.S. preschoolers (N = 247, average age 56 months) were measured for BMI and completed the Peabody Picture Vocabulary Test plus recognition and recall measures for a selection of U.S. food brands. Parents completed measures of healthy eating guidance, child dietary intake, child commercial TV viewing, parent education, household income, parent BMI, and child age and race/ethnicity. Controlling these variables, child food brand recognition predicted higher child BMI percentile. Further, qualitative examination of children's incorrect answers to recall items demonstrated perceptual confusion between brand mascots and other fantasy characters to which children are exposed during the preschool years, extending theory on child consumer development. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. EMPIRICAL STUDY OF CAR LICENSE PLATES RECOGNITION

    Directory of Open Access Journals (Sweden)

    Nasa Zata Dina

    2015-01-01

    Full Text Available The number of vehicles on the road has increased drastically in recent years. The license plate is an identity card for a vehicle. It can map to the owner and further information about vehicle. License plate information is useful to help traffic management systems. For example, traffic management systems can check for vehicles moving at speeds not permitted by law and can also be installed in parking areas to se-cure the entrance or exit way for vehicles. License plate recognition algorithms have been proposed by many researchers. License plate recognition requires license plate detection, segmentation, and charac-ters recognition. The algorithm detects the position of a license plate and extracts the characters. Various license plate recognition algorithms have been implemented, and each algorithm has its strengths and weaknesses. In this research, I implement three algorithms for detecting license plates, three algorithms for segmenting license plates, and two algorithms for recognizing license plate characters. I evaluate each of these algorithms on the same two datasets, one from Greece and one from Thailand. For detecting li-cense plates, the best result is obtained by a Haar cascade algorithm. After the best result of license plate detection is obtained, for the segmentation part a Laplacian based method has the highest accuracy. Last, the license plate recognition experiment shows that a neural network has better accuracy than other algo-rithm. I summarize and analyze the overall performance of each method for comparison.

  7. Quality based approach for adaptive face recognition

    Science.gov (United States)

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

    2009-05-01

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

  8. How fast is famous face recognition?

    Directory of Open Access Journals (Sweden)

    Gladys eBarragan-Jason

    2012-10-01

    Full Text Available The rapid recognition of familiar faces is crucial for social interactions. However the actual speed with which recognition can be achieved remains largely unknown as most studies have been carried out without any speed constraints. Different paradigms have been used, leading to conflicting results, and although many authors suggest that face recognition is fast, the speed of face recognition has not been directly compared to fast visual tasks. In this study, we sought to overcome these limitations. Subjects performed three tasks, a familiarity categorization task (famous faces among unknown faces, a superordinate categorization task (human faces among animal ones and a gender categorization task. All tasks were performed under speed constraints. The results show that, despite the use of speed constraints, subjects were slow when they had to categorize famous faces: minimum reaction time was 467 ms, which is 180 ms more than during superordinate categorization and 160 ms more than in the gender condition. Our results are compatible with a hierarchy of face processing from the superordinate level to the familiarity level. The processes taking place between detection and recognition need to be investigated in detail.

  9. The optimal viewing position in face recognition.

    Science.gov (United States)

    Hsiao, Janet H; Liu, Tina T

    2012-02-28

    In English word recognition, the best recognition performance is usually obtained when the initial fixation is directed to the left of the center (optimal viewing position, OVP). This effect has been argued to involve an interplay of left hemisphere lateralization for language processing and the perceptual experience of fixating at word beginnings most often. While both factors predict a left-biased OVP in visual word recognition, in face recognition they predict contrasting biases: People prefer to fixate the left half-face, suggesting that the OVP should be to the left of the center; nevertheless, the right hemisphere lateralization in face processing suggests that the OVP should be to the right of the center in order to project most of the face to the right hemisphere. Here, we show that the OVP in face recognition was to the left of the center, suggesting greater influence from the perceptual experience than hemispheric asymmetry in central vision. In contrast, hemispheric lateralization effects emerged when faces were presented away from the center; there was an interaction between presented visual field and location (center vs. periphery), suggesting differential influence from perceptual experience and hemispheric asymmetry in central and peripheral vision.

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

    Science.gov (United States)

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

    2016-09-01

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

  11. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

    Science.gov (United States)

    Bourobou, Serge Thomas Mickala; Yoo, Younghwan

    2015-05-21

    This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

  12. User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

    Directory of Open Access Journals (Sweden)

    Serge Thomas Mickala Bourobou

    2015-05-01

    Full Text Available This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

  13. Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

    Science.gov (United States)

    Raicar, Gaurav; Saini, Harsh; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

    2016-08-07

    Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

    Science.gov (United States)

    Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

    2017-12-01

    The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Microfluidic step-emulsification in axisymmetric geometry.

    Science.gov (United States)

    Chakraborty, I; Ricouvier, J; Yazhgur, P; Tabeling, P; Leshansky, A M

    2017-10-25

    Biphasic step-emulsification (Z. Li et al., Lab Chip, 2015, 15, 1023) is a promising microfluidic technique for high-throughput production of μm and sub-μm highly monodisperse droplets. The step-emulsifier consists of a shallow (Hele-Shaw) microchannel operating with two co-flowing immiscible liquids and an abrupt expansion (i.e., step) to a deep and wide reservoir. Under certain conditions the confined stream of the disperse phase, engulfed by the co-flowing continuous phase, breaks into small highly monodisperse droplets at the step. Theoretical investigation of the corresponding hydrodynamics is complicated due to the complex geometry of the planar device, calling for numerical approaches. However, direct numerical simulations of the three dimensional surface-tension-dominated biphasic flows in confined geometries are computationally expensive. In the present paper we study a model problem of axisymmetric step-emulsification. This setup consists of a stable core-annular biphasic flow in a cylindrical capillary tube connected co-axially to a reservoir tube of a larger diameter through a sudden expansion mimicking the edge of the planar step-emulsifier. We demonstrate that the axisymmetric setup exhibits similar regimes of droplet generation to the planar device. A detailed parametric study of the underlying hydrodynamics is feasible via inexpensive (two dimensional) simulations owing to the axial symmetry. The phase diagram quantifying the different regimes of droplet generation in terms of governing dimensionless parameters is presented. We show that in qualitative agreement with experiments in planar devices, the size of the droplets generated in the step-emulsification regime is independent of the capillary number and almost insensitive to the viscosity ratio. These findings confirm that the step-emulsification regime is solely controlled by surface tension. The numerical predictions are in excellent agreement with in-house experiments with the axisymmetric

  16. Lateral step initiation behavior in older adults.

    Science.gov (United States)

    Sparto, Patrick J; Jennings, J Richard; Furman, Joseph M; Redfern, Mark S

    2014-02-01

    Older adults have varied postural responses during induced and voluntary lateral stepping. The purpose of the research was to quantify the occurrence of different stepping strategies during lateral step initiation in older adults and to relate the stepping responses to retrospective history of falls. Seventy community-ambulating older adults (mean age 76 y, range 70-94 y) performed voluntary lateral steps as quickly as possible to the right or left in response to a visual cue, in a blocked design. Vertical ground reaction forces were measured using a forceplate, and the number and latency of postural adjustments were quantified. Subjects were assigned to groups based on their stepping strategy. The frequency of trials with one or two postural adjustments was compared with data from 20 younger adults (mean age 38 y, range 21-58 y). Logistic regression was used to relate presence of a fall in the previous year with the number and latency of postural adjustments. In comparison with younger adults, who almost always demonstrated one postural adjustment when stepping laterally, older adults constituted a continuous distribution in the percentage of step trials made with one postural adjustment (from 0% to 100% of trials). Latencies of the initial postural adjustment and foot liftoff varied depending on the number of postural adjustments made. A history of falls was associated a larger percentage of two postural adjustments, and a longer latency of foot liftoff. In conclusion, the number and latency of postural adjustments made during voluntary lateral stepping provides additional evidence that lateral control of posture may be a critical indicator of aging. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. The Value of Step-by-Step Risk Assessment for Unmanned Aircraft

    DEFF Research Database (Denmark)

    La Cour-Harbo, Anders

    2018-01-01

    The new European legislation expected in 2018 or 2019 will introduce a step-by-step process for conducting risk assessments for unmanned aircraft flight operations. This is a relatively simple approach to a very complex challenge. This work compares this step-by-step process to high fidelity risk...... modeling, and shows that at least for a series of example flight missions there is reasonable agreement between the two very different methods....

  18. Pendekatan Pelatihan On-Site dan Step by Step untuk Optimalisasi Fungsi Guru dalam Pembelajaran

    OpenAIRE

    Moch. Sholeh Y.A. Ichrom

    2016-01-01

    Remoteness of programme content from teachers' real work situation and unsuitability of approach employed were suspected as main reasons contributing to the failure of many inservise teacher training programmes. A step by step, onsite teacher training (SSOTT) model was tried out in this experiment to study if the weakness of inservise programmes could be rectified. As it was tried out in relation with kindergarten mathemathics it was then called SSOTT-MTW (Step by Step Onsite Teacher Training...

  19. Pendekatan Pelatihan On-Site Dan Step by Step Untuk Optimalisasi Fungsi Guru Dalam Pembelajaran

    OpenAIRE

    Ichrom, Moch. Sholeh Y.A

    1996-01-01

    Remoteness of programme content from teachers' real work situation and unsuitability of approach employed were suspected as main reasons contributing to the failure of many inservise teacher training programmes. A step by step, onsite teacher training (SSOTT) model was tried out in this experiment to study if the weakness of inservise programmes could be rectified. As it was tried out in relation with kindergarten mathemathics it was then called SSOTT-MTW (Step by Step Onsite Teacher Training...

  20. Phonon scattering in graphene over substrate steps

    International Nuclear Information System (INIS)

    Sevinçli, H.; Brandbyge, M.

    2014-01-01

    We calculate the effect on phonon transport of substrate-induced bends in graphene. We consider bending induced by an abrupt kink in the substrate, and provide results for different step-heights and substrate interaction strengths. We find that individual substrate steps reduce thermal conductance in the range between 5% and 47%. We also consider the transmission across linear kinks formed by adsorption of atomic hydrogen at the bends and find that individual kinks suppress thermal conduction substantially, especially at high temperatures. Our analysis show that substrate irregularities can be detrimental for thermal conduction even for small step heights.