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Sample records for s1for acetyl-group recognition

  1. Studies of conformation and interaction of the cyclohexenone and acetyl group of progesterone with liposomes.

    PubMed

    Sanchez-Bueno, A; Watanabe, S; Sancho, M J; Saito, T

    1991-02-01

    The conformations of the A-ring and the 17-acetyl groups of progesterone were examined within liposomes, which were prepared from L-alpha-phosphatidylcholine in the presence or absence of cholesterol in the buffer, using qualitative nuclear magnetic resonance and circular dichroism of the progesterone spectra in the wavelength regions of 260-360 nm. The preferred conformational assignments, in the rotational conformations of the 17-acetyl group and invertible conformations of the cyclohexenone of progesterone were discussed on the basis of the elliptical strength of the Cotton effect and an energy estimation of the preferred conformers. Energetically unstable conformers of the acetyl group and alpha,beta-unsaturated cyclohexenone of progesterone remarkably increased with an increase in the concentration of the liposomes. The liposomes containing 10% cholesterol were similar to the effect of the liposomes lacking cholesterol on the 17-acetyl group and the alpha,beta-unsaturated cyclohexenone but those containing 50% cholesterol showed an increase in the number of energetically stable conformers of the alpha,beta-unsaturated cyclohexenone. The nuclear magnetic resonance signal from liposomes together with the progesterone indicated the existence of the progesterone adjacent to a double bond or ester moiety in the lipid molecule. Therefore, it was apparent that the liposomes and the cholesterol within the liposomes regulated the conformational populations of both the cyclohexone and acetyl groups of the progesterone molecule. PMID:2004040

  2. Effect of Acetyl Group on Mechanical Properties of Chitin/Chitosan Nanocrystal: A Molecular Dynamics Study

    PubMed Central

    Cui, Junhe; Yu, Zechuan; Lau, Denvid

    2016-01-01

    Chitin fiber is the load-bearing component in natural chitin-based materials. In these materials, chitin is always partially deacetylated to different levels, leading to diverse material properties. In order to understand how the acetyl group enhances the fracture resistance capability of chitin fiber, we constructed atomistic models of chitin with varied acetylation degree and analyzed the hydrogen bonding pattern, fracture, and stress-strain behavior of these models. We notice that the acetyl group can contribute to the formation of hydrogen bonds that can stabilize the crystalline structure. In addition, it is found that the specimen with a higher acetylation degree presents a greater resistance against fracture. This study describes the role of the functional group, acetyl groups, in crystalline chitin. Such information could provide preliminary understanding of nanomaterials when similar functional groups are encountered. PMID:26742033

  3. Effect of Acetyl Group on Mechanical Properties of Chitin/Chitosan Nanocrystal: A Molecular Dynamics Study.

    PubMed

    Cui, Junhe; Yu, Zechuan; Lau, Denvid

    2016-01-05

    Chitin fiber is the load-bearing component in natural chitin-based materials. In these materials, chitin is always partially deacetylated to different levels, leading to diverse material properties. In order to understand how the acetyl group enhances the fracture resistance capability of chitin fiber, we constructed atomistic models of chitin with varied acetylation degree and analyzed the hydrogen bonding pattern, fracture, and stress-strain behavior of these models. We notice that the acetyl group can contribute to the formation of hydrogen bonds that can stabilize the crystalline structure. In addition, it is found that the specimen with a higher acetylation degree presents a greater resistance against fracture. This study describes the role of the functional group, acetyl groups, in crystalline chitin. Such information could provide preliminary understanding of nanomaterials when similar functional groups are encountered.

  4. Catalytic Depolymerization of Chitin with Retention of N-Acetyl Group.

    PubMed

    Yabushita, Mizuho; Kobayashi, Hirokazu; Kuroki, Kyoichi; Ito, Shogo; Fukuoka, Atsushi

    2015-11-01

    Chitin, a polymer of N-acetylglucosamine units with β-1,4-glycosidic linkages, is the most abundant marine biomass. Chitin monomers containing N-acetyl groups are useful precursors to various fine chemicals and medicines. However, the selective conversion of robust chitin to N-acetylated monomers currently requires a large excess of acid or a long reaction time, which limits its application. We demonstrate a fast catalytic transformation of chitin to monomers with retention of N-acetyl groups by combining mechanochemistry and homogeneous catalysis. Mechanical-force-assisted depolymerization of chitin with a catalytic amount of H2SO4 gave soluble short-chain oligomers. Subsequent hydrolysis of the ball-milled sample provided N-acetylglucosamine in 53% yield, and methanolysis afforded 1-O-methyl-N-acetylglucosamine in yields of up to 70%. Our process can greatly reduce the use of acid compared to the conventional process. PMID:26538108

  5. Evidence for a blockwise distribution of acetyl groups onto homogalacturonans from a commercial sugar beet (Beta vulgaris) pectin.

    PubMed

    Ralet, Marie-Christine; Crépeau, Marie-Jeanne; Bonnin, Estelle

    2008-06-01

    Commercial acid-extracted sugar beet pectin was extensively hydrolysed using an endo-polygalacturonase (AnPGI from Aspergillus niger or AnPGII from A. niger or FmPG from Fusarium moniliforme) in combination with Aspergillus aculeatus pectin methyl-esterase (AaPME). The homogalacturonan-derived oligogalacturonates released were quantified by high-performance anion-exchange chromatography and their structure determined by mass spectrometry. The different endo-polygalacturonases exhibited variable tolerance towards acetyl groups. AnPGI was the most active and FmPG the less. A hypothetical homogalacturonan was constructed using the AnPGI-recovered oligogalacturonates as building blocks and the validity of the model was checked taking into account FmPG observed requirements and hydrolysis products. A blockwise repartition of the acetyl groups onto sugar beet pectin homogalacturonan is proposed.

  6. [Structure and characteristics of glucomannans from Eremurus iae and E.zangezuricus: detection of acetyl group localization in macromolecules].

    PubMed

    Smirnova, N I; Mestechkina, N M; Shcherbukhin, V D

    2001-01-01

    Water-soluble glucomannans from roots of Eremurus iae and E. zangezuricus were studied. These polysaccharides were shown to contain 28.8; 69.0, and 2.2% (E. iae) and 22.6; 74.8, and 2.6% (E. zangezuricus) of D-glucose, D-mannose and acetyl groups, respectively. Their IR spectra were identical and revealed the presence of 1,4-beta-glycosidic bonds and ester carbonyl groups. 13C-NMR spectroscopy revealed both polysaccharides to be linear partially acetylated 1,4-beta-D-glucomannans. Acetyl groups substituted C-2- and C-3-hydroxyls of mannopyranose residues. Comparison of 13C-NMR data and the results of correlation analysis enables a conclusion to be made that acetyl groups can substitute no more than one OH-group in the mannopyranosyl residue. [alpha]D = -34.0 degrees, [eta] and molecular weights (MW) for E. iae polysaccharide were determined to be -34.0, 6.5 dl/g, and 265.5 kDa, respectively, and for E. zangezuricus polysaccharide -38.2, 5.4 dl/g, and 233.5 kDa, respectively. A correlation between intrinsic viscosities of polysaccharides and their molecular masses determined by HPLC was revealed.

  7. Coacervate formation from natural glycolipid: one acetyl group on the headgroup triggers coacervate-to-vesicle transition.

    PubMed

    Imura, T; Yanagishita, H; Kitamoto, D

    2004-09-01

    Coacervate (L3 phase) formation of the single component "natural" glycoliped biosurfactant, MEL-A, was observed for the first time by using an optical microscope, a confocal laser scanning microscope (CLSM), and a freeze-fracture electron microscope (FF-TEM). It was also found that only a slight decrease in spontaneous curvature resulting from the absence of one acetyl group on the headgroup induced a drastic morphological change in the 3D self-assembled structure from coacervates (L3 phase) to ordered vesicles (Lalpha phase).

  8. Stereocontrolled photocyclization of 1,2-diketones: application of a 1,3-acetyl group transfer methodology to carbohydrates.

    PubMed

    Herrera, Antonio J; Rondón, María; Suárez, Ernesto

    2008-05-01

    Photolysis of 1-glycosyl-2,3-butanodione derivatives using visible light is a mild and selective procedure for the synthesis of chiral 1-hydroxy-1-methyl-5-oxaspiro[3.5]nonan-2-one carbohydrate derivatives. The results strongly suggest that stereocontrol of the cyclization is dependent on conformational and stereoelectronic factors. Further oxidative opening of the 1-hydroxy-1-methyl-2-cyclobutanone moiety affords new C-ketoside derivatives either in C- and O-glycoside series. This tandem two-step process could be considered to be a stereocontrolled 1,3-transference of an acetyl group, and it can be applied either to pyranose and furanose models.

  9. Surface modification of bacterial cellulose nanofibers for property enhancement of optically transparent composites: dependence on acetyl-group DS.

    PubMed

    Ifuku, Shinsuke; Nogi, Masaya; Abe, Kentaro; Handa, Keishin; Nakatsubo, Fumiaki; Yano, Hiroyuki

    2007-06-01

    Bacterial cellulose (BC) nanofibers were acetylated to enhance the properties of optically transparent composites of acrylic resin reinforced with the nanofibers. A series of BC nanofibers acetylated from degree-of-substitution (DS) 0 to 1.76 were obtained. X-ray diffraction profiles indicated that acetylation proceeded from the surface to the core of BC nanofibers, and scanning electron microscopy images showed that the volume of nanofibers increases by the bulky acetyl group. Since acetylation decreased the refractive index of cellulose, regular transmittance of composites comprised of 63% BC nanofiber was improved, and deterioration at 580 nm because of fiber reinforcement was suppressed to only 3.4%. Acetylation of nanofibers changed their surface properties and reduced the moisture content of the composite to about one-third that of untreated composite, although excessive acetylation increased hygroscopicity. Furthermore, acetylation was found to reduce the coefficient of thermal expansion of a BC sheet from 3 x 10(-6) to below 1 x 10(-6) 1/K.

  10. The Acetyl Group Buffering Action of Carnitine Acetyltransferase Offsets Macronutrient-induced Lysine Acetylation of Mitochondrial Proteins

    PubMed Central

    Davies, Michael N.; Kjalarsdottir, Lilja; Thompson, J. Will; Dubois, Laura G.; Stevens, Robert D.; Ilkayeva, Olga R.; Brosnan, M. Julia; Rolph, Timothy P.; Grimsrud, Paul A.; Muoio, Deborah M.

    2016-01-01

    Lysine acetylation (AcK), a posttranslational modification wherein a two-carbon acetyl group binds covalently to a lysine residue, occurs prominently on mitochondrial proteins and has been linked to metabolic dysfunction. An emergent theory suggests mitochondrial AcK occurs via mass action rather than targeted catalysis. To test this hypothesis we performed mass spectrometry-based acetylproteomic analyses of quadriceps muscles from mice with skeletal muscle-specific deficiency of carnitine acetyltransferase (CrAT), an enzyme that buffers the mitochondrial acetyl-CoA pool by converting short-chain acyl-CoAs to their membrane permeant acylcarnitine counterparts. CrAT deficiency increased tissue acetyl-CoA levels and susceptibility to diet-induced AcK of broad-ranging mitochondrial proteins, coincident with diminished whole body glucose control. Sub-compartment acetylproteome analyses of muscles from obese mice and humans showed remarkable overrepresentation of mitochondrial matrix proteins. These findings reveal roles for CrAT and L-carnitine in modulating the muscle acetylproteome and provide strong experimental evidence favoring the nonenzymatic carbon pressure model of mitochondrial AcK. PMID:26748706

  11. Assignment of acetyl groups to O-2 and/or O-3 of pectic oligogalacturonides using negative electrospray ionization ion trap mass spectrometry.

    PubMed

    Quéméner, Bernard; Cabrera Pino, Juan Carlos; Ralet, Marie-Christine; Bonnin, Estelle; Thibault, Jean-François

    2003-06-01

    Partially acetylated and methylated oligogalacturonides produced by enzymatic hydrolysis of sugar beet pectin were analysed by negative electrospray ionization ion trap mass spectrometry (ESI-ITMS). The (18)O labelling of the oligomer reducing end allowed the precise assignment of the fragments resulting from glycosidic bond and cross-ring cleavages. The collisional-induced dissociation of the C(i) and Z(j) fragment ions through sequential MS(n) experiments always displayed (0, 2)A-type cross-ring cleavage ions which were related to C(2)H(4)O(2) losses. These (0, 2)A ions appeared to be highly diagnostic ions allowing the precise location of the acetyl groups to the O-2 and/or O-3 of the acetylated galacturonic acid residues.

  12. Feasibility of intensity-modulated radiotherapy combined with gemcitabine and S-1 for patients with pancreatic cancer

    PubMed Central

    KENNOKI, NORIFUMI; NAKAYAMA, HIDETSUGU; NAGAKAWA, YUICHI; HOSOKAWA, YUICHI; ITONAGA, TOMOHIRO; TAJIMA, YU; SHIRAISHI, SACHICA; MIKAMI, RYUJI; TSUCHIDA, AKIHIKO; TOKUUYE, KOICHI

    2016-01-01

    The aim of the present study was to establish whether intensity-modulated radiotherapy (IMRT) with concurrent gemcitabine and S-1 is a feasible treatment option for patients with locally advanced pancreatic ductal adenocarcinoma. Patients with pancreatic ductal adenocarcinoma were prospectively enrolled. An IMRT dose of 50.4 Gy in 28 fractions with concurrent gemcitabine at a dose of 600 mg/m2 and S-1 at a dose of 60 mg were administrated. Adverse events and associated dosimetric factors were assessed. Between February 2012 and January 2014, 17 patients with borderline resectable and 4 with unresectable pancreatic cancer were enrolled. None of the patients experienced grade 3 or worse nausea and vomiting. The planning target volume (≥200 vs. <200 ml) was a statistically significant predictive factor for neutrocytopenia (≥500 vs. 500/µl, P=0.02). Concurrent IMRT with gemcitabine and S-1 for patients with locally advanced pancreatic cancer is feasible, with tolerable hematological toxicities and low gastrointestinal toxicities. PMID:26870355

  13. Recognition Tunneling

    PubMed Central

    Lindsay, Stuart; He, Jin; Sankey, Otto; Hapala, Prokop; Jelinek, Pavel; Zhang, Peiming; Chang, Shuai; Huang, Shuo

    2010-01-01

    Single molecules in a tunnel junction can now be interrogated reliably using chemically-functionalized electrodes. Monitoring stochastic bonding fluctuations between a ligand bound to one electrode and its target bound to a second electrode (“tethered molecule-pair” configuration) gives insight into the nature of the intermolecular bonding at a single molecule-pair level, and defines the requirements for reproducible tunneling data. Simulations show that there is an instability in the tunnel gap at large currents, and this results in a multiplicity of contacts with a corresponding spread in the measured currents. At small currents (i.e. large gaps) the gap is stable, and functionalizing a pair of electrodes with recognition reagents (the “free analyte” configuration) can generate a distinct tunneling signal when an analyte molecule is trapped in the gap. This opens up a new interface between chemistry and electronics with immediate implications for rapid sequencing of single DNA molecules. PMID:20522930

  14. Molecular mechanism underlying promiscuous polyamine recognition by spermidine acetyltransferase.

    PubMed

    Sugiyama, Shigeru; Ishikawa, Sae; Tomitori, Hideyuki; Niiyama, Mayumi; Hirose, Mika; Miyazaki, Yuma; Higashi, Kyohei; Murata, Michio; Adachi, Hiroaki; Takano, Kazufumi; Murakami, Satoshi; Inoue, Tsuyoshi; Mori, Yusuke; Kashiwagi, Keiko; Igarashi, Kazuei; Matsumura, Hiroyoshi

    2016-07-01

    Spermidine acetyltransferase (SAT) from Escherichia coli, which catalyses the transfer of acetyl groups from acetyl-CoA to spermidine, is a key enzyme in controlling polyamine levels in prokaryotic cells. In this study, we determined the crystal structure of SAT in complex with spermidine (SPD) and CoA at 2.5Å resolution. SAT is a dodecamer organized as a hexamer of dimers. The secondary structural element and folding topology of the SAT dimer resemble those of spermidine/spermine N(1)-acetyltransferase (SSAT), suggesting an evolutionary link between SAT and SSAT. However, the polyamine specificity of SAT is distinct from that of SSAT and is promiscuous. The SPD molecule is also located at the inter-dimer interface. The distance between SPD and CoA molecules is 13Å. A deep, highly acidic, water-filled cavity encompasses the SPD and CoA binding sites. Structure-based mutagenesis and in-vitro assays identified SPD-bound residues, and the acidic residues lining the walls of the cavity are mostly essential for enzymatic activities. Based on mutagenesis and structural data, we propose an acetylation mechanism underlying promiscuous polyamine recognition for SAT. PMID:27163532

  15. Building Group Recognition.

    ERIC Educational Resources Information Center

    Chartier, George

    1994-01-01

    Discusses the value of name recognition for theater companies. Describes steps toward identity and recognition, analyzing the group, the mission statement, symbolic logic, designing and identity, developing a communications plan, and meaningful activities. (SR)

  16. Speech recognition and understanding

    SciTech Connect

    Vintsyuk, T.K.

    1983-05-01

    This article discusses the automatic processing of speech signals with the aim of finding a sequence of works (speech recognition) or a concept (speech understanding) being transmitted by the speech signal. The goal of the research is to develop an automatic typewriter that will automatically edit and type text under voice control. A dynamic programming method is proposed in which all possible class signals are stored, after which the presented signal is compared to all the stored signals during the recognition phase. Topics considered include element-by-element recognition of words of speech, learning speech recognition, phoneme-by-phoneme speech recognition, the recognition of connected speech, understanding connected speech, and prospects for designing speech recognition and understanding systems. An application of the composition dynamic programming method for the solution of basic problems in the recognition and understanding of speech is presented.

  17. Profiles of Discourse Recognition

    ERIC Educational Resources Information Center

    Singer, Murray

    2013-01-01

    A discourse recognition theory derived from more general memory formulations would be broad in its psychological implications. This study compared discourse recognition with some established profiles of item recognition. Participants read 10 stories either once or twice each. They then rated their confidence in recognizing explicit, paraphrased,…

  18. Multimodal eye recognition

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

  19. Kin Recognition in Bacteria.

    PubMed

    Wall, Daniel

    2016-09-01

    The ability of bacteria to recognize kin provides a means to form social groups. In turn these groups can lead to cooperative behaviors that surpass the ability of the individual. Kin recognition involves specific biochemical interactions between a receptor(s) and an identification molecule(s). Recognition specificity, ensuring that nonkin are excluded and kin are included, is critical and depends on the number of loci and polymorphisms involved. After recognition and biochemical perception, the common ensuing cooperative behaviors include biofilm formation, quorum responses, development, and swarming motility. Although kin recognition is a fundamental mechanism through which cells might interact, microbiologists are only beginning to explore the topic. This review considers both molecular and theoretical aspects of bacterial kin recognition. Consideration is also given to bacterial diversity, genetic relatedness, kin selection theory, and mechanisms of recognition. PMID:27359217

  20. Diagnostic odor recognition

    PubMed

    Rosenblatt; Phan; Desandre; Lobon; Hsu

    2000-10-01

    Many diseases, toxic ingestions, and intoxications have characteristic odors. These odors may provide diagnostic clues that affect rapid treatment long before laboratory confirmation or clinical deterioration. Odor recognition skills, similar to auscultation and palpation skills, require teaching and practical exposure. Dr. Goldfrank and colleagues recognized the importance of teaching odor recognition to emergency service providers. They proposed the "sniffing bar" method for odor recognition training. OBJECTIVES: (1) To identify the recognition rates of medically important odors among emergency care providers. (2) To investigate the effectiveness of teaching odor recognition. Hypothesis: The recognition rates of medically important odors will increase after teaching exposure. METHODS: The study exposed emergency care providers to 11 tubes of odors. Identifications of each substance were recorded. After corrective feedback, subjects were re-tested on their ability to identify the odors. Analysis of odor recognition improvement after teaching was done via chi-square test. RESULTS: Improvement in identification after teaching was seen in all odors. However, the improvement was significant only in the lesscommon substances because their initial recognition was especially low. Significant changes may improve with a larger sample size. Subjects often confuse the odors of alcohol with acetone, and wintergreen with camphor. CONCLUSIONS: The recognition rates are higher for the more-common odors, and lower for the less-common odors. Teaching exposures to the less well-known odors are effective and can significantly improve the recognition rate of these substances. Because odor recognition may affect rapid diagnosis and treatment of certain medical emergencies such as toxic ingestion, future studies should investigate the correlation between odor recognition and the ability to identify corresponding medical emergencies.

  1. Moreland Recognition Program.

    ERIC Educational Resources Information Center

    Moreland Elementary School District, San Jose, CA.

    THE FOLLOWING IS THE FULL TEXT OF THIS DOCUMENT: Recognition for special effort and achievement has been noted as a component of effective schools. Schools in the Moreland School District have effectively improved standards of discipline and achievement by providing forty-six different ways for children to receive positive recognition. Good…

  2. Infant Visual Recognition Memory

    ERIC Educational Resources Information Center

    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…

  3. Molecular basis of non-self recognition by the horseshoe crab tachylectins.

    PubMed

    Kawabata, Shun-ichiro; Tsuda, Ryoko

    2002-09-19

    The self/non-self discrimination by innate immunity through simple ligands universally expressed both on pathogens and hosts, such as monosaccharides and acetyl group, depends on the density or clustering patterns of the ligands. The specific recognition by the horseshoe crab tachylectins with a propeller-like fold or a propeller-like oligomeric arrangement is reinforced by the short distance between the individual binding sites that interact with pathogen-associated molecular patterns (PAMPs). There is virtually no conformational change in the main or side chains of tachylectins upon binding with the ligands. This low structural flexibility of the propeller structures must be very important for specific interaction with PAMPs. Mammalian lectins, such as mannose-binding lectin and ficolins, trigger complement activation through the lectin pathway in the form of opsonins. However, tachylectins have no effector collagenous domains and no lectin-associated serine proteases found in the mammalian lectins. Furthermore, no complement-like proteins have been found in horseshoe crabs, except for alpha(2)-macroglobulin. The mystery of the molecular mechanism of the scavenging pathway of pathogens in horseshoe crabs remains to be solved.

  4. PCA facial expression recognition

    NASA Astrophysics Data System (ADS)

    El-Hori, Inas H.; El-Momen, Zahraa K.; Ganoun, Ali

    2013-12-01

    This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. The comparative study of Facial Expression Recognition (FER) techniques namely Principal Component's analysis (PCA) and PCA with Gabor filters (GF) is done. The objective of this research is to show that PCA with Gabor filters is superior to the first technique in terms of recognition rate. To test and evaluates their performance, experiments are performed using real database by both techniques. The universally accepted five principal emotions to be recognized are: Happy, Sad, Disgust and Angry along with Neutral. The recognition rates are obtained on all the facial expressions.

  5. Pattern recognition technique

    NASA Technical Reports Server (NTRS)

    Hong, J. P.

    1971-01-01

    Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

  6. Context based gait recognition

    NASA Astrophysics Data System (ADS)

    Bazazian, Shermin; Gavrilova, Marina

    2012-06-01

    Gait recognition has recently become a popular topic in the field of biometrics. However, the main hurdle is the insufficient recognition rate in the presence of low quality samples. The main focus of this paper is to investigate how the performance of a gait recognition system can be improved using additional information about behavioral patterns of users and the context in which samples have been taken. The obtained results show combining the context information with biometric data improves the performance of the system at a very low cost. The amount of improvement depends on the distinctiveness of the behavioral patterns and the quality of the gait samples. Using the appropriate distinctive behavioral models it is possible to achieve a 100% recognition rate.

  7. CASE Recognition Awards.

    ERIC Educational Resources Information Center

    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)

  8. Progress in fold recognition.

    PubMed

    Flöckner, H; Braxenthaler, M; Lackner, P; Jaritz, M; Ortner, M; Sippl, M J

    1995-11-01

    The prediction experiment reveals that fold recognition has become a powerful tool in structural biology. We applied our fold recognition technique to 13 target sequences. In two cases, replication terminating protein and prosequence of subtilisin, the predicted structures are very similar to the experimentally determined folds. For the first time, in a public blind test, the unknown structures of proteins have been predicted ahead of experiment to an accuracy approaching molecular detail. In two other cases the approximate folds have been predicted correctly. According to the assessors there were 12 recognizable folds among the target proteins. In our postprediction analysis we find that in 7 cases our fold recognition technique is successful. In several of the remaining cases the predicted folds have interesting features in common with the experimental results. We present our procedure, discuss the results, and comment on several fundamental and technical problems encountered in fold recognition.

  9. [Electrocardiograph beat pattern recognition].

    PubMed

    Zhou, Qunyi; Lu, Xudong; Duan, Huiling

    2005-02-01

    It is very important to recognize arrhythmia in clinical electrocardiography (ECG) analysis. The fundamental of beat pattern recognition is presented in this paper. Various prevalent methods for arrhythmia recognitiion are categorized and summarized, based on which the advantages and disadvantages among the methods are compared, and the main problems are discussed in depth. At last, the development trend of arrhythmia recognition technology is pointed out.

  10. Page Recognition: Quantum Leap In Recognition Technology

    NASA Astrophysics Data System (ADS)

    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

  11. Probabilistic Open Set Recognition

    NASA Astrophysics Data System (ADS)

    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

  12. Toward hyperspectral face recognition

    NASA Astrophysics Data System (ADS)

    Robila, Stefan A.

    2008-02-01

    Face recognition continues to meet significant challenges in reaching accurate results and still remains one of the activities where humans outperform technology. An attractive approach in improving face identification is provided by the fusion of multiple imaging sources such as visible and infrared images. Hyperspectral data, i.e. images collected over hundreds of narrow contiguous light spectrum intervals constitute a natural choice for expanding face recognition image fusion, especially since it may provide information beyond the normal visible range, thus exceeding the normal human sensing. In this paper we investigate the efficiency of hyperspectral face recognition through an in house experiment that collected data in over 120 bands within the visible and near infrared range. The imagery was produced using an off the shelf sensor in both indoors and outdoors with the subjects being photographed from various angles. Further processing included spectra collection and feature extraction. Human matching performance based on spectral properties is discussed.

  13. Recognition for Employed Inventors.

    ERIC Educational Resources Information Center

    Sanders, Howard J.

    1980-01-01

    Presents arguments for monetary rewards and other forms of recognition by employers for inventions of employed inventors, particularly as the concept applies to stimulating innovativeness in America. Discusses the controversy of federally mandated compensation for employed inventors. The efforts of the American Chemical Society along these lines…

  14. Units of Word Recognition.

    ERIC Educational Resources Information Center

    Santa, Carol M.; And Others

    Both psychologists and reading specialists have been interested in whether words are processed letter by letter or in larger units. A reaction time paradigm was used to evaluate these options with interest focused on potential units of word recognition which might be functional within single syllable words. The basic paradigm involved presenting…

  15. Optical Character Recognition.

    ERIC Educational Resources Information Center

    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)

  16. [Facial recognition and autism].

    PubMed

    Assumpçäo Júnior, F B; Sprovieri, M H; Kuczynski, E; Farinha, V

    1999-12-01

    Through the presentation of four facial expressions' illustrations, we evaluate the capacity of autistic children recognition, comparing with normal intelligence children and adults. The comparison of results was accomplished through the qui-square test. The differences observed were significant, showing that a disturbance of the facial expressions' perception is present in autistic children, and that it interferes directly in the social relationships.

  17. Recognition Memory for Pseudowords

    ERIC Educational Resources Information Center

    Greene, Robert L.

    2004-01-01

    Participants are more likely to give positive responses on a recognition test to pseudowords (pronounceable nonwords) than words. A series of experiments suggests that this difference reflects the greater overall familiarity of pseudowords than of words. Pseudowords receive higher ratings of similarity to a studied list than do words. Pseudowords…

  18. Microprocessor for speech recognition

    SciTech Connect

    Ishizuka, H.; Watari, M.; Sakoe, H.; Chiba, S.; Iwata, T.; Matsuki, T.; Kawakami, Y.

    1983-01-01

    A new single-chip microprocessor for speech recognition has been developed utilizing multi-processor architecture and pipelined structure. By DP-matching algorithm, the processor recognizes up to 340 isolated words or 40 connected words in realtime. 6 references.

  19. 1987 CASE Recognition Awards.

    ERIC Educational Resources Information Center

    Currents, 1987

    1987-01-01

    The 1987 CASE Recognition Awards are presented for: general excellence in programs; student recruitment marketing improvement; video public service announcements, news, and commercial spots; total publications; magazines of the decade; improvement in periodicals; photocommunications via print; designer of the year and series; and imagination in…

  20. Pattern recognition in bioinformatics.

    PubMed

    de Ridder, Dick; de Ridder, Jeroen; Reinders, Marcel J T

    2013-09-01

    Pattern recognition is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Less explicitly, classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology. A course on pattern recognition (or machine learning) should therefore be at the core of any bioinformatics education program. In this review, we discuss the main elements of a pattern recognition course, based on material developed for courses taught at the BSc, MSc and PhD levels to an audience of bioinformaticians, computer scientists and life scientists. We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained.

  1. Supporting Quality Teachers with Recognition

    ERIC Educational Resources Information Center

    Andrews, Hans A.

    2011-01-01

    Value has been found in providing recognition and awards programs for excellent teachers. Research has also found a major lack of these programs in both the USA and in Australia. Teachers receiving recognition and awards for their teaching have praised recognition programs as providing motivation for them to continue high-level instruction.…

  2. Word Recognition in Auditory Cortex

    ERIC Educational Resources Information Center

    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…

  3. Visual Recognition Memory across Contexts

    ERIC Educational Resources Information Center

    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…

  4. Recognition of Teaching Excellence*

    PubMed Central

    Piascik, Peggy; Medina, Melissa; Pittenger, Amy; Rose, Renee; Creekmore, Freddy; Soltis, Robert; Bouldin, Alicia; Schwarz, Lindsay; Scott, Steven

    2010-01-01

    The 2008-2009 Task Force for the Recognition of Teaching Excellence was charged by the AACP Council of Faculties Leadership to examine teaching excellence by collecting best practices from colleges and schools of pharmacy, evaluating the literature to identify evidence-based criteria for excellent teaching, and recommending appropriate means to acknowledge and reward teaching excellence. This report defines teaching excellence and discusses a variety of ways to assess it, including student, alumni, peer, and self-assessment. The task force identifies important considerations that colleges and schools must address when establishing teaching recognition programs including the purpose, criteria, number and mix of awards, frequency, type of award, and method of nominating and determining awardees. The report concludes with recommendations for the academy to consider when establishing and revising teaching award programs. PMID:21301598

  5. Recognition of teaching excellence.

    PubMed

    Hammer, Dana; Piascik, Peggy; Medina, Melissa; Pittenger, Amy; Rose, Renee; Creekmore, Freddy; Soltis, Robert; Bouldin, Alicia; Schwarz, Lindsay; Scott, Steven

    2010-11-10

    The 2008-2009 Task Force for the Recognition of Teaching Excellence was charged by the AACP Council of Faculties Leadership to examine teaching excellence by collecting best practices from colleges and schools of pharmacy, evaluating the literature to identify evidence-based criteria for excellent teaching, and recommending appropriate means to acknowledge and reward teaching excellence. This report defines teaching excellence and discusses a variety of ways to assess it, including student, alumni, peer, and self-assessment. The task force identifies important considerations that colleges and schools must address when establishing teaching recognition programs including the purpose, criteria, number and mix of awards, frequency, type of award, and method of nominating and determining awardees. The report concludes with recommendations for the academy to consider when establishing and revising teaching award programs.

  6. Audio-visual gender recognition

    NASA Astrophysics Data System (ADS)

    Liu, Ming; Xu, Xun; Huang, Thomas S.

    2007-11-01

    Combining different modalities for pattern recognition task is a very promising field. Basically, human always fuse information from different modalities to recognize object and perform inference, etc. Audio-Visual gender recognition is one of the most common task in human social communication. Human can identify the gender by facial appearance, by speech and also by body gait. Indeed, human gender recognition is a multi-modal data acquisition and processing procedure. However, computational multimodal gender recognition has not been extensively investigated in the literature. In this paper, speech and facial image are fused to perform a mutli-modal gender recognition for exploring the improvement of combining different modalities.

  7. Substrate recognition of N,N'-diacetylchitobiose deacetylase from Pyrococcus horikoshii.

    PubMed

    Nakamura, Tsutomu; Yonezawa, Yasushige; Tsuchiya, Yuko; Niiyama, Mayumi; Ida, Kurumi; Oshima, Maki; Morita, Junji; Uegaki, Koichi

    2016-09-01

    Enzymes of carbohydrate esterase (CE) family 14 catalyze hydrolysis of N-acetyl groups at the non-reducing end of the N-acetylglucosamine (GlcNAc) residue of chitooligosaccharides or related compounds. N,N'-diacetylchitobiose deacetylase (Dac) belongs to the CE-14 family and plays a role in the chitinolytic pathway in archaea by deacetylating N,N'-diacetylchitobiose (GlcNAc2), which is the end product of chitinase. In this study, we revealed the structural basis of reaction specificity in CE-14 deacetylases by solving a crystal structure of Dac from Pyrococcus horikoshii (Ph-Dac) in complex with a novel reaction intermediate analog. We developed 2-deoxy-2-methylphosphoramido-d-glucose (MPG) as the analog of the tetrahedral oxyanion intermediate of the monosaccharide substrate GlcNAc. The crystal structure of Ph-Dac in complex with MPG demonstrated that Arg92, Asp115, and His152 side chains interact with hydroxyl groups of the glucose moiety of the non-reducing-end GlcNAc residue. The amino acid residues responsible for recognition of the MPG glucose moiety are spatially conserved in other CE-14 deacetylases. Molecular dynamics simulation of the structure of the Ph-Dac-GlcNAc2 complex indicated that the reducing GlcNAc residue is placed in a large intermolecular cleft and is not involved with specific interactions with the enzyme. This observation was consistent with results indicating that Ph-Dac displayed similar kinetic parameters for both GlcNAc and GlcNAc2. This study provides the structural basis of reaction-site specificity of Dac and related CE-14 enzymes.

  8. Substrate recognition of N,N'-diacetylchitobiose deacetylase from Pyrococcus horikoshii.

    PubMed

    Nakamura, Tsutomu; Yonezawa, Yasushige; Tsuchiya, Yuko; Niiyama, Mayumi; Ida, Kurumi; Oshima, Maki; Morita, Junji; Uegaki, Koichi

    2016-09-01

    Enzymes of carbohydrate esterase (CE) family 14 catalyze hydrolysis of N-acetyl groups at the non-reducing end of the N-acetylglucosamine (GlcNAc) residue of chitooligosaccharides or related compounds. N,N'-diacetylchitobiose deacetylase (Dac) belongs to the CE-14 family and plays a role in the chitinolytic pathway in archaea by deacetylating N,N'-diacetylchitobiose (GlcNAc2), which is the end product of chitinase. In this study, we revealed the structural basis of reaction specificity in CE-14 deacetylases by solving a crystal structure of Dac from Pyrococcus horikoshii (Ph-Dac) in complex with a novel reaction intermediate analog. We developed 2-deoxy-2-methylphosphoramido-d-glucose (MPG) as the analog of the tetrahedral oxyanion intermediate of the monosaccharide substrate GlcNAc. The crystal structure of Ph-Dac in complex with MPG demonstrated that Arg92, Asp115, and His152 side chains interact with hydroxyl groups of the glucose moiety of the non-reducing-end GlcNAc residue. The amino acid residues responsible for recognition of the MPG glucose moiety are spatially conserved in other CE-14 deacetylases. Molecular dynamics simulation of the structure of the Ph-Dac-GlcNAc2 complex indicated that the reducing GlcNAc residue is placed in a large intermolecular cleft and is not involved with specific interactions with the enzyme. This observation was consistent with results indicating that Ph-Dac displayed similar kinetic parameters for both GlcNAc and GlcNAc2. This study provides the structural basis of reaction-site specificity of Dac and related CE-14 enzymes. PMID:27456364

  9. A fibrinogen-related protein identified from hepatopancreas of crayfish is a potential pattern recognition receptor.

    PubMed

    Chen, Qiming; Bai, Suhua; Dong, Chaohua

    2016-09-01

    Fibrinogen-related protein (FREP) family is a large group of proteins containing fibrinogen-like (FBG) domain and plays multiple physiological roles in animals. However, their immune functions in crayfish are not fully explored. In the present study, a novel fibrinogen-like protein (designated as PcFBN1) was identified and characterized from hepatopancreas of red swamp crayfish Procambarus clarkii. The cDNA sequence of PcFBN1 contains an open reading frame (ORF) of 1353 bp encoding a protein of 450 amino acids. Sequence and structural analysis indicated that PcFBN1 contains an FBG domain in C-terminal and a putative signal peptide of 19 amino acids in N-terminal. Semi-quantitative PCR revealed that the main expression of PcFBN1 was observed in hepatopancreas and hemocyte. Temporal expression analysis exhibited that PcFBN1 expression could be significantly induced by heat-killed Aeromonas hydrophila. Tissue distribution and temporal change of PcFBN1 suggested that PcFBN1 may be involved in immune responses of red swamp crayfish. Recombinant PcFBN1 protein binds and agglutinates both gram-negative bacteria Escherichia coli and gram-positive bacteria Micrococcus lysodeikticus. Moreover, binding and agglutination is Ca(2+) dependent. Further analysis indicated that PcFBN1 recognizes some acetyl group-containing substance LPS and PGN. RNAi experiment revealed that PcFBN1 is required for bacterial clearance and survival from A. hydrophila infection. Reduction of PcFBN1 expression significantly decreased the survival and enhanced the number of A. hydrophila in the hemolymph. These results indicated that PcFBN1 plays an important role in the innate immunity of red swamp crayfish as a potential pattern recognition receptor. PMID:27417229

  10. Smart pattern recognition

    NASA Astrophysics Data System (ADS)

    Alfalou, A.; Brosseau, C.; Alam, M. S.

    2013-03-01

    The purpose of this paper is to test correlation methods for pattern recognition applications. A broad overview of the main correlation architectures is first given. Many correlation data are compared with those obtained from standard pattern recognition methods. We used our simulations to predict improved decisional performance from correlation methods. More specifically, we are focused on the POF filter and composite filter family. We present an optimized composite correlation filter, called asymmetric segmented phase-only filter (ASPOF) for mobile target recognition applications. The main objective is to find a compromise between the number of references to be merged in the correlation filter and the time needed for making a decision. We suggest an all-numerical implementation of a VanderLugt (VLC) type composite filter. The aim of this all-numerical implementation is to take advantage of the benefits of the correlation methods and make the correlator easily reconfigurable for various scenarios. The use of numerical implementation of the optical Fourier transform improves the decisional performance of the correlator. Further, it renders the correlator less sensitive to the saturation phenomenon caused by the increased number of references used for fabricating the composite filter. Different tests are presented making use of the peak-to-correlation energy criterion and ROC curves. These tests confirm the validity ofour technique. Elderly fall detection and underwater mine detection are two applications which are considered for illustrating the benefits of our approach. The present work is motivated by the need for detailed discussions of the choice of the correlation architecture for these specific applications, pre-processing in the input plane and post processing in the output plane techniques for such analysis.

  11. [Comparative studies of face recognition].

    PubMed

    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.

    PubMed

    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. Retina vascular network recognition

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

    1993-09-01

    The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.

  14. Complex Event Recognition Architecture

    NASA Technical Reports Server (NTRS)

    Fitzgerald, William A.; Firby, R. James

    2009-01-01

    Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

  15. Sudden Event Recognition: A Survey

    PubMed Central

    Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

    2013-01-01

    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. PMID:23921828

  16. Frequency-Based Fingerprint Recognition

    NASA Astrophysics Data System (ADS)

    Aguilar, Gualberto; Sánchez, Gabriel; Toscano, Karina; Pérez, Héctor

    abstract Fingerprint recognition is one of the most popular methods used for identification with greater success degree. Fingerprint has unique characteristics called minutiae, which are points where a curve track ends, intersects, or branches off. In this chapter a fingerprint recognition method is proposed in which a combination of Fast Fourier Transform (FFT) and Gabor filters is used for image enhancement. A novel recognition stage using local features for recognition is also proposed. Also a verification stage is introduced to be used when the system output has more than one person.

  17. [Faces affect recognition in schizophrenia].

    PubMed

    Prochwicz, Katarzyna; Rózycka, Jagoda

    2012-01-01

    Clinical observations and the results of many experimental researches indicate that individuals suffering from schizophrenia reveal difficulties in the recognition of emotional states experienced by other people; however the causes and the range of these problems have not been clearly described. Despite early research results confirming that difficulties in emotion recognition are related only to negative emotions, the results of the researches conducted over the lat 30 years indicate that emotion recognition problems are a manifestation of a general cognitive deficit, and they do not concern specific emotions. The article contains a review of the research on face affect recognition in schizophrenia. It discusses the causes of these difficulties, the differences in the accuracy of the recognition of specific emotions, the relationship between the symptoms of schizophrenia and the severity of problems with face perception, and the types of cognitive processes which influence the disturbances in face affect recognition. Particular attention was paid to the methodology of the research on face affect recognition, including the methods used in control tasks relying on the identification of neutral faces designed to assess the range of deficit underlying the face affect recognition problems. The analysis of methods used in particular researches revealed some weaknesses. The article also deals with the question of the possibilities of improving the ability to recognise the emotions, and briefly discusses the efficiency of emotion recognition training programs designed for patients suffering from schizophrenia.

  18. The Legal Recognition of Sign Languages

    ERIC Educational Resources Information Center

    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…

  19. Teaching and the Dialectic of Recognition

    ERIC Educational Resources Information Center

    Huttunen, Rauno; Heikkinen, Hannu L. T.

    2004-01-01

    In this article, the processes of recognition within education are discussed. Frequently, recognition is reduced to polite behaviour or etiquette. Another narrow view of recognition is, behaviouristically speaking, to regard it as mere feedback. We claim that authentic recognition is a different matter. Receiving recognition, as Charles Taylor has…

  20. Chemical recognition software

    SciTech Connect

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.H. Jr.; Tisone, G.C.

    1994-06-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures, even when the mixture is noisy and contaminated with unknowns.

  1. Chemical recognition software

    SciTech Connect

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.J. Jr.; Tisone, G.C.

    1994-12-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures. even when the mixture is noisy and contaminated with unknowns.

  2. Early recognition of speech

    PubMed Central

    Remez, Robert E; Thomas, Emily F

    2013-01-01

    Classic research on the perception of speech sought to identify minimal acoustic correlates of each consonant and vowel. In explaining perception, this view designated momentary components of an acoustic spectrum as cues to the recognition of elementary phonemes. This conceptualization of speech perception is untenable given the findings of phonetic sensitivity to modulation independent of the acoustic and auditory form of the carrier. The empirical key is provided by studies of the perceptual organization of speech, a low-level integrative function that finds and follows the sensory effects of speech amid concurrent events. These projects have shown that the perceptual organization of speech is keyed to modulation; fast; unlearned; nonsymbolic; indifferent to short-term auditory properties; and organization requires attention. The ineluctably multisensory nature of speech perception also imposes conditions that distinguish language among cognitive systems. WIREs Cogn Sci 2013, 4:213–223. doi: 10.1002/wcs.1213 PMID:23926454

  3. Recognition Using Hybrid Classifiers.

    PubMed

    Osadchy, Margarita; Keren, Daniel; Raviv, Dolev

    2016-04-01

    A canonical problem in computer vision is category recognition (e.g., find all instances of human faces, cars etc., in an image). Typically, the input for training a binary classifier is a relatively small sample of positive examples, and a huge sample of negative examples, which can be very diverse, consisting of images from a large number of categories. The difficulty of the problem sharply increases with the dimension and size of the negative example set. We propose to alleviate this problem by applying a "hybrid" classifier, which replaces the negative samples by a prior, and then finds a hyperplane which separates the positive samples from this prior. The method is extended to kernel space and to an ensemble-based approach. The resulting binary classifiers achieve an identical or better classification rate than SVM, while requiring far smaller memory and lower computational complexity to train and apply.

  4. TOPICAL REVIEW: Recognition tunneling

    NASA Astrophysics Data System (ADS)

    Lindsay, Stuart; He, Jin; Sankey, Otto; Hapala, Prokop; Jelinek, Pavel; Zhang, Peiming; Chang, Shuai; Huang, Shuo

    2010-07-01

    Single molecules in a tunnel junction can now be interrogated reliably using chemically functionalized electrodes. Monitoring stochastic bonding fluctuations between a ligand bound to one electrode and its target bound to a second electrode ('tethered molecule-pair' configuration) gives insight into the nature of the intermolecular bonding at a single molecule-pair level, and defines the requirements for reproducible tunneling data. Simulations show that there is an instability in the tunnel gap at large currents, and this results in a multiplicity of contacts with a corresponding spread in the measured currents. At small currents (i.e. large gaps) the gap is stable, and functionalizing a pair of electrodes with recognition reagents (the 'free-analyte' configuration) can generate a distinct tunneling signal when an analyte molecule is trapped in the gap. This opens up a new interface between chemistry and electronics with immediate implications for rapid sequencing of single DNA molecules.

  5. Automatic speech recognition

    NASA Astrophysics Data System (ADS)

    Espy-Wilson, Carol

    2005-04-01

    Great strides have been made in the development of automatic speech recognition (ASR) technology over the past thirty years. Most of this effort has been centered around the extension and improvement of Hidden Markov Model (HMM) approaches to ASR. Current commercially-available and industry systems based on HMMs can perform well for certain situational tasks that restrict variability such as phone dialing or limited voice commands. However, the holy grail of ASR systems is performance comparable to humans-in other words, the ability to automatically transcribe unrestricted conversational speech spoken by an infinite number of speakers under varying acoustic environments. This goal is far from being reached. Key to the success of ASR is effective modeling of variability in the speech signal. This tutorial will review the basics of ASR and the various ways in which our current knowledge of speech production, speech perception and prosody can be exploited to improve robustness at every level of the system.

  6. Computer image processing and recognition

    NASA Technical Reports Server (NTRS)

    Hall, E. L.

    1979-01-01

    A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.

  7. Methods of Teaching Speech Recognition

    ERIC Educational Resources Information Center

    Rader, Martha H.; Bailey, Glenn A.

    2010-01-01

    Objective: This article introduces the history and development of speech recognition, addresses its role in the business curriculum, outlines related national and state standards, describes instructional strategies, and discusses the assessment of student achievement in speech recognition classes. Methods: Research methods included a synthesis of…

  8. Sign Facilitation in Word Recognition.

    ERIC Educational Resources Information Center

    Wauters, Loes N.; Knoors, Harry E. T.; Vervloed, Mathijs P. J.; Aarnoutse, Cor A. J.

    2001-01-01

    This study examined whether use of sign language would facilitate reading word recognition by 16 deaf children (6- to 1 years-old) in the Netherlands. Results indicated that if words were learned through speech, accompanied by the relevant sign, accuracy of word recognition was greater than if words were learned solely through speech. (Contains…

  9. Word Recognition and Critical Reading.

    ERIC Educational Resources Information Center

    Groff, Patrick

    1991-01-01

    This article discusses the distinctions between literal and critical reading and explains the role that word recognition ability plays in critical reading behavior. It concludes that correct word recognition provides the raw material on which higher order critical reading is based. (DB)

  10. Recognition without Rewards: Building Connections.

    ERIC Educational Resources Information Center

    Cameron, Caren; Tate, Betty; MacNaughton, Daphne; Politano, Colleen

    Noting that the use of rewards in the form of stickers, trophies, prizes, points, tokens, and grades is commonplace in elementary education today, this book explores the differences between rewards and recognition and shows how teachers can build student confidence, motivate learning, and develop skills for lifelong learning through recognition.…

  11. Face recognition performance with superresolution.

    PubMed

    Hu, Shuowen; Maschal, Robert; Young, S Susan; Hong, Tsai Hong; Phillips, P Jonathon

    2012-06-20

    With the prevalence of surveillance systems, face recognition is crucial to aiding the law enforcement community and homeland security in identifying suspects and suspicious individuals on watch lists. However, face recognition performance is severely affected by the low face resolution of individuals in typical surveillance footage, oftentimes due to the distance of individuals from the cameras as well as the small pixel count of low-cost surveillance systems. Superresolution image reconstruction has the potential to improve face recognition performance by using a sequence of low-resolution images of an individual's face in the same pose to reconstruct a more detailed high-resolution facial image. This work conducts an extensive performance evaluation of superresolution for a face recognition algorithm using a methodology and experimental setup consistent with real world settings at multiple subject-to-camera distances. Results show that superresolution image reconstruction improves face recognition performance considerably at the examined midrange and close range. PMID:22722306

  12. Face recognition performance with superresolution.

    PubMed

    Hu, Shuowen; Maschal, Robert; Young, S Susan; Hong, Tsai Hong; Phillips, P Jonathon

    2012-06-20

    With the prevalence of surveillance systems, face recognition is crucial to aiding the law enforcement community and homeland security in identifying suspects and suspicious individuals on watch lists. However, face recognition performance is severely affected by the low face resolution of individuals in typical surveillance footage, oftentimes due to the distance of individuals from the cameras as well as the small pixel count of low-cost surveillance systems. Superresolution image reconstruction has the potential to improve face recognition performance by using a sequence of low-resolution images of an individual's face in the same pose to reconstruct a more detailed high-resolution facial image. This work conducts an extensive performance evaluation of superresolution for a face recognition algorithm using a methodology and experimental setup consistent with real world settings at multiple subject-to-camera distances. Results show that superresolution image reconstruction improves face recognition performance considerably at the examined midrange and close range.

  13. Speech Recognition: How Do We Teach It?

    ERIC Educational Resources Information Center

    Barksdale, Karl

    2002-01-01

    States that growing use of speech recognition software has made voice writing an essential computer skill. Describes how to present the topic, develop basic speech recognition skills, and teach speech recognition outlining, writing, proofreading, and editing. (Contains 14 references.) (SK)

  14. Accuracy enhanced thermal face recognition

    NASA Astrophysics Data System (ADS)

    Lin, Chun-Fu; Lin, Sheng-Fuu

    2013-11-01

    Human face recognition has been generally researched for the last three decades. Face recognition with thermal image has begun to attract significant attention gradually since illumination of environment would not affect the recognition performance. However, the recognition performance of traditional thermal face recognizer is still insufficient in practical application. This study presents a novel thermal face recognizer employing not only thermal features but also critical facial geometric features which would not be influenced by hair style to improve the recognition performance. A three-layer back-propagation feed-forward neural network is applied as the classifier. Traditional thermal face recognizers only use the indirect information of the topography of blood vessels like thermogram as features. To overcome this limitation, the proposed thermal face recognizer can use not only the indirect information but also the direct information of the topography of blood vessels which is unique for every human. Moreover, the recognition performance of the proposed thermal features would not decrease even if the hair of frontal bone varies, the eye blinks or the nose breathes. Experimental results show that the proposed features are significantly more effective than traditional thermal features and the recognition performance of thermal face recognizer is improved.

  15. Macromolecular recognition: Recognition of polymer side chains by cyclodextrin

    NASA Astrophysics Data System (ADS)

    Hashidzume, Akihito; Harada, Akira

    2015-12-01

    The interaction of cyclodextrins (CD) with water soluble polymers possessing guest residues has been investigated as model systems in biological molecular recognition. The selectivity of interaction of CD with polymer-carrying guest residues is controlled by polymer chains, i.e., the steric effect of polymer main chain, the conformational effect of polymer main chain, and multi-site interaction. Macroscopic assemblies have been also realized based on molecular recognition using polyacrylamide-based gels possessing CD and guest residues.

  16. Gesture recognition on smart cameras

    NASA Astrophysics Data System (ADS)

    Dziri, Aziz; Chevobbe, Stephane; Darouich, Mehdi

    2013-02-01

    Gesture recognition is a feature in human-machine interaction that allows more natural interaction without the use of complex devices. For this reason, several methods of gesture recognition have been developed in recent years. However, most real time methods are designed to operate on a Personal Computer with high computing resources and memory. In this paper, we analyze relevant methods found in the literature in order to investigate the ability of smart camera to execute gesture recognition algorithms. We elaborate two hand gesture recognition pipelines. The first method is based on invariant moments extraction and the second on finger tips detection. The hand detection method used for both pipeline is based on skin color segmentation. The results obtained show that the un-optimized versions of invariant moments method and finger tips detection method can reach 10 fps on embedded processor and use about 200 kB of memory.

  17. Face recognition based tensor structure

    NASA Astrophysics Data System (ADS)

    Yang, De-qiang; Ye, Zhi-xia; Zhao, Yang; Liu, Li-mei

    2012-01-01

    Face recognition has broad applications, and it is a difficult problem since face image can change with photographic conditions, such as different illumination conditions, pose changes and camera angles. How to obtain some invariable features for a face image is the key issue for a face recognition algorithm. In this paper, a novel tensor structure of face image is proposed to represent image features with eight directions for a pixel value. The invariable feature of the face image is then obtained from gradient decomposition to make up the tensor structure. Then the singular value decomposition (SVD) and principal component analysis (PCA) of this tensor structure are used for face recognition. The experimental results from this study show that many difficultly recognized samples can correctly be recognized, and the recognition rate is increased by 9%-11% in comparison with same type of algorithms.

  18. Processing orientation and emotion recognition.

    PubMed

    Martin, Douglas; Slessor, Gillian; Allen, Roy; Phillips, Louise H; Darling, Stephen

    2012-02-01

    There is evidence that some emotional expressions are characterized by diagnostic cues from individual face features. For example, an upturned mouth is indicative of happiness, whereas a furrowed brow is associated with anger. The current investigation explored whether motivating people to perceive stimuli in a local (i.e., feature-based) rather than global (i.e., holistic) processing orientation was advantageous for recognizing emotional facial expressions. Participants classified emotional faces while primed with local and global processing orientations, via a Navon letter task. Contrary to previous findings for identity recognition, the current findings are indicative of a modest advantage for face emotion recognition under conditions of local processing orientation. When primed with a local processing orientation, participants performed both significantly faster and more accurately on an emotion recognition task than when they were primed with a global processing orientation. The impacts of this finding for theories of emotion recognition and face processing are considered. PMID:21842989

  19. The neuroecology of competitor recognition.

    PubMed

    Grether, Gregory F

    2011-11-01

    Territorial animals can be expected to distinguish among the types of competitors and noncompetitors that they encounter on a regular basis, including prospective mates and rivals of their own species, but they may not correctly classify individuals of other species. Closely related species often have similar phenotypes and this can cause confusion when formerly allopatric populations first come into contact. Errors in recognizing competitors can have important ecological and evolutionary effects. I review what is known about the mechanisms of competitor recognition in animals generally, focusing on cases in which the targets of recognition include other species. Case studies include damselflies, ants, skinks, salamanders, reef fishes, and birds. In general, recognition systems consist of a phenotypic cue (e.g., chemical, color, song), a neural template against which cues are compared, a motor response (e.g., aggression), and sensory integration circuits for context dependency of the response (if any). Little is known about how competitor recognition systems work at the neural level, but inferences about specificity of cues and about sensory integration can be drawn from the responses of territory residents to simulated intruders. Competitor recognition often involves multiple cues in the same, or different, sensory modalities. The same cues and templates are often, but not always, used for intraspecific and interspecific recognition. Experiments have shown that imprinting on local cues is common, which may enable templates to track evolved changes in cues automatically. The dependence of aggression and tolerance on context is important even in the simplest systems. Species in which mechanisms of competitor recognition are best known offer untapped opportunities to examine how competitor-recognition systems evolve (e.g., by comparing allopatric and sympatric populations). Cues that are gene products (peptides, proteins) may provide insights into rates of evolution

  20. On Tangut Historical Documents Recognition*

    NASA Astrophysics Data System (ADS)

    Liu, Changqing

    As the Tangut studies have made progress, a considerable number of Tangut historical documents' copies have been published. It is of great importance to carry out digitalization and domestication of these copies. The paper firstly makes an initial processing of images by global threshold, then dissect the photocopies by scanning. Finally adopts the recognition approach of principal component analysis. The experiment shows that a better recognition can be achieved by calculation without extra time.

  1. Holistic processing predicts face recognition.

    PubMed

    Richler, Jennifer J; Cheung, Olivia S; Gauthier, Isabel

    2011-04-01

    The concept of holistic processing is a cornerstone of face-recognition research. In the study reported here, we demonstrated that holistic processing predicts face-recognition abilities on the Cambridge Face Memory Test and on a perceptual face-identification task. Our findings validate a large body of work that relies on the assumption that holistic processing is related to face recognition. These findings also reconcile the study of face recognition with the perceptual-expertise work it inspired; such work links holistic processing of objects with people's ability to individuate them. Our results differ from those of a recent study showing no link between holistic processing and face recognition. This discrepancy can be attributed to the use in prior research of a popular but flawed measure of holistic processing. Our findings salvage the central role of holistic processing in face recognition and cast doubt on a subset of the face-perception literature that relies on a problematic measure of holistic processing.

  2. Document Form and Character Recognition using SVM

    NASA Astrophysics Data System (ADS)

    Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

    2009-08-01

    Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

  3. Bidirectional Modulation of Recognition Memory

    PubMed Central

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

    2015-01-01

    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

  4. Cognitive object recognition system (CORS)

    NASA Astrophysics Data System (ADS)

    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.

  5. An audiovisual emotion recognition system

    NASA Astrophysics Data System (ADS)

    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.

  6. Asymmetric Reinstatement Effects in Recognition.

    PubMed

    Shahabuddin, Shaan S; Smith, Steven M

    2016-01-01

    Our experiment examined two questions: (1) Does reinstating a studied context affect recognition of an associated word, and (2) Does reinstating a studied word affect recognition of an associated context? After encoding 75 words, each of which was shown superimposed over a different 5-sec video of an environment (e.g., a playground, a traffic scene, or a grocery store), participants were asked to recognize 50 of the words and 50 of the video scenes. On the test, half of the studied words were shown superimposed over the same video contexts that had been present at encoding, and half were shown over new scenes. Similarly, videos were presented with either old or new words. Context reinstatement increased hits and reduced false alarms for words, but word reinstatement did not affect recognition of video contexts. The results suggest that the associations that bind word events with their contexts may not be bidirectional. PMID:27649359

  7. Palmprint Recognition across Different Devices

    PubMed Central

    Jia, Wei; Hu, Rong-Xiang; Gui, Jie; Zhao, Yang; Ren, Xiao-Ming

    2012-01-01

    In this paper, the problem of Palmprint Recognition Across Different Devices (PRADD) is investigated, which has not been well studied so far. Since there is no publicly available PRADD image database, we created a non-contact PRADD image database containing 12,000 grayscale captured from 100 subjects using three devices, i.e., one digital camera and two smart-phones. Due to the non-contact image acquisition used, rotation and scale changes between different images captured from a same palm are inevitable. We propose a robust method to calculate the palm width, which can be effectively used for scale normalization of palmprints. On this PRADD image database, we evaluate the recognition performance of three different methods, i.e., subspace learning method, correlation method, and orientation coding based method, respectively. Experiments results show that orientation coding based methods achieved promising recognition performance for PRADD. PMID:22969380

  8. DNA recognition by synthetic constructs.

    PubMed

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

    2011-09-01

    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.

  9. Emotion-independent face recognition

    NASA Astrophysics Data System (ADS)

    De Silva, Liyanage C.; Esther, Kho G. P.

    2000-12-01

    Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

  10. Mandarin recognition over the telephone

    NASA Astrophysics Data System (ADS)

    Kao, Yuhung

    1996-06-01

    Mandarin Chinese is the official language in China and Taiwan, it is the native language of a quarter of the world population. As the services enabled by speech recognition technology (e.g. telephone voice dialing, information query) become more popular in English, we would like to extend this capability to other languages. Mandarin is one of the major languages under research in our laboratory. This paper describes how we extend our work in English speech recognition into Mandarin. We will described the corpus: Voice Across Taiwan, the training of a complete set of Mandarin syllable models, preliminary performance results and error analysis. A fast prototyping system was built, where a user can write any context free grammar with no restriction of vocabulary, then the grammar can be compiled into recognition models. It enables user to quickly test the performance of a new vocabulary.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Group collaboration in recognition memory.

    PubMed

    Clark, S E; Hori, A; Putnam, A; Martin, T P

    2000-11-01

    Group collaboration was examined in item and associative recognition. The present study distinguishes between group effects versus collaborative processes and defines the latter as interactive information exchange among group members. By that definition, many group effects do not involve collaboration. For example, group performance can exceed individual performance by pooling the increased resources of the group. Specifically, a group advantage can be obtained by deferring to a majority vote or to the group's best member. For both item and associative recognition, a group advantage was obtained that could not be accounted for by resource pooling. Collaborative facilitation was shown reliably in recognizing targets but not for rejecting distractors. PMID:11185784

  13. Emotion recognition during cocaine intoxication.

    PubMed

    Kuypers, K P C; Steenbergen, L; Theunissen, E L; Toennes, S W; Ramaekers, J G

    2015-11-01

    Chronic or repeated cocaine use has been linked to impairments in social skills. It is not clear whether cocaine is responsible for this impairment or whether other factors, like polydrug use, distort the observed relation. We aimed to investigate this relation by means of a placebo-controlled experimental study. Additionally, associations between stressor-related activity (cortisol, cardiovascular parameters) induced by the biological stressor cocaine, and potential cocaine effects on emotion recognition were studied. Twenty-four healthy recreational cocaine users participated in this placebo-controlled within-subject study. Participants were tested between 1 and 2 h after treatment with oral cocaine (300 mg) or placebo. Emotion recognition of low and high intensity expressions of basic emotions (fear, anger, disgust, sadness, and happiness) was tested. Findings show that cocaine impaired recognition of negative emotions; this was mediated by the intensity of the presented emotions. When high intensity expressions of Anger and Disgust were shown, performance under influence of cocaine 'normalized' to placebo-like levels while it made identification of Sadness more difficult. The normalization of performance was most notable for participants with the largest cortisol responses in the cocaine condition compared to placebo. It was demonstrated that cocaine impairs recognition of negative emotions, depending on the intensity of emotion expression and cortisol response. PMID:26328908

  14. The Army word recognition system

    NASA Technical Reports Server (NTRS)

    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.

  15. Low-resolution gait recognition.

    PubMed

    Zhang, Junping; Pu, Jian; Chen, Changyou; Fleischer, Rudolf

    2010-08-01

    Unlike other biometric authentication methods, gait recognition is noninvasive and effective from a distance. However, the performance of gait recognition will suffer in the low-resolution (LR) case. Furthermore, when gait sequences are projected onto a nonoptimal low-dimensional subspace to reduce the data complexity, the performance of gait recognition will also decline. To deal with these two issues, we propose a new algorithm called superresolution with manifold sampling and backprojection (SRMS), which learns the high-resolution (HR) counterparts of LR test images from a collection of HR/LR training gait image patch pairs. Then, we incorporate SRMS into a new algorithm called multilinear tensor-based learning without tuning parameters (MTP) for LR gait recognition. Our contributions include the following: 1) With manifold sampling, the redundancy of gait image patches is remarkably decreased; thus, the superresolution procedure is more efficient and reasonable. 2) Backprojection guarantees that the learned HR gait images and the corresponding LR gait images can be more consistent. 3) The optimal subspace dimension for dimension reduction is automatically determined without introducing extra parameters. 4) Theoretical analysis of the algorithm shows that MTP converges. Experiments on the USF human gait database and the CASIA gait database show the increased efficiency of the proposed algorithm, compared with previous algorithms. PMID:20199936

  16. Enduring voice recognition in bonobos.

    PubMed

    Keenan, Sumir; Mathevon, Nicolas; Stevens, Jeroen M G; Guéry, Jean Pascal; Zuberbühler, Klaus; Levréro, Florence

    2016-01-01

    Long-term social recognition is vital for species with complex social networks, where familiar individuals can encounter one another after long periods of separation. For non-human primates who live in dense forest environments, visual access to one another is often limited, and recognition of social partners over distances largely depends on vocal communication. Vocal recognition after years of separation has never been reported in any great ape species, despite their complex societies and advanced social intelligence. Here we show that bonobos, Pan paniscus, demonstrate reliable vocal recognition of social partners, even if they have been separated for five years. We experimentally tested bonobos' responses to the calls of previous group members that had been transferred between captive groups. Despite long separations, subjects responded more intensely to familiar voices than to calls from unknown individuals - the first experimental evidence that bonobos can identify individuals utilising vocalisations even years after their last encounter. Our study also suggests that bonobos may cease to discriminate between familiar and unfamiliar individuals after a period of eight years, indicating that voice representations or interest could be limited in time in this species. PMID:26911199

  17. Output Interference in Recognition Memory

    ERIC Educational Resources Information Center

    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…

  18. Enduring voice recognition in bonobos

    PubMed Central

    Keenan, Sumir; Mathevon, Nicolas; Stevens, Jeroen MG; Guéry, Jean Pascal; Zuberbühler, Klaus; Levréro, Florence

    2016-01-01

    Long-term social recognition is vital for species with complex social networks, where familiar individuals can encounter one another after long periods of separation. For non-human primates who live in dense forest environments, visual access to one another is often limited, and recognition of social partners over distances largely depends on vocal communication. Vocal recognition after years of separation has never been reported in any great ape species, despite their complex societies and advanced social intelligence. Here we show that bonobos, Pan paniscus, demonstrate reliable vocal recognition of social partners, even if they have been separated for five years. We experimentally tested bonobos’ responses to the calls of previous group members that had been transferred between captive groups. Despite long separations, subjects responded more intensely to familiar voices than to calls from unknown individuals - the first experimental evidence that bonobos can identify individuals utilising vocalisations even years after their last encounter. Our study also suggests that bonobos may cease to discriminate between familiar and unfamiliar individuals after a period of eight years, indicating that voice representations or interest could be limited in time in this species. PMID:26911199

  19. Emotion recognition during cocaine intoxication.

    PubMed

    Kuypers, K P C; Steenbergen, L; Theunissen, E L; Toennes, S W; Ramaekers, J G

    2015-11-01

    Chronic or repeated cocaine use has been linked to impairments in social skills. It is not clear whether cocaine is responsible for this impairment or whether other factors, like polydrug use, distort the observed relation. We aimed to investigate this relation by means of a placebo-controlled experimental study. Additionally, associations between stressor-related activity (cortisol, cardiovascular parameters) induced by the biological stressor cocaine, and potential cocaine effects on emotion recognition were studied. Twenty-four healthy recreational cocaine users participated in this placebo-controlled within-subject study. Participants were tested between 1 and 2 h after treatment with oral cocaine (300 mg) or placebo. Emotion recognition of low and high intensity expressions of basic emotions (fear, anger, disgust, sadness, and happiness) was tested. Findings show that cocaine impaired recognition of negative emotions; this was mediated by the intensity of the presented emotions. When high intensity expressions of Anger and Disgust were shown, performance under influence of cocaine 'normalized' to placebo-like levels while it made identification of Sadness more difficult. The normalization of performance was most notable for participants with the largest cortisol responses in the cocaine condition compared to placebo. It was demonstrated that cocaine impairs recognition of negative emotions, depending on the intensity of emotion expression and cortisol response.

  20. Face recognition for uncontrolled environments

    NASA Astrophysics Data System (ADS)

    Podilchuk, Christine; Hulbert, William; Flachsbart, Ralph; Barinov, Lev

    2010-04-01

    A new face recognition algorithm has been proposed which is robust to variations in pose, expression, illumination and occlusions such as sunglasses. The algorithm is motivated by the Edit Distance used to determine the similarity between strings of one dimensional data such as DNA and text. The key to this approach is how to extend the concept of an Edit Distance on one-dimensional data to two-dimensional image data. The algorithm is based on mapping one image into another and using the characteristics of the mapping to determine a two-dimensional Pictorial-Edit Distance or P-Edit Distance. We show how the properties of the mapping are similar to insertion, deletion and substitution errors defined in an Edit Distance. This algorithm is particularly well suited for face recognition in uncontrolled environments such as stand-off and other surveillance applications. We will describe an entire system designed for face recognition at a distance including face detection, pose estimation, multi-sample fusion of video frames and identification. Here we describe how the algorithm is used for face recognition at a distance, present some initial results and describe future research directions.(

  1. Method and System for Object Recognition Search

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

    2012-01-01

    A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

  2. Structural basis of cofactor-mediated stabilization and substrate recognition of the α-tubulin acetyltransferase αTAT1.

    PubMed

    Yuzawa, Satoru; Kamakura, Sachiko; Hayase, Junya; Sumimoto, Hideki

    2015-04-01

    The functions of microtubules are controlled in part by tubulin post-translational modification including acetylation of Lys⁴⁰ in α-tubulin. αTAT1 (α-tubulin acetyltransferase 1), an enzyme evolutionarily conserved among eukaryotes, has recently been identified as the major α-tubulin Lys⁴⁰ acetyltransferase, in which AcCoA (acetyl-CoA) serves as an acetyl group donor. The regulation and substrate recognition of this enzyme, however, have not been fully understood. In the present study, we show that AcCoA and CoA each form a stable complex with human αTAT1 to maintain the protein integrity both in vivo and in vitro. The invariant residues Arg¹³² and Ser¹⁶⁰ in αTAT1 participate in the stable interaction not only with AcCoA but also with CoA, which is supported by analysis of the present crystal structures of the αTAT1 catalytic domain in complex with CoA. Alanine substitution for Arg¹³² or Ser¹⁶⁰ leads to a drastic misfolding of the isolated αTAT1 catalytic domain in the absence of CoA and AcCoA but not in the presence of excess amounts of either cofactor. A mutant αTAT1 carrying the R132A or S160A substitution is degraded much faster than the wild-type protein when expressed in mammalian Madin-Darby canine kidney cells. Furthermore, alanine-scanning experiments using Lys⁴⁰-containing peptides reveal that α-tubulin Ser³⁸ is crucial for substrate recognition of αTAT1, whereas Asp³⁹, Ile⁴², the glycine stretch (amino acid residues 43-45) and Asp⁴⁶ are also involved. The requirement for substrate selection is totally different from that in various histone acetyltransferases, which appears to be consistent with the inability of αTAT1 to acetylate histones.

  3. A propositional theory of recognition memory.

    PubMed

    Anderson, J R; Bower, G H

    1974-05-01

    This paper modifies the Anderson and Bower (1972) theory of recognition memory for words. A propositional representation is outlined for the contextual information underlying word recognition. Logical arguments are offered for preferring this representation over the undifferentiated associative representation used earlier. The propositional representation is used to interpret effects of verbal context upon recognition memory. The implications of these context effects are considered for two-process models of recall and recognition. PMID:21274765

  4. 77 FR 9590 - Recognition and Accreditation

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-17

    ...; ] DEPARTMENT OF JUSTICE 8 CFR Part 1292 RIN 1125-AA72 Recognition and Accreditation AGENCY: Executive Office... the recognition of organizations and accreditation of representatives who appear before EOIR. EOIR... discuss these regulations. The first meeting will be limited to a discussion of the recognition...

  5. Lateralized processes in face recognition.

    PubMed

    Rhodes, G

    1985-05-01

    In this paper a model is presented in which face recognition is analysed into several stages, each of which may be independently lateralized. Evidence is reviewed which suggests that lateralization is important at all stages of processing a face. Early visuospatial processing, and the creation and comparison of facial representations, appear to be carried out more efficiently by the right hemisphere. Comparisons based on discrete, namable features of faces may yield a left hemisphere advantage. It is also proposed that faces may activate semantic information, including names, more efficiently in the left hemisphere. The model is useful in resolving inconsistencies in the degree and direction of asymmetries found in face-recognition tasks. Suggestions are also made for future research.

  6. Molecular Recognition and Ligand Association

    NASA Astrophysics Data System (ADS)

    Baron, Riccardo; McCammon, J. Andrew

    2013-04-01

    We review recent developments in our understanding of molecular recognition and ligand association, focusing on two major viewpoints: (a) studies that highlight new physical insight into the molecular recognition process and the driving forces determining thermodynamic signatures of binding and (b) recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational ensembles comprising multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of ensemble-averaged experimental observables. Physics-based approaches are increasingly expanding their power in pharmacology applications.

  7. Turbo Processing for Speech Recognition.

    PubMed

    Moon, Todd K; Gunther, Jacob H; Broadus, Cortnie; Hou, Wendy; Nelson, Nils

    2014-01-01

    Speech recognition is a classic example of a human/machine interface, typifying many of the difficulties and opportunities of human/machine interaction. In this paper, speech recognition is used as an example of applying turbo processing principles to the general problem of human/machine interface. Speech recognizers frequently involve a model representing phonemic information at a local level, followed by a language model representing information at a nonlocal level. This structure is analogous to the local (e.g., equalizer) and nonlocal (e.g., error correction decoding) elements common in digital communications. Drawing from the analogy of turbo processing for digital communications, turbo speech processing iteratively feeds back the output of the language model to be used as prior probabilities for the phonemic model. This analogy is developed here, and the performance of this turbo model is characterized by using an artificial language model. Using turbo processing, the relative error rate improves significantly, especially in high-noise settings.

  8. Immune recognition of citrullinated epitopes.

    PubMed

    Nguyen, Hai; James, Eddie A

    2016-10-01

    Conversion of arginine into citrulline is a post-translational modification that is observed in normal physiological processes. However, abnormal citrullination can provoke autoimmunity by generating altered self-epitopes that are specifically targeted by autoantibodies and T cells. In this review we discuss the recognition of citrullinated antigens in human autoimmune diseases and the role that this modification plays in increasing antigenic diversity and circumventing tolerance mechanisms. Early published work demonstrated that citrullinated proteins are specifically targeted by autoantibodies in rheumatoid arthritis and that citrullinated peptides are more readily presented to T cells by arthritis-susceptible HLA class II 'shared epitope' proteins. Emerging data support the relevance of citrullinated epitopes in other autoimmune diseases, including type 1 diabetes and multiple sclerosis, whose susceptible HLA haplotypes also preferentially present citrullinated peptides. In these settings, autoimmune patients have been shown to have elevated responses to citrullinated epitopes derived from tissue-specific antigens. Contrasting evidence implicates autophagy or perforin and complement-mediated membrane attack as inducers of ectopic citrullination. In either case, the peptidyl deiminases responsible for citrullination are activated in response to inflammation or insult, providing a mechanistic link between this post-translational modification and interactions with the environment and infection. As such, it is likely that immune recognition of citrullinated epitopes also plays a role in pathogen clearance. Indeed, our recent data suggest that responses to citrullinated peptides facilitate recognition of novel influenza strains. Therefore, increased understanding of responses to citrullinated epitopes may provide important insights about the initiation of autoimmunity and recognition of heterologous viruses. PMID:27531825

  9. Immune recognition of protein antigens

    SciTech Connect

    Laver, W.G.; Air, G.M.

    1985-01-01

    This book contains 33 papers. Some of the titles are: Antigenic Structure of Influenze Virus Hemagglutinin; Germ-line and Somatic Diversity in the Antibody Response to the Influenza Virus A/PR/8/34 Hemagglutinin; Recognition of Cloned Influenza A Virus Gene Products by Cytotoxic T Lymphocytes; Antigenic Structure of the Influenza Virus N2 Neuraminidase; and The Molecular and Genetic Basis of Antigenic Variation in Gonococcal Pillin.

  10. Image processing for drawing recognition

    NASA Astrophysics Data System (ADS)

    Feyzkhanov, Rustem; Zhelavskaya, Irina

    2014-03-01

    The task of recognizing edges of rectangular structures is well known. Still, almost all of them work with static images and has no limit on work time. We propose application of conducting homography for the video stream which can be obtained from the webcam. We propose algorithm which can be successfully used for this kind of application. One of the main use cases of such application is recognition of drawings by person on the piece of paper before webcam.

  11. Face Recognition Incorporating Ancillary Information

    NASA Astrophysics Data System (ADS)

    Kim, Sang-Ki; Toh, Kar-Ann; Lee, Sangyoun

    2007-12-01

    Due to vast variations of extrinsic and intrinsic imaging conditions, face recognition remained to be a challenging computer vision problem even today. This is particularly true when the passive imaging approach is considered for robust applications. To advance existing recognition systems for face, numerous techniques and methods have been proposed to overcome the almost inevitable performance degradation due to external factors such as pose, expression, occlusion, and illumination. In particular, the recent part-based method has provided noticeable room for verification performance improvement based on the localized features which have good tolerance to variation of external conditions. The part-based method, however, does not really stretch the performance without incorporation of global information from the holistic method. In view of the need to fuse the local information and the global information in an adaptive manner for reliable recognition, in this paper we investigate whether such external factors can be explicitly estimated and be used to boost the verification performance during fusion of the holistic and part-based methods. Our empirical evaluations show noticeable performance improvement adopting the proposed method.

  12. Human recognition of familiar voices.

    PubMed

    Wenndt, Stanley J

    2016-08-01

    Recognizing familiar voices is something we do every day. In quiet environments, it is usually easy to recognize a familiar voice. In noisier environments, this can become a difficult task. This paper examines how robust listeners are at identifying familiar voices in noisy, changing environments and what factors may affect their recognition rates. While there is previous research addressing familiar speaker recognition, the research is limited due to the difficulty in obtaining appropriate data that eliminates speaker dependent traits, such as word choice, along with having corresponding listeners who are familiar with the speakers. The data used in this study were collected in such a fashion to mimic conversational, free-flow dialogue, but in a way to eliminate many variables such as word choice, intonation, or non-verbal cues. These data provide some of the most realistic test scenarios to-date for familiar speaker identification. A pure-tone hearing test was used to separate listeners into normal hearing and hearing impaired groups. It is hypothesized that the results of the Normal Hearing Group will be statistically better. Additionally, the aspect of familiar speaker recognition is addressed by having each listener rate his or her familiarity with each speaker. Two statistical approaches showed that the more familiar a listener is with a speaker, the more likely the listener will recognize the speaker. PMID:27586746

  13. Additive attacks on speaker recognition

    NASA Astrophysics Data System (ADS)

    Farrokh Baroughi, Alireza; Craver, Scott

    2014-02-01

    Speaker recognition is used to identify a speaker's voice from among a group of known speakers. A common method of speaker recognition is a classification based on cepstral coefficients of the speaker's voice, using a Gaussian mixture model (GMM) to model each speaker. In this paper we try to fool a speaker recognition system using additive noise such that an intruder is recognized as a target user. Our attack uses a mixture selected from a target user's GMM model, inverting the cepstral transformation to produce noise samples. In our 5 speaker data base, we achieve an attack success rate of 50% with a noise signal at 10dB SNR, and 95% by increasing noise power to 0dB SNR. The importance of this attack is its simplicity and flexibility: it can be employed in real time with no processing of an attacker's voice, and little computation is needed at the moment of detection, allowing the attack to be performed by a small portable device. For any target user, knowing that user's model or voice sample is sufficient to compute the attack signal, and it is enough that the intruder plays it while he/she is uttering to be classiffed as the victim.

  14. Fingerprint recognition using image processing

    NASA Astrophysics Data System (ADS)

    Dholay, Surekha; Mishra, Akassh A.

    2011-06-01

    Finger Print Recognition is concerned with the difficult task of matching the images of finger print of a person with the finger print present in the database efficiently. Finger print Recognition is used in forensic science which helps in finding the criminals and also used in authentication of a particular person. Since, Finger print is the only thing which is unique among the people and changes from person to person. The present paper describes finger print recognition methods using various edge detection techniques and also how to detect correct finger print using a camera images. The present paper describes the method that does not require a special device but a simple camera can be used for its processes. Hence, the describe technique can also be using in a simple camera mobile phone. The various factors affecting the process will be poor illumination, noise disturbance, viewpoint-dependence, Climate factors, and Imaging conditions. The described factor has to be considered so we have to perform various image enhancement techniques so as to increase the quality and remove noise disturbance of image. The present paper describe the technique of using contour tracking on the finger print image then using edge detection on the contour and after that matching the edges inside the contour.

  15. Visual recognition of permuted words

    NASA Astrophysics Data System (ADS)

    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.

  16. Infant Visual Attention and Object Recognition

    PubMed Central

    Reynolds, Greg D.

    2015-01-01

    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. PMID:25596333

  17. Fluency and response speed in recognition judgments.

    PubMed

    Poldrack, R A; Logan, G D

    1997-01-01

    Previous research has suggested that perceptual fluency can contribute to recognition judgments. In this study, we examined whether fluency in recognition is based upon the speed of preceding operations, as suggested by studies of perceptual fluency. Subjects studied items in both lexical decision and naming tasks, and were then tested on two blocks of lexical decision trials with probe recognition trials. Jacoby's process dissociation procedure was used, and results from this procedure suggested that recognition judgments in the task were based largely upon familiarity. However, the estimated discriminability available from response time distributions was significantly less than the observed recognition discriminability. Simulated memory operating characteristics confirmed this under determination of recognition by response times. The results demonstrate, contrary to previous suggestions, that fluency in recognition is not based upon speed.

  18. Automatic speech recognition technology development at ITT Defense Communications Division

    NASA Technical Reports Server (NTRS)

    White, George M.

    1977-01-01

    An assessment of the applications of automatic speech recognition to defense communication systems is presented. Future research efforts include investigations into the following areas: (1) dynamic programming; (2) recognition of speech degraded by noise; (3) speaker independent recognition; (4) large vocabulary recognition; (5) word spotting and continuous speech recognition; and (6) isolated word recognition.

  19. Acquired prosopagnosia without word recognition deficits.

    PubMed

    Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley

    2015-01-01

    It has long been suggested that face recognition relies on specialized mechanisms that are not involved in visual recognition of other object categories, including those that require expert, fine-grained discrimination at the exemplar level such as written words. But according to the recently proposed many-to-many theory of object recognition (MTMT), visual recognition of faces and words are carried out by common mechanisms [Behrmann, M., & Plaut, D. C. ( 2013 ). Distributed circuits, not circumscribed centers, mediate visual recognition. Trends in Cognitive Sciences, 17, 210-219]. MTMT acknowledges that face and word recognition are lateralized, but posits that the mechanisms that predominantly carry out face recognition still contribute to word recognition and vice versa. MTMT makes a key prediction, namely that acquired prosopagnosics should exhibit some measure of word recognition deficits. We tested this prediction by assessing written word recognition in five acquired prosopagnosic patients. Four patients had lesions limited to the right hemisphere while one had bilateral lesions with more pronounced lesions in the right hemisphere. The patients completed a total of seven word recognition tasks: two lexical decision tasks and five reading aloud tasks totalling more than 1200 trials. The performances of the four older patients (3 female, age range 50-64 years) were compared to those of 12 older controls (8 female, age range 56-66 years), while the performances of the younger prosopagnosic (male, 31 years) were compared to those of 14 younger controls (9 female, age range 20-33 years). We analysed all results at the single-patient level using Crawford's t-test. Across seven tasks, four prosopagnosics performed as quickly and accurately as controls. Our results demonstrate that acquired prosopagnosia can exist without word recognition deficits. These findings are inconsistent with a key prediction of MTMT. They instead support the hypothesis that face

  20. Acquired prosopagnosia without word recognition deficits.

    PubMed

    Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley

    2015-01-01

    It has long been suggested that face recognition relies on specialized mechanisms that are not involved in visual recognition of other object categories, including those that require expert, fine-grained discrimination at the exemplar level such as written words. But according to the recently proposed many-to-many theory of object recognition (MTMT), visual recognition of faces and words are carried out by common mechanisms [Behrmann, M., & Plaut, D. C. ( 2013 ). Distributed circuits, not circumscribed centers, mediate visual recognition. Trends in Cognitive Sciences, 17, 210-219]. MTMT acknowledges that face and word recognition are lateralized, but posits that the mechanisms that predominantly carry out face recognition still contribute to word recognition and vice versa. MTMT makes a key prediction, namely that acquired prosopagnosics should exhibit some measure of word recognition deficits. We tested this prediction by assessing written word recognition in five acquired prosopagnosic patients. Four patients had lesions limited to the right hemisphere while one had bilateral lesions with more pronounced lesions in the right hemisphere. The patients completed a total of seven word recognition tasks: two lexical decision tasks and five reading aloud tasks totalling more than 1200 trials. The performances of the four older patients (3 female, age range 50-64 years) were compared to those of 12 older controls (8 female, age range 56-66 years), while the performances of the younger prosopagnosic (male, 31 years) were compared to those of 14 younger controls (9 female, age range 20-33 years). We analysed all results at the single-patient level using Crawford's t-test. Across seven tasks, four prosopagnosics performed as quickly and accurately as controls. Our results demonstrate that acquired prosopagnosia can exist without word recognition deficits. These findings are inconsistent with a key prediction of MTMT. They instead support the hypothesis that face

  1. Face Processing: Models For Recognition

    NASA Astrophysics Data System (ADS)

    Turk, Matthew A.; Pentland, Alexander P.

    1990-03-01

    The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.

  2. Speech recognition technology: a critique.

    PubMed Central

    Levinson, S E

    1995-01-01

    This paper introduces the session on advanced speech recognition technology. The two papers comprising this session argue that current technology yields a performance that is only an order of magnitude in error rate away from human performance and that incremental improvements will bring us to that desired level. I argue that, to the contrary, present performance is far removed from human performance and a revolution in our thinking is required to achieve the goal. It is further asserted that to bring about the revolution more effort should be expended on basic research and less on trying to prematurely commercialize a deficient technology. PMID:7479808

  3. Handwritten digits recognition based on immune network

    NASA Astrophysics Data System (ADS)

    Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

    2011-11-01

    With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

  4. Studies of human vision recognition: some improvements

    NASA Astrophysics Data System (ADS)

    Wu, Bo-Wen; Fang, Yi-Chin; Chang, Lin-Song

    2010-01-01

    This paper proposes a new method to improve human recognition by artificial intelligence, specifically of images without the interference of high frequencies. The human eye is the most delicate optical system. Notwithstanding the dramatic progression of its structure and functions through a long evolution, the capability of visual recognition is not yet close to perfection. This paper is a study, based on the limitations of recognition by the human eye, of image recognition through the application of artificial intelligence. Those aspects which have been explored focus on human eye modeling, including aberration analysis, creative models of the human eye, human vision recognition characteristics and various mathematical models for verification. By using images consisting of four black and white bands and modulation transfer function (MTF) curve evaluation recognition capability on all the studied models, the optimum model most compatible with the physiology of the human eye is found.

  5. Speech recognition with amplitude and frequency modulations

    NASA Astrophysics Data System (ADS)

    Zeng, Fan-Gang; Nie, Kaibao; Stickney, Ginger S.; Kong, Ying-Yee; Vongphoe, Michael; Bhargave, Ashish; Wei, Chaogang; Cao, Keli

    2005-02-01

    Amplitude modulation (AM) and frequency modulation (FM) are commonly used in communication, but their relative contributions to speech recognition have not been fully explored. To bridge this gap, we derived slowly varying AM and FM from speech sounds and conducted listening tests using stimuli with different modulations in normal-hearing and cochlear-implant subjects. We found that although AM from a limited number of spectral bands may be sufficient for speech recognition in quiet, FM significantly enhances speech recognition in noise, as well as speaker and tone recognition. Additional speech reception threshold measures revealed that FM is particularly critical for speech recognition with a competing voice and is independent of spectral resolution and similarity. These results suggest that AM and FM provide independent yet complementary contributions to support robust speech recognition under realistic listening situations. Encoding FM may improve auditory scene analysis, cochlear-implant, and audiocoding performance. auditory analysis | cochlear implant | neural code | phase | scene analysis

  6. Document recognition serving people with disabilities

    NASA Astrophysics Data System (ADS)

    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.

  7. Encoding and reinstatement of threat: recognition potentials.

    PubMed

    Weymar, Mathias; Bradley, Margaret M; Hamm, Alfons O; Lang, Peter J

    2014-01-01

    On a recognition test, stimuli originally encoded in the context of shock threat show an enhanced late parietal positivity during later recognition compared to stimuli encoded during safety, particularly for emotionally arousing stimuli. The present study investigated whether this ERP old/new effect is further influenced when a threat context is reinstated during the recognition test. ERPs were measured in a yes-no recognition test for words rated high or low in emotional arousal that were encoded and recognized in the context of cues that signaled threat of shock or safety. Correct recognition of words encoded under threat, irrespective of reinstatement, was associated with an enhanced old-new ERP difference (500-700ms; centro-parietal), and this difference was only reliable for emotionally arousing words. Taken together, the data suggest that information processed in a stressful context are associated with better recollection on later recognition, an effect that was not modulated by reinstating the stressful context at retrieval.

  8. Familiar people recognition disorders: an introductory review.

    PubMed

    Gainotti, Guido

    2014-01-01

    The aim of this introduction is to provide a general background for the individual contributions dealing with different aspects of familiar people recognition disorders. Following are the main points considered in this survey: 1) the cognitive models proposed to explain the functional architecture of processes subsuming familiar people recognition; 2) the different roles of the right and left hemisphere in identifying people by face voice and name; 3) the anatomical structures and the cognitive processes involved in face and voice recognition; 4) the interactions that exist among the perceptual processes subsuming face and voice recognition, but not people's faces, voices and proper names; 5) the patterns of multimodal defects of familiar people recognition and their implications for current cognitive models. Finally, there is a short discussion of two models advanced to explain the role of the anterior temporal lobes in people recognition.

  9. Automated leukocyte recognition using fuzzy divergence.

    PubMed

    Ghosh, Madhumala; Das, Devkumar; Chakraborty, Chandan; Ray, Ajoy K

    2010-10-01

    This paper aims at introducing an automated approach to leukocyte recognition using fuzzy divergence and modified thresholding techniques. The recognition is done through the segmentation of nuclei where Gamma, Gaussian and Cauchy type of fuzzy membership functions are studied for the image pixels. It is in fact found that Cauchy leads better segmentation as compared to others. In addition, image thresholding is modified for better recognition. Results are studied and discussed.

  10. Ordinal measures for iris recognition.

    PubMed

    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. PMID:19834142

  11. Sonority contours in word recognition

    NASA Astrophysics Data System (ADS)

    McLennan, Sean

    2003-04-01

    Contrary to the Generativist distinction between competence and performance which asserts that speech or perception errors are due to random, nonlinguistic factors, it seems likely that errors are principled and possibly governed by some of the same constraints as language. A preliminary investigation of errors modeled after the child's ``Chain Whisper'' game (a degraded stimulus task) suggests that a significant number of recognition errors can be characterized as an improvement in syllable sonority contour towards the linguistically least-marked, voiceless-stop-plus-vowel syllable. An independent study of sonority contours showed that approximately half of the English lexicon can be uniquely identified by their contour alone. Additionally, ``sororities'' (groups of words that share a single sonority contour), surprisingly, show no correlation to familiarity or frequency in either size or membership. Together these results imply that sonority contours may be an important factor in word recognition and in defining word ``neighborhoods.'' Moreover, they suggest that linguistic markedness constraints may be more prevalent in performance-related phenomena than previously accepted.

  12. Longitudinal study of fingerprint recognition

    PubMed Central

    Yoon, Soweon; Jain, Anil K.

    2015-01-01

    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. PMID:26124106

  13. Innate Immune Recognition of EBV.

    PubMed

    Lünemann, Anna; Rowe, Martin; Nadal, David

    2015-01-01

    The ability of Epstein-Barr virus (EBV) to establish latency despite specific immune responses and to successfully persist lifelong in the human host shows that EBV has developed powerful strategies and mechanisms to exploit, evade, abolish, or downsize otherwise effective immune responses to ensure its own survival. This chapter focuses on current knowledge on innate immune responses against EBV and its evasion strategies for own benefit and summarizes the questions that remain to be tackled. Innate immune reactions against EBV originate both from the main target cells of EBV and from nontarget cells, which are elements of the innate immune system. Thus, we structured our review accordingly but with a particular focus on the innate recognition of EBV in its two stages in its life cycle, latent state and lytic replication. Specifically, we discuss (I) innate sensing and resulting innate immune responses against EBV by its main target cells, focusing on (i) EBV transmission between epithelial cells and B cells and their life cycle stages; and (ii) elements of innate immunity in EBV's target cells. Further, we debate (II) the innate recognition and resulting innate immune responses against EBV by cells other than the main target cells, focusing on (iii) myeloid cells: dendritic cells, monocytes, macrophages, and neutrophil granulocytes; and (iv) natural killer cells. Finally, we address (III) how EBV counteracts or exploits innate immunity in its latent and lytic life cycle stages, concentrating on (v) TLRs; (vi) EBERs; and (vii) microRNAs. PMID:26428378

  14. Dynamic chemistry of anion recognition

    SciTech Connect

    Custelcean, Radu

    2012-01-01

    In the past 40 years, anion recognition by synthetic receptors has grown into a rich and vibrant research topic, developing into a distinct branch of Supramolecular Chemistry. Traditional anion receptors comprise organic scaffolds functionalized with complementary binding groups that are assembled by multistep organic synthesis. Recently, a new approach to anion receptors has emerged, in which the host is dynamically self-assembled in the presence of the anionic guest, via reversible bond formation between functional building units. While coordination bonds were initially employed for the self-assembly of the anion hosts, more recent studies demonstrated that reversible covalent bonds can serve the same purpose. In both cases, due to their labile connections, the molecular constituents have the ability to assemble, dissociate, and recombine continuously, thereby creating a dynamic combinatorial library (DCL) of receptors. The anionic guests, through specific molecular recognition, may then amplify (express) the formation of a particular structure among all possible combinations (real or virtual) by shifting the equilibria involved towards the most optimal receptor. This approach is not limited to solution self-assembly, but is equally applicable to crystallization, where the fittest anion-binding crystal may be selected. Finally, the pros and cons of employing dynamic combinatorial chemistry (DCC) vs molecular design for developing anion receptors, and the implications of both approaches to selective anion separations, will be discussed.

  15. Longitudinal study of fingerprint recognition.

    PubMed

    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.

  16. Toward the ultimate synthesis/recognition system.

    PubMed Central

    Furui, S

    1995-01-01

    This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems. Images Fig. 3 PMID:7479723

  17. Facial recognition at the CIA

    NASA Astrophysics Data System (ADS)

    Gragg, Susan

    1997-01-01

    Law enforcement agencies need to identify suspects as they travel around the world. Terrorists and others change all sorts of information about themselves but their faces remain the same. The first operational facial recognition system (face trace) was developed at the Central Intelligence Agency (CIA) in the late eighties. It combines image analysis technology with collateral information to create an 'electronic mug book.' Using some simple collateral information about a suspect (height, age and sex) and a photograph, the system gives users the ability to identify an unknown person with a reasonable probability. The system matches information extracted from the photographs with similar information extracted from a database of photographs of existing suspects. The technology was subsequently transferred to the Immigration and Naturalization Service (INS) for use by the Border Patrol.

  18. Opportunity recognition in complex environments

    SciTech Connect

    Pryor, L.

    1996-12-31

    An agent operating in an unpredictable world must be able to take advantage of opportunities but cannot afford to perform a detailed analysis of the effects of every nuance of the current situation on its goals if it is to respond in a timely manner. This paper describes a filtering mechanism that enables the effective recognition of opportunities. The mechanism is based on a characterization of the world in terms of reference features, features that are both cheap and functional and that appear to be prevalent in everyday life. Its use enables the plan execution system PARETO to recognize types of opportunities that other systems cannot. Reference features can also play a role in the detection of threats, and may be involved in the development of expertise.

  19. Place recognition using batlike sonar.

    PubMed

    Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

    2016-01-01

    Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map. PMID:27481189

  20. Plant pattern-recognition receptors.

    PubMed

    Zipfel, Cyril

    2014-07-01

    Plants are constantly exposed to would-be pathogens in their immediate environment. Yet, despite relying on innate immunity only, plants are resistant to most microbes. They employ pattern-recognition receptors (PRRs) for sensitive and rapid detection of the potential danger caused by microbes and pests. Plant PRRs are either surface-localized receptor kinases (RKs) or receptor-like proteins (RLPs) containing various ligand-binding ectodomains that perceive pathogen-associated molecular patterns (PAMPs) or damage-associated molecular patterns (DAMPs). In this review, I summarize our current knowledge of plant PRRs and their ligands, illustrating the multiple molecular strategies employed by plant PRRs to activate innate immune signaling to survive.

  1. Aircraft recognition and tracking device

    NASA Astrophysics Data System (ADS)

    Filis, Dimitrios P.; Renios, Christos I.

    2011-11-01

    The technology of aircraft recognition and tracking has various applications in all areas of air navigation, be they civil or military, spanning from air traffic control and regulation at civilian airports to anti-aircraft weapon handling and guidance for military purposes.1, 18 The system presented in this thesis is an alternative implementation of identifying and tracking flying objects, which benefits from the optical spectrum by using an optical camera built into a servo motor (pan-tilt unit). More specifically, through the purpose-developed software, when a target (aircraft) enters the field of view of the camera18, it is both detected and identified.5, 22 Then the servo motor, being provided with data on target position and velocity, tracks the aircraft while it is in constant communication with the camera (Fig. 1). All the features are so designed as to operate under real time conditions.

  2. Recognition of Handwriting from Electromyography

    PubMed Central

    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

  3. Task-oriented situation recognition

    NASA Astrophysics Data System (ADS)

    Bauer, Alexander; Fischer, Yvonne

    2010-04-01

    From the advances in computer vision methods for the detection, tracking and recognition of objects in video streams, new opportunities for video surveillance arise: In the future, automated video surveillance systems will be able to detect critical situations early enough to enable an operator to take preventive actions, instead of using video material merely for forensic investigations. However, problems such as limited computational resources, privacy regulations and a constant change in potential threads have to be addressed by a practical automated video surveillance system. In this paper, we show how these problems can be addressed using a task-oriented approach. The system architecture of the task-oriented video surveillance system NEST and an algorithm for the detection of abnormal behavior as part of the system are presented and illustrated for the surveillance of guests inside a video-monitored building.

  4. Place recognition using batlike sonar.

    PubMed

    Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

    2016-01-01

    Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map.

  5. Recognition of movement object collision

    NASA Astrophysics Data System (ADS)

    Chang, Hsiao Tsu; Sun, Geng-tian; Zhang, Yan

    1991-03-01

    The paper explores the collision recognition of two objects in both crisscross and revolution motions A mathematical model has been established based on the continuation theory. The objects of any shape may be regarded as being built of many 3siniplexes or their convex hulls. Therefore the collision problem of two object in motion can be reduced to the collision of two corresponding 3siinplexes on two respective objects accordingly. Thus an optimized algorithm is developed for collision avoidance which is suitable for computer control and eliminating the need for vision aid. With this algorithm computation time has been reduced significantly. This algorithm is applicable to the path planning of mobile robots And also is applicable to collision avoidance of the anthropomorphic arms grasping two complicated shaped objects. The algorithm is realized using LISP language on a VAX8350 minicomputer.

  6. Proline-rich Sequence Recognition

    PubMed Central

    Schlundt, Andreas; Sticht, Jana; Piotukh, Kirill; Kosslick, Daniela; Jahnke, Nadin; Keller, Sandro; Schuemann, Michael; Krause, Eberhard; Freund, Christian

    2009-01-01

    The tumor maintenance protein Tsg101 has recently gained much attention because of its involvement in endosomal sorting, virus release, cytokinesis, and cancerogenesis. The ubiquitin-E2-like variant (UEV) domain of the protein interacts with proline-rich sequences of target proteins that contain P(S/T)AP amino acid motifs and weakly binds to the ubiquitin moiety of proteins committed to sorting or degradation. Here we performed peptide spot analysis and phage display to refine the peptide binding specificity of the Tsg101 UEV domain. A mass spectrometric proteomics approach that combines domain-based pulldown experiments, binding site inactivation, and stable isotope labeling by amino acids in cell culture (SILAC) was then used to delineate the relative importance of the peptide and ubiquitin binding sites. Clearly “PTAP” interactions dominate target recognition, and we identified several novel binders as for example the poly(A)-binding protein 1 (PABP1), Sec24b, NFκB2, and eIF4b. For PABP1 and eIF4b the interactions were confirmed in the context of the corresponding full-length proteins in cellular lysates. Therefore, our results strongly suggest additional roles of Tsg101 in cellular regulation of mRNA translation. Regulation of Tsg101 itself by the ubiquitin ligase TAL (Tsg101-associated ligase) is most likely conferred by a single PSAP binding motif that enables the interaction with Tsg101 UEV. Together with the results from the accompanying article (Kofler, M., Schuemann, M., Merz, C., Kosslick, D., Schlundt, A., Tannert, A., Schaefer, M., Lührmann, R., Krause, E., and Freund, C. (2009) Proline-rich sequence recognition: I. Marking GYF and WW domain assembly sites in early spliceosomal complexes. Mol. Cell. Proteomics 8, 2461–2473) on GYF and WW domain pathways our work defines major proline-rich sequence-mediated interaction networks that contribute to the modular assembly of physiologically relevant protein complexes. PMID:19542561

  7. Neural mechanisms for voice recognition.

    PubMed

    Andics, Attila; McQueen, James M; Petersson, Karl Magnus; Gál, Viktor; Rudas, Gábor; Vidnyánszky, Zoltán

    2010-10-01

    We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The pre-defined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training histories on different tests. Cortical sensitivity to voice similarity appeared over different time-scales and at different representational stages. First, there were short-term adaptation effects: increasing acoustic similarity to the directly preceding stimulus led to haemodynamic response reduction in the middle/posterior STS and in right ventrolateral prefrontal regions. Second, there were longer-term effects: response reduction was found in the orbital/insular cortex for stimuli that were most versus least similar to the acoustic mean of all preceding stimuli, and, in the anterior temporal pole, the deep posterior STS and the amygdala, for stimuli that were most versus least similar to the trained voice-identity category mean. These findings are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values. The analyses also reveal anatomically separable voice representations: one in a voice-acoustics space and one in a voice-identity space. Voice-identity representations flexibly followed the trained identity shift, and listeners with a greater identity effect were more accurate at recognizing familiar voices. Voice recognition is thus supported by neural voice spaces that are organized around flexible 'mean voice' representations. PMID:20553895

  8. Cortical dynamics of word recognition.

    PubMed

    Mainy, Nelly; Jung, Julien; Baciu, Monica; Kahane, Philippe; Schoendorff, Benjamin; Minotti, Lorella; Hoffmann, Dominique; Bertrand, Olivier; Lachaux, Jean-Philippe

    2008-11-01

    While functional neuroimaging studies have helped elucidate major regions implicated in word recognition, much less is known about the dynamics of the associated activations or the actual neural processes of their functional network. We used intracerebral electroencephalography recordings in 10 patients with epilepsy to directly measure neural activity in the temporal and frontal lobes during written words' recognition, predominantly in the left hemisphere. The patients were presented visually with consonant strings, pseudo-words, and words and performed a hierarchical paradigm contrasting semantic processes (living vs. nonliving word categorization task), phonological processes (rhyme decision task on pseudo-words), and visual processes (visual analysis of consonant strings). Stimuli triggered a cascade of modulations in the gamma-band (>40 Hz) with reproducible timing and task-sensitivity throughout the functional reading network: the earliest gamma-band activations were observed for all stimuli in the mesial basal temporal lobe at 150 ms, reaching the word form area in the mid fusiform gyrus at 200 ms, evidencing a superiority effect for word-like stimuli. Peaks of gamma-band activations were then observed for word-like stimuli after 400 ms in the anterior and middle portion of the superior temporal gyrus (BA 38 and BA 22 respectively), in the pars triangularis of Broca's area for the semantic task (BAs 45 and 47), and in the pars opercularis for the phonological task (BA 44). Concurrently, we observed a two-pronged effect in the prefrontal cortex (BAs 9 and 46), with nonspecific sustained dorsal activation related to sustained attention and, more ventrally, a strong reflex deactivation around 500 ms, possibly due to semantic working memory reset. PMID:17712785

  9. The Commission on Magnet® Recognition.

    PubMed

    Moran, Janice W

    2016-09-01

    The American Nurses Credentialing Center (ANCC) Commission on Magnet® Recognition is a voluntary governing body that oversees the Magnet Recognition Program®. Commission members are appointed by the ANCC Board of Directors and are expert representatives from various sectors of the nursing community. In addition, 1 commission member represents public consumers. PMID:27556648

  10. Sign and Word Recognition: A First Comparison.

    ERIC Educational Resources Information Center

    Grosjean, Francois

    1981-01-01

    The results of a word recognition study are compared to those of a sign recognition study in order to determine which aspects of lexical access are comparable in speech and sign, and which are specific to each of the two language modalities. The "gating paradigm" was used in both studies. (Author/AMH)

  11. Adult Word Recognition and Visual Sequential Memory

    ERIC Educational Resources Information Center

    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…

  12. Performing speech recognition research with hypercard

    NASA Technical Reports Server (NTRS)

    Shepherd, Chip

    1993-01-01

    The purpose of this paper is to describe a HyperCard-based system for performing speech recognition research and to instruct Human Factors professionals on how to use the system to obtain detailed data about the user interface of a prototype speech recognition application.

  13. Voice Recognition: A New Assessment Tool?

    ERIC Educational Resources Information Center

    Jones, Darla

    2005-01-01

    This article presents the results of a study conducted in Anchorage, Alaska, that evaluated the accuracy and efficiency of using voice recognition (VR) technology to collect oral reading fluency data for classroom-based assessments. The primary research question was as follows: Is voice recognition technology a valid and reliable alternative to…

  14. The Status of Voice Recognition Technology.

    ERIC Educational Resources Information Center

    Miller, Ruth

    1986-01-01

    After examining the historical view of voice recognition, voice recognition technology today, the future of this technology, and information processing applications, the author states that educators must begin to prepare for tomorrow's technology now by researching current literature, analyzing hardware and software needs, and emphasizing oral…

  15. Short-Term Recognition Memory in Children

    ERIC Educational Resources Information Center

    Calfee, Robert C.

    1970-01-01

    A series of studies indicated that performance on serial recognition memory tasks was relatively constant over a wide range of age and IQ, and except for response biases and forgetting rate, recognition memory processes of normal and retarded children appeared to be identical with those of adults. (Author/DR)

  16. Sources of Interference in Recognition Testing

    ERIC Educational Resources Information Center

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

    2013-01-01

    Recognition memory accuracy is harmed by prior testing (a.k.a., output interference [OI]; Tulving & Arbuckle, 1966). In several experiments, we interpolated various tasks between recognition test trials. The stimuli and the tasks were more similar (lexical decision [LD] of words and nonwords) or less similar (gender identification of male and…

  17. Object Recognition Memory and the Rodent Hippocampus

    ERIC Educational Resources Information Center

    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…

  18. Discovery and Recognition of the Artistically Talented.

    ERIC Educational Resources Information Center

    Wenner, Gene C.

    1985-01-01

    The National Foundation for the Advancement of the Arts, a program designed to provide national recognition and support for artistically talented youth, sponsors the Arts Recognition and Talent Search Program (ARTS). ARTS addresses areas of theater, visual arts, writing, dance, and music. The judging process is described. (Author/CL)

  19. Rapid Naming Speed and Chinese Character Recognition

    ERIC Educational Resources Information Center

    Liao, Chen-Huei; Georgiou, George K.; Parrila, Rauno

    2008-01-01

    We examined the relationship between rapid naming speed (RAN) and Chinese character recognition accuracy and fluency. Sixty-three grade 2 and 54 grade 4 Taiwanese children were administered four RAN tasks (colors, digits, Zhu-Yin-Fu-Hao, characters), and two character recognition tasks. RAN tasks accounted for more reading variance in grade 4 than…

  20. Robotic CCD microscope for enhanced crystal recognition

    DOEpatents

    Segelke, Brent W.; Toppani, Dominique

    2007-11-06

    A robotic CCD microscope and procedures to automate crystal recognition. The robotic CCD microscope and procedures enables more accurate crystal recognition, leading to fewer false negative and fewer false positives, and enable detection of smaller crystals compared to other methods available today.

  1. Sleep Enhances Explicit Recollection in Recognition Memory

    ERIC Educational Resources Information Center

    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…

  2. Syllable Transposition Effects in Korean Word Recognition

    ERIC Educational Resources Information Center

    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…

  3. Articulation effects in melody recognition memory.

    PubMed

    Wee Hun Lim, Stephen; Goh, Winston D

    2013-09-01

    Various surface features-timbre, tempo, and pitch-influence melody recognition memory, but articulation format effects, if any, remain unknown. For the first time, these effects were examined. In Experiment 1, melodies that remained in the same, or appeared in a different but similar, articulation format from study to test were recognized better than were melodies that were presented in a distinct format at test. A similar articulation format adequately induced matching processes to enhance recognition. Experiment 2 revealed that melodies rated as perceptually dissimilar on the basis of the location of the articulation mismatch did not impair recognition performance, suggesting an important boundary condition for articulation format effects on memory recognition-the matching of the memory trace and recognition probe may depend more on the overall proportion, rather than the temporal location, of the mismatch. The present findings are discussed in terms of a global matching advantage hypothesis. PMID:23410265

  4. Review of chart recognition in document images

    NASA Astrophysics Data System (ADS)

    Liu, Yan; Lu, Xiaoqing; Qin, Yeyang; Tang, Zhi; Xu, Jianbo

    2013-01-01

    As an effective information transmitting way, chart is widely used to represent scientific statistics datum in books, research papers, newspapers etc. Though textual information is still the major source of data, there has been an increasing trend of introducing graphs, pictures, and figures into the information pool. Text recognition techniques for documents have been accomplished using optical character recognition (OCR) software. Chart recognition techniques as a necessary supplement of OCR for document images are still an unsolved problem due to the great subjectiveness and variety of charts styles. This paper reviews the development process of chart recognition techniques in the past decades and presents the focuses of current researches. The whole process of chart recognition is presented systematically, which mainly includes three parts: chart segmentation, chart classification, and chart Interpretation. In each part, the latest research work is introduced. In the last, the paper concludes with a summary and promising future research direction.

  5. Modal-Power-Based Haptic Motion Recognition

    NASA Astrophysics Data System (ADS)

    Kasahara, Yusuke; Shimono, Tomoyuki; Kuwahara, Hiroaki; Sato, Masataka; Ohnishi, Kouhei

    Motion recognition based on sensory information is important for providing assistance to human using robots. Several studies have been carried out on motion recognition based on image information. However, in the motion of humans contact with an object can not be evaluated precisely by image-based recognition. This is because the considering force information is very important for describing contact motion. In this paper, a modal-power-based haptic motion recognition is proposed; modal power is considered to reveal information on both position and force. Modal power is considered to be one of the defining features of human motion. A motion recognition algorithm based on linear discriminant analysis is proposed to distinguish between similar motions. Haptic information is extracted using a bilateral master-slave system. Then, the observed motion is decomposed in terms of primitive functions in a modal space. The experimental results show the effectiveness of the proposed method.

  6. Gender recognition from point-light walkers.

    PubMed

    Pollick, Frank E; Kay, Jim W; Heim, Katrin; Stringer, Rebecca

    2005-12-01

    Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal observer for gender recognition on the basis of center of moment (J. E. Cutting, D. R. Proffitt, & L. T. Kozlowski, 1978) and, with the use of anthropometric data from various populations, show optimal recognition of approximately 79% correct. Next, they perform a meta-analysis of 21 experiments examining gender recognition, obtaining accuracies of 66% correct for a side view and 71% for other views. Finally, results of the meta-analysis and the ideal observer are combined to obtain estimates of human efficiency at gender recognition of 26% for the side view and 47% for other views. PMID:16366787

  7. Practical automatic Arabic license plate recognition system

    NASA Astrophysics Data System (ADS)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

  8. Apply lightweight recognition algorithms in optical music recognition

    NASA Astrophysics Data System (ADS)

    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%.

  9. Recognition of a signal peptide by the signal recognition particle

    PubMed Central

    Janda, Claudia Y.; Li, Jade; Oubridge, Chris; Hernández, Helena; Robinson, Carol V.; Nagai, Kiyoshi

    2010-01-01

    Targeting of proteins to appropriate sub-cellular compartments is a crucial process in all living cells. Secretory and membrane proteins usually contain an N-terminal signal peptide, which is recognised by the signal recognition particle (SRP) when nascent polypeptide chains emerge from the ribosome. The SRP-ribosome nascent chain complex is then targeted through its GTP-dependent interaction with SRP-receptor to the protein-conducting channel on endoplasmic reticulum membrane in eukaryotes or plasma membrane in bacteria. A universally conserved component of SRP1, 2, SRP54 or its bacterial homolog, fifty-four homolog (Ffh), binds the signal peptides which have a highly divergent sequence divisible into a positively charged n-region, an h-region commonly containing 8-20 hydrophobic residues and a polar c-region 3-5. No structure has been reported that exemplified SRP54 binding of any signal sequence. We have produced a fusion protein between Sulfolobus solfataricus SRP54 and a signal peptide connected via a flexible linker. This fusion protein oligomerises in solution, through interaction between the SRP54 and signal peptide moieties belonging to different chains, and it is functional, able to bind SRP RNA and SRP-receptor FtsY. Here we present the crystal structure at 3.5 Å resolution of an SRP54-signal peptide complex in the dimer, which reveals how a signal sequence is recognised by SRP54. PMID:20364120

  10. The coevolution of recognition and social behavior.

    PubMed

    Smead, Rory; Forber, Patrick

    2016-01-01

    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. PMID:27225673

  11. [Face recognition in patients with schizophrenia].

    PubMed

    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.

  12. Window Size Impact in Human Activity Recognition

    PubMed Central

    Banos, Oresti; Galvez, Juan-Manuel; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

    2014-01-01

    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. PMID:24721766

  13. The coevolution of recognition and social behavior

    PubMed Central

    Smead, Rory; Forber, Patrick

    2016-01-01

    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. PMID:27225673

  14. Window size impact in human activity recognition.

    PubMed

    Banos, Oresti; Galvez, Juan-Manuel; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

    2014-01-01

    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. PMID:24721766

  15. Textual emotion recognition for enhancing enterprise computing

    NASA Astrophysics Data System (ADS)

    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.

  16. Recognition in a Social Symbiosis: Chemical Phenotypes and Nestmate Recognition Behaviors of Neotropical Parabiotic Ants

    PubMed Central

    Emery, Virginia J.; Tsutsui, Neil D.

    2013-01-01

    Social organisms rank among the most abundant and ecologically dominant species on Earth, in part due to exclusive recognition systems that allow cooperators to be distinguished from exploiters. Exploiters, such as social parasites, manipulate their hosts’ recognition systems, whereas cooperators are expected to minimize interference with their partner’s recognition abilities. Despite our wealth of knowledge about recognition in single-species social nests, less is known of the recognition systems in multi-species nests, particularly involving cooperators. One uncommon type of nesting symbiosis, called parabiosis, involves two species of ants sharing a nest and foraging trails in ostensible cooperation. Here, we investigated recognition cues (cuticular hydrocarbons) and recognition behaviors in the parabiotic mixed-species ant nests of Camponotus femoratus and Crematogaster levior in North-Eastern Amazonia. We found two sympatric, cryptic Cr. levior chemotypes in the population, with one type in each parabiotic colony. Although they share a nest, very few hydrocarbons were shared between Ca. femoratus and either Cr. levior chemotype. The Ca. femoratus hydrocarbons were also unusually long–chained branched alkenes and dienes, compounds not commonly found amongst ants. Despite minimal overlap in hydrocarbon profile, there was evidence of potential interspecific nestmate recognition –Cr. levior ants were more aggressive toward Ca. femoratus non-nestmates than Ca. femoratus nestmates. In contrast to the prediction that sharing a nest could weaken conspecific recognition, each parabiotic species also maintains its own aggressive recognition behaviors to exclude conspecific non-nestmates. This suggests that, despite cohabitation, parabiotic ants maintain their own species-specific colony odors and recognition mechanisms. It is possible that such social symbioses are enabled by the two species each using their own separate recognition cues, and that interspecific

  17. Symmetry, probability, and recognition in face space.

    PubMed

    Sirovich, Lawrence; Meytlis, Marsha

    2009-04-28

    The essential midline symmetry of human faces is shown to play a key role in facial coding and recognition. This also has deep and important connections with recent explorations of the organization of primate cortex, as well as human psychophysical experiments. Evidence is presented that the dimension of face recognition space for human faces is dramatically lower than previous estimates. One result of the present development is the construction of a probability distribution in face space that produces an interesting and realistic range of (synthetic) faces. Another is a recognition algorithm that by reasonable criteria is nearly 100% accurate.

  18. Cortical Networks for Visual Self-Recognition

    NASA Astrophysics Data System (ADS)

    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.

  19. Modelling of DNA-protein recognition

    NASA Technical Reports Server (NTRS)

    Rein, R.; Garduno, R.; Colombano, S.; Nir, S.; Haydock, K.; Macelroy, R. D.

    1980-01-01

    Computer model-building procedures using stereochemical principles together with theoretical energy calculations appear to be, at this stage, the most promising route toward the elucidation of DNA-protein binding schemes and recognition principles. A review of models and bonding principles is conducted and approaches to modeling are considered, taking into account possible di-hydrogen-bonding schemes between a peptide and a base (or a base pair) of a double-stranded nucleic acid in the major groove, aspects of computer graphic modeling, and a search for isogeometric helices. The energetics of recognition complexes is discussed and several models for peptide DNA recognition are presented.

  20. Learning curve of speech recognition.

    PubMed

    Kauppinen, Tomi A; Kaipio, Johanna; Koivikko, Mika P

    2013-12-01

    Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new users become as skilled as the experienced users. We studied SR log entries for 0.25 million reports from 154 radiologists and after careful exclusions, defined a group of 11 experienced radiologists and 71 radiologists new to SR (24,833 and 122,093 reports, respectively). Data were analyzed for sound file and report lengths, character-based error rates, and words unknown to the SR's dictionary. Experienced radiologists corrected 6 characters for each report and for new users, 11. Some users presented a very unfavorable learning curve, with error rates not declining as expected. New users' reports were longer, and data for the experienced users indicates that their reports, initially equally lengthy, shortened over a period of several years. For most radiologists, only minor corrections of dictated reports were necessary. While new users adopted SR quickly, with a subset outperforming experienced users from the start, identification of users struggling with SR will help facilitate troubleshooting and support.

  1. Distributed nestmate recognition in ants

    PubMed Central

    Esponda, Fernando; Gordon, Deborah M.

    2015-01-01

    We propose a distributed model of nestmate recognition, analogous to the one used by the vertebrate immune system, in which colony response results from the diverse reactions of many ants. The model describes how individual behaviour produces colony response to non-nestmates. No single ant knows the odour identity of the colony. Instead, colony identity is defined collectively by all the ants in the colony. Each ant responds to the odour of other ants by reference to its own unique decision boundary, which is a result of its experience of encounters with other ants. Each ant thus recognizes a particular set of chemical profiles as being those of non-nestmates. This model predicts, as experimental results have shown, that the outcome of behavioural assays is likely to be variable, that it depends on the number of ants tested, that response to non-nestmates changes over time and that it changes in response to the experience of individual ants. A distributed system allows a colony to identify non-nestmates without requiring that all individuals have the same complete information and helps to facilitate the tracking of changes in cuticular hydrocarbon profiles, because only a subset of ants must respond to provide an adequate response. PMID:25833853

  2. Recurrent Processing during Object Recognition

    PubMed Central

    O’Reilly, Randall C.; Wyatte, Dean; Herd, Seth; Mingus, Brian; Jilk, David J.

    2013-01-01

    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 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. PMID:23554596

  3. Distributed nestmate recognition in ants.

    PubMed

    Esponda, Fernando; Gordon, Deborah M

    2015-05-01

    We propose a distributed model of nestmate recognition, analogous to the one used by the vertebrate immune system, in which colony response results from the diverse reactions of many ants. The model describes how individual behaviour produces colony response to non-nestmates. No single ant knows the odour identity of the colony. Instead, colony identity is defined collectively by all the ants in the colony. Each ant responds to the odour of other ants by reference to its own unique decision boundary, which is a result of its experience of encounters with other ants. Each ant thus recognizes a particular set of chemical profiles as being those of non-nestmates. This model predicts, as experimental results have shown, that the outcome of behavioural assays is likely to be variable, that it depends on the number of ants tested, that response to non-nestmates changes over time and that it changes in response to the experience of individual ants. A distributed system allows a colony to identify non-nestmates without requiring that all individuals have the same complete information and helps to facilitate the tracking of changes in cuticular hydrocarbon profiles, because only a subset of ants must respond to provide an adequate response.

  4. Defining protein electrostatic recognition processes

    NASA Astrophysics Data System (ADS)

    Getzoff, Elizabeth D.; Roberts, Victoria A.

    The objective is to elucidate the nature of electrostatic forces controlling protein recognition processes by using a tightly coupled computational and interactive computer graphics approach. The TURNIP program was developed to determine the most favorable precollision orientations for two molecules by systematic search of all orientations and evaluation of the resulting electrostatic interactions. TURNIP was applied to the transient interaction between two electron transfer metalloproteins, plastocyanin and cytochrome c. The results suggest that the productive electron-transfer complex involves interaction of the positive region of cytochrome c with the negative patch of plastocyanin, consistent with experimental data. Application of TURNIP to the formation of the stable complex between the HyHEL-5 antibody and its protein antigen lysozyme showed that long-distance electrostatic forces guide lysozyme toward the HyHEL-5 binding site, but do not fine tune its orientation. Determination of docked antigen/antibody complexes requires including steric as well as electrostatic interactions, as was done for the U10 mutant of the anti-phosphorylcholine antibody S107. The graphics program Flex, a convenient desktop workstation program for visualizing molecular dynamics and normal mode motions, was enhanced. Flex now has a user interface and was rewritten to use standard graphics libraries, so as to run on most desktop workstations.

  5. Object recognition by active fusion

    NASA Astrophysics Data System (ADS)

    Prantl, Manfred; Kopp-Borotschnig, Hermann; Ganster, Harald; Sinclair, David; Pinz, Axel J.

    1996-10-01

    Today's computer vision applications often have to deal with multiple, uncertain, and incomplete visual information. In this paper, we apply a new method, termed 'active fusion', to the problem of generic object recognition. Active fusion provides a common framework for active selection and combination of information from multiple sources in order to arrive at a reliable result at reasonable costs. In our experimental setup we use a camera mounted on a 2m by 1.5m x/z-table observing objects placed on a rotating table. Zoom, pan, tilt, and aperture setting of the camera can be controlled by the system. We follow a part-based approach, trying to decompose objects into parts, which are modeled as geons. The active fusion system starts from an initial view of the objects placed on the table and is continuously trying to refine its current object hypotheses by requesting additional views. The implementation of active fusion on the basis of probability theory, Dempster-Shafer's theory of evidence and fuzzy set theory is discussed. First results demonstrating segmentation improvements by active fusion are presented.

  6. Viral cell recognition and entry.

    PubMed Central

    Rossmann, M. G.

    1994-01-01

    Rhinovirus infection is initiated by the recognition of a specific cell-surface receptor. The major group of rhinovirus serotypes attach to intercellular adhesion molecule-1 (ICAM-1). The attachment process initiates a series of conformational changes resulting in the loss of genomic RNA from the virion. X-ray crystallography and sequence comparisons suggested that a deep crevice or canyon is the site on the virus recognized by the cellular receptor molecule. This has now been verified by electron microscopy of human rhinovirus 14 (HRV14) and HRV16 complexed with a soluble component of ICAM-1. A hydrophobic pocket underneath the canyon is the site of binding of various hydrophobic drug compounds that can inhibit attachment and uncoating. This pocket is also associated with an unidentified, possibly cellular in origin, "pocket factor." The pocket factor binding site overlaps the binding site of the receptor. It is suggested that competition between the pocket factor and receptor regulates the conformational changes required for the initiation of the entry of the genomic RNA into the cell. PMID:7849588

  7. Place recognition using batlike sonar

    PubMed Central

    Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

    2016-01-01

    Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map. DOI: http://dx.doi.org/10.7554/eLife.14188.001 PMID:27481189

  8. Temporal regulation of kin recognition maintains recognition-cue diversity and suppresses cheating.

    PubMed

    Ho, Hsing-I; Shaulsky, Gad

    2015-05-28

    Kin recognition, the ability to distinguish kin from non-kin, can facilitate cooperation between relatives. Evolutionary theory predicts that polymorphism in recognition cues, which is essential for effective recognition, would be unstable. Individuals carrying rare recognition cues would benefit less from social interactions than individuals with common cues, leading to loss of the genetic-cue diversity. We test this evolutionary hypothesis in Dictyostelium discoideum, which forms multicellular fruiting bodies by aggregation and utilizes two polymorphic membrane proteins to facilitate preferential cooperation. Surprisingly, we find that rare recognition variants are tolerated and maintain their frequencies among incompatible majority during development. Although the rare variants are initially excluded from the aggregates, they subsequently rejoin the aggregate and produce spores. Social cheating is also refrained in late development, thus limiting the cost of chimerism. Our results suggest a potential mechanism to sustain the evolutionary stability of kin-recognition genes and to suppress cheating.

  9. Adaptive pattern recognition and neural networks

    SciTech Connect

    Pao, Yohhan.

    1989-01-01

    The application of neural-network computers to pattern-recognition tasks is discussed in an introduction for advanced students. Chapters are devoted to the nature of the pattern-recognition task, the Bayesian approach to the estimation of class membership, the fuzzy-set approach, patterns with nonnumeric feature values, learning discriminants and the generalized perceptron, recognition and recall on the basis of partial cues, associative memories, self-organizing nets, the functional-link net, fuzzy logic in the linking of symbolic and subsymbolic processing, and adaptive pattern recognition and its applications. Also included are C-language programs for (1) a generalized delta-rule net for supervised learning and (2) unsupervised learning based on the discovery of clustered structure. 183 refs.

  10. Face recognition based on fringe pattern analysis

    NASA Astrophysics Data System (ADS)

    Guo, Hong; Huang, Peisen

    2010-03-01

    Two-dimensional face-recognition techniques suffer from facial texture and illumination variations. Although 3-D techniques can overcome these limitations, the reconstruction and storage expenses of 3-D information are extremely high. We present a novel face-recognition method that directly utilizes 3-D information encoded in face fringe patterns without having to reconstruct 3-D geometry. In the proposed method, a digital video projector is employed to sequentially project three phase-shifted sinusoidal fringe patterns onto the subject's face. Meanwhile, a camera is used to capture the distorted fringe patterns from an offset angle. Afterward, the face fringe images are analyzed by the phase-shifting method and the Fourier transform method to obtain a spectral representation of the 3-D face. Finally, the eigenface algorithm is applied to the face-spectrum images to perform face recognition. Simulation and experimental results demonstrate that the proposed method achieved satisfactory recognition rates with reduced computational complexity and storage expenses.

  11. Support vector machine for automatic pain recognition

    NASA Astrophysics Data System (ADS)

    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.

  12. History of Maternal Recognition of Pregnancy.

    PubMed

    Bazer, Fuller W

    2015-01-01

    The mechanism for signaling pregnancy recognition is highly variable among species, and the signaling molecule itself varies between estrogens in pigs to chorionic gonadotrophin in primates. This chapter provides insight into the menstrual cycle of women and estrous cycles of rodents, dog, cat, pigs, sheep, rabbits, and marsupials, as well as the hormones required for pregnancy recognition. Pregnancy recognition involves specific hormones such as prolactin in rodents or interferons in ruminants and estrogens in pigs that in their own way ensure the maintenance of the corpus luteum and its secretion of progesterone which is the hormone of pregnancy. However, these pregnancy recognition signals may also modify gene expression in a cell-specific and temporal manner to ensure the growth and development of the conceptus. This chapter provides some historical aspects of the development of understanding of mechanisms for the establishment and maintenance of pregnancy in several species of mammals. PMID:26450492

  13. Speech therapy and voice recognition instrument

    NASA Technical Reports Server (NTRS)

    Cohen, J.; Babcock, M. L.

    1972-01-01

    Characteristics of electronic circuit for examining variations in vocal excitation for diagnostic purposes and in speech recognition for determiniog voice patterns and pitch changes are described. Operation of the circuit is discussed and circuit diagram is provided.

  14. Description, Recognition and Analysis of Biological Images

    SciTech Connect

    Yu Donggang; Jin, Jesse S.; Luo Suhuai; Pham, Tuan D.; Lai Wei

    2010-01-25

    Description, recognition and analysis biological images plays an important role for human to describe and understand the related biological information. The color images are separated by color reduction. A new and efficient linearization algorithm is introduced based on some criteria of difference chain code. A series of critical points is got based on the linearized lines. The series of curvature angle, linearity, maximum linearity, convexity, concavity and bend angle of linearized lines are calculated from the starting line to the end line along all smoothed contours. The useful method can be used for shape description and recognition. The analysis, decision, classification of the biological images are based on the description of morphological structures, color information and prior knowledge, which are associated each other. The efficiency of the algorithms is described based on two applications. One application is the description, recognition and analysis of color flower images. Another one is related to the dynamic description, recognition and analysis of cell-cycle images.

  15. Innate predator recognition in giant pandas.

    PubMed

    Du, Yiping; Huang, Yan; Zhang, Hemin; Li, Desheng; Yang, Bo; Wei, Ming; Zhou, Yingmin; Liu, Yang

    2012-02-01

    Innate predator recognition confers a survival advantage to prey animals. We investigate whether giant pandas exhibit innate predator recognition. We analyzed behavioral responses of 56 naive adult captive giant pandas (Ailuropoda melanoleuca), to urine from predators and non-predators and water control. Giant pandas performed more chemosensory investigation and displayed flehmen behaviors more frequently in response to predator urine compared to both non-predator urine and water control. Subjects also displayed certain defensive behaviors, as indicated by vigilance, and in certain cases, fleeing behaviors. Our results suggest that there is an innate component to predator recognition in captive giant pandas, although such recognition was only slight to moderate. These results have implications that may be applicable to the conservation and reintroduction of this endangered species. PMID:22303845

  16. Human visual pattern recognition of medical images

    NASA Astrophysics Data System (ADS)

    Biederman, Irving

    1990-07-01

    The output of most medical imaging systems is a display for interpretation by human observers. This paper provides a general summary of recent work on shape recognition by humans. Two broad modes of visual image processing executed by different cortical loci can be distinguished: a) a mode for motor interaction which is sensitive to quantitative variation in image parameters and b) a mode for basic-level object recognition which is based on a small set of qualitative contrasts in viewpoint invariant properties of images edges. Many medical image classifications pose inherently difficult problems for the recognition system in that they are based on quantitative and surface patch variations--rather than qualitative--variations. But when recognition can be achieved quickly and accurately it is possible that a small viewpoint invariant contrast has been discovered and is being exploited by the interpreter.

  17. An Efficient Gait Recognition with Backpack Removal

    NASA Astrophysics Data System (ADS)

    Lee, Heesung; Hong, Sungjun; Kim, Euntai

    2009-12-01

    Gait-based human identification is a paradigm to recognize individuals using visual cues that characterize their walking motion. An important requirement for successful gait recognition is robustness to variations including different lighting conditions, poses, and walking speed. Deformation of the gait silhouette caused by objects carried by subjects also has a significant effect on the performance of gait recognition systems; a backpack is the most common of these objects. This paper proposes methods for eliminating the effect of a carried backpack for efficient gait recognition. We apply simple, recursive principal component analysis (PCA) reconstructions and error compensation to remove the backpack from the gait representation and then conduct gait recognition. Experiments performed with the CASIA database illustrate the performance of the proposed algorithm.

  18. Hand gesture recognition based on surface electromyography.

    PubMed

    Samadani, Ali-Akbar; Kulic, Dana

    2014-01-01

    Human hands are the most dexterous of human limbs and hand gestures play an important role in non-verbal communication. Underlying electromyograms associated with hand gestures provide a wealth of information based on which varying hand gestures can be recognized. This paper develops an inter-individual hand gesture recognition model based on Hidden Markov models that receives surface electromyography (sEMG) signals as inputs and predicts a corresponding hand gesture. The developed recognition model is tested with a dataset of 10 various hand gestures performed by 25 subjects in a leave-one-subject-out cross validation and an inter-individual recognition rate of 79% was achieved. The promising recognition rate demonstrates the efficacy of the proposed approach for discriminating between gesture-specific sEMG signals and could inform the design of sEMG-controlled prostheses and assistive devices. PMID:25570917

  19. Facial emotion recognition in remitted depressed women.

    PubMed

    Biyik, Utku; Keskin, Duygu; Oguz, Kaya; Akdeniz, Fisun; Gonul, Ali Saffet

    2015-10-01

    Although major depressive disorder (MDD) is primarily characterized by mood symptoms, depressed patients have impairments in facial emotion recognition in many of the basic emotions (anger, fear, happiness, surprise, disgust and sadness). On the other hand, the data in remitted MDD (rMDD) patients is inconsistent and it is not clear that if those impairments persist in remission. To extend the current findings, we applied facial emotion recognition test to a group of remitted depressed women and compared to those of controls. Analyses of variance results showed a significant emotion and group interaction, and in the post hoc analyses, rMDD patients had higher accuracy rate for recognition of sadness compared to those of controls. There were no differences in the reaction time among the patients and controls across the all the basic emotions. The higher recognition rates for sad faces in rMDD patients might contribute to the impairments in social communication and the prognosis of the disease.

  20. Visual cluster analysis and pattern recognition methods

    DOEpatents

    Osbourn, Gordon Cecil; Martinez, Rubel Francisco

    2001-01-01

    A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  1. Innate predator recognition in giant pandas.

    PubMed

    Du, Yiping; Huang, Yan; Zhang, Hemin; Li, Desheng; Yang, Bo; Wei, Ming; Zhou, Yingmin; Liu, Yang

    2012-02-01

    Innate predator recognition confers a survival advantage to prey animals. We investigate whether giant pandas exhibit innate predator recognition. We analyzed behavioral responses of 56 naive adult captive giant pandas (Ailuropoda melanoleuca), to urine from predators and non-predators and water control. Giant pandas performed more chemosensory investigation and displayed flehmen behaviors more frequently in response to predator urine compared to both non-predator urine and water control. Subjects also displayed certain defensive behaviors, as indicated by vigilance, and in certain cases, fleeing behaviors. Our results suggest that there is an innate component to predator recognition in captive giant pandas, although such recognition was only slight to moderate. These results have implications that may be applicable to the conservation and reintroduction of this endangered species.

  2. Pattern recognition using linguistic fuzzy logic predictors

    NASA Astrophysics Data System (ADS)

    Habiballa, Hashim

    2016-06-01

    The problem of pattern recognition has been solved with numerous methods in the Artificial Intelligence field. We present an unconventional method based on Lingustic Fuzzy Logic Forecaster which is primarily used for the task of time series analysis and prediction through logical deduction wtih linguistic variables. This method should be used not only to the time series prediction itself, but also for recognition of patterns in a signal with seasonal component.

  3. Neural-Network Object-Recognition Program

    NASA Technical Reports Server (NTRS)

    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.

  4. Door latching recognition apparatus and process

    DOEpatents

    Eakle, Jr., Robert F.

    2012-05-15

    An acoustic door latch detector is provided in which a sound recognition sensor is integrated into a door or door lock mechanism. The programmable sound recognition sensor can be trained to recognize the acoustic signature of the door and door lock mechanism being properly engaged and secured. The acoustic sensor will signal a first indicator indicating that proper closure was detected or sound an alarm condition if the proper acoustic signature is not detected within a predetermined time interval.

  5. Geometric hashing and object recognition

    NASA Astrophysics Data System (ADS)

    Stiller, Peter F.; Huber, Birkett

    1999-09-01

    We discuss a new geometric hashing method for searching large databases of 2D images (or 3D objects) to match a query built from geometric information presented by a single 3D object (or single 2D image). The goal is to rapidly determine a small subset of the images that potentially contain a view of the given object (or a small set of objects that potentially match the item in the image). Since this must be accomplished independent of the pose of the object, the objects and images, which are characterized by configurations of geometric features such as points, lines and/or conics, must be treated using a viewpoint invariant formulation. We are therefore forced to characterize these configurations in terms of their 3D and 2D geometric invariants. The crucial relationship between the 3D geometry and its 'residual' in 2D is expressible as a correspondence (in the sense of algebraic geometry). Computing a set of generating equations for the ideal of this correspondence gives a complete characterization of the view of independent relationships between an object and all of its possible images. Once a set of generators is in hand, it can be used to devise efficient recognition algorithms and to give an efficient geometric hashing scheme. This requires exploiting the form and symmetry of the equations. The result is a multidimensional access scheme whose efficiency we examine. Several potential directions for improving this scheme are also discussed. Finally, in a brief appendix, we discuss an alternative approach to invariants for generalized perspective that replaces the standard invariants by a subvariety of a Grassmannian. The advantage of this is that one can circumvent many annoying general position assumptions and arrive at invariant equations (in the Plucker coordinates) that are more numerically robust in applications.

  6. The hierarchical brain network for face recognition.

    PubMed

    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.

  7. Object recognition by artificial cortical maps.

    PubMed

    Plebe, Alessio; Domenella, Rosaria Grazia

    2007-09-01

    Object recognition is one of the most important functions of the human visual system, yet one of the least understood, this despite the fact that vision is certainly the most studied function of the brain. We understand relatively well how several processes in the cortical visual areas that support recognition capabilities take place, such as orientation discrimination and color constancy. This paper proposes a model of the development of object recognition capability, based on two main theoretical principles. The first is that recognition does not imply any sort of geometrical reconstruction, it is instead fully driven by the two dimensional view captured by the retina. The second assumption is that all the processing functions involved in recognition are not genetically determined or hardwired in neural circuits, but are the result of interactions between epigenetic influences and basic neural plasticity mechanisms. The model is organized in modules roughly related to the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent neural self-organizing map model that simulates the effects of intercortical lateral connections. This paper shows how recognition capabilities, similar to those found in brain ventral visual areas, can develop spontaneously by exposure to natural images in an artificial cortical model.

  8. Multispectral palmprint recognition using a quaternion matrix.

    PubMed

    Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

    2012-01-01

    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%. PMID:22666049

  9. Oxytocin improves emotion recognition for older males.

    PubMed

    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.

  10. Multispectral Palmprint Recognition Using a Quaternion Matrix

    PubMed Central

    Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

    2012-01-01

    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%. PMID:22666049

  11. Facial expression recognition in Williams syndrome.

    PubMed

    Gagliardi, Chiara; Frigerio, Elisa; Burt, D Michael; Cazzaniga, Ilaria; Perrett, David I; Borgatti, Renato

    2003-01-01

    Individuals with Williams syndrome (WS) excel in face recognition and show both a remarkable concern for social stimuli and a linguistic capacity for, in particular, emotionally referenced language. The animated full facial expression comprehension test (AFFECT), a new test of emotional expression perception, was used to compare participants with WS with both chronological and mental age-matched controls. It was found that expression recognition in WS was worse than that of chronologically age-matched controls but indistinguishable from that of mental age controls. Different processing strategies are thought to underlie the similar performance of individuals with WS and mental age controls. The expression recognition performance of individuals with WS did not correlate with age, but was instead found to correlate with IQ. This is compared to earlier findings, replicated here, that face recognition performance on the Benton test correlates with age and not IQ. The results of the Benton test have been explained in terms of individuals with WS being good at face recognition; since a piecemeal strategy can be used, this strategy is improved with practice which would explain the correlation with age. We propose that poor expression recognition of the individuals with WS is due to a lack of configural ability since changes in the configuration of the face are an important part of expressions. Furthermore, these reduced configural abilities may be due to abnormal neuronal development and are thus fixed from an early age. PMID:12591030

  12. Individual recognition between mother and infant bats (Myotis)

    NASA Technical Reports Server (NTRS)

    Turner, D.; Shaughnessy, A.; Gould, E.

    1972-01-01

    The recognition process and the basis for that recognition, in brown bats, between mother and infant are analyzed. Two parameters, ultrasonic communication and olfactory stimuli, are investigated. The test animals were not allowed any visual contact. It was concluded that individual recognition between mother and infant occurred. However, it could not be determined if the recognition was based on ultrasonic signals or olfactory stimuli.

  13. 29 CFR 29.13 - Recognition of State Apprenticeship Agencies.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 29 Labor 1 2012-07-01 2012-07-01 false Recognition of State Apprenticeship Agencies. 29.13 Section 29.13 Labor Office of the Secretary of Labor LABOR STANDARDS FOR THE REGISTRATION OF APPRENTICESHIP PROGRAMS § 29.13 Recognition of State Apprenticeship Agencies. (a) Recognition. The Department may exercise its authority to grant recognition to...

  14. Stereochemical Recognition of Helicenes on Metal Surfaces.

    PubMed

    Ernst, Karl-Heinz

    2016-06-21

    The chiral recognition among biomolecules is fundamentally important for many processes of life, including the stereochemistry of evolution. Of special interest is chiral recognition during crystallization of racemates, when either homochiral recognition leads to a conglomerate of homochiral crystals or heterochiral recognition dominates resulting in a racemic compound. The complex nature of molecular recognition at the level of nucleation and crystal growth renders it difficult to understand and calls for manageable model systems. Notably, the approach of studying aggregation of molecules at surfaces under well-defined conditions includes the benefit of the availability of a multitude of highly sensitive investigation methods, of which scanning tunneling microscopy (STM) with its submolecular resolution is tremendously valuable. Heterogeneous nucleation at surfaces is strongly favored over homogeneous nucleation in solution; hence, surfaces are significantly involved in stereochemical recognition during crystallization. Helicenes are a fascinating class of chiral compounds with outstanding optical activity. These π-conjugated, ortho-fused, aromatic hydrocarbons are promising candidates for organic electronic devices such as sensors, circular dichroic photonics, liquid crystal displays or spin filters. But in particular the defined footprint of their terminal benzo rings on a surface makes them interesting for studying stereochemical recognition with different single crystalline surfaces and the impact this has, in turn, on intermolecular recognition. In this Account, we describe the self-assembly of helicenes on metal surfaces with the focus on stereochemical recognition in two-dimensional structures. Using the isomeric all-carbon helicenes, heptahelicene and dibenzohelicene as examples, different aggregation phenomena on different surfaces of single crystalline copper, silver, and gold are investigated. By means of STM different modes of transmission of

  15. Stereochemical Recognition of Helicenes on Metal Surfaces.

    PubMed

    Ernst, Karl-Heinz

    2016-06-21

    The chiral recognition among biomolecules is fundamentally important for many processes of life, including the stereochemistry of evolution. Of special interest is chiral recognition during crystallization of racemates, when either homochiral recognition leads to a conglomerate of homochiral crystals or heterochiral recognition dominates resulting in a racemic compound. The complex nature of molecular recognition at the level of nucleation and crystal growth renders it difficult to understand and calls for manageable model systems. Notably, the approach of studying aggregation of molecules at surfaces under well-defined conditions includes the benefit of the availability of a multitude of highly sensitive investigation methods, of which scanning tunneling microscopy (STM) with its submolecular resolution is tremendously valuable. Heterogeneous nucleation at surfaces is strongly favored over homogeneous nucleation in solution; hence, surfaces are significantly involved in stereochemical recognition during crystallization. Helicenes are a fascinating class of chiral compounds with outstanding optical activity. These π-conjugated, ortho-fused, aromatic hydrocarbons are promising candidates for organic electronic devices such as sensors, circular dichroic photonics, liquid crystal displays or spin filters. But in particular the defined footprint of their terminal benzo rings on a surface makes them interesting for studying stereochemical recognition with different single crystalline surfaces and the impact this has, in turn, on intermolecular recognition. In this Account, we describe the self-assembly of helicenes on metal surfaces with the focus on stereochemical recognition in two-dimensional structures. Using the isomeric all-carbon helicenes, heptahelicene and dibenzohelicene as examples, different aggregation phenomena on different surfaces of single crystalline copper, silver, and gold are investigated. By means of STM different modes of transmission of

  16. Impaired picture recognition in transient epileptic amnesia.

    PubMed

    Dewar, Michaela; Hoefeijzers, Serge; Zeman, Adam; Butler, Christopher; Della Sala, Sergio

    2015-01-01

    Transient epileptic amnesia (TEA) is an epileptic syndrome characterized by recurrent, brief episodes of amnesia. Transient epileptic amnesia is often associated with the rapid decline in recall of new information over hours to days (accelerated long-term forgetting - 'ALF'). It remains unknown how recognition memory is affected in TEA over time. Here, we report a systematic study of picture recognition in patients with TEA over the course of one week. Sixteen patients with TEA and 16 matched controls were presented with 300 photos of everyday life scenes. Yes/no picture recognition was tested 5min, 2.5h, 7.5h, 24h, and 1week after picture presentation using a subset of target pictures as well as similar and different foils. Picture recognition was impaired in the patient group at all test times, including the 5-minute test, but it declined normally over the course of 1week. This impairment was associated predominantly with an increased false alarm rate, especially for similar foils. High performance on a control test indicates that this impairment was not associated with perceptual or discrimination deficits. Our findings suggest that, at least in some TEA patients with ALF in verbal recall, picture recognition does not decline more rapidly than in controls over 1week. However, our findings of an early picture recognition deficit suggest that new visual memories are impoverished after minutes in TEA. This could be the result of deficient encoding or impaired early consolidation. The early picture recognition deficit observed could reflect either the early stages of the process that leads to ALF or a separable deficit of anterograde memory in TEA. Lastly, our study suggests that at least some patients with TEA are prone to falsely recognizing new everyday visual information that they have not in fact seen previously. This deficit, alongside their ALF in free recall, likely affects everyday memory performance.

  17. RIG-I in RNA virus recognition

    PubMed Central

    Kell, Alison M.; Gale, Michael

    2015-01-01

    Antiviral immunity is initiated upon host recognition of viral products via non-self molecular patterns known as pathogen-associated molecular patterns (PAMPs). Such recognition initiates signaling cascades that induce intracellular innate immune defenses and an inflammatory response that facilitates development of the acquired immune response. The retinoic acid-inducible gene I (RIG-I) and the RIG-I-like receptor (RLR) protein family are key cytoplasmic pathogen recognition receptors that are implicated in the recognition of viruses across genera and virus families, including functioning as major sensors of RNA viruses, and promoting recognition of some DNA viruses. RIG-I, the charter member of the RLR family, is activated upon binding to PAMP RNA. Activated RIG-I signals by interacting with the adapter protein MAVS leading to a signaling cascade that activates the transcription factors IRF3 and NF-κB. These actions induce the expression of antiviral gene products and the production of type I and III interferons that lead to an antiviral state in the infected cell and surrounding tissue. RIG-I signaling is essential for the control of infection by many RNA viruses. Recently, RIG-I crosstalk with other pathogen recognition receptors and components of the inflammasome has been described. In this review, we discuss the current knowledge regarding the role of RIG-I in recognition of a variety of virus families and its role in programming the adaptive immune response through cross-talk with parallel arms of the innate immune system, including how RIG-I can be leveraged for antiviral therapy. PMID:25749629

  18. Improving protein fold recognition by random forest

    PubMed Central

    2014-01-01

    Background Recognizing the correct structural fold among known template protein structures for a target protein (i.e. fold recognition) is essential for template-based protein structure modeling. Since the fold recognition problem can be defined as a binary classification problem of predicting whether or not the unknown fold of a target protein is similar to an already known template protein structure in a library, machine learning methods have been effectively applied to tackle this problem. In our work, we developed RF-Fold that uses random forest - one of the most powerful and scalable machine learning classification methods - to recognize protein folds. Results RF-Fold consists of hundreds of decision trees that can be trained efficiently on very large datasets to make accurate predictions on a highly imbalanced dataset. We evaluated RF-Fold on the standard Lindahl's benchmark dataset comprised of 976 × 975 target-template protein pairs through cross-validation. Compared with 17 different fold recognition methods, the performance of RF-Fold is generally comparable to the best performance in fold recognition of different difficulty ranging from the easiest family level, the medium-hard superfamily level, and to the hardest fold level. Based on the top-one template protein ranked by RF-Fold, the correct recognition rate is 84.5%, 63.4%, and 40.8% at family, superfamily, and fold levels, respectively. Based on the top-five template protein folds ranked by RF-Fold, the correct recognition rate increases to 91.5%, 79.3% and 58.3% at family, superfamily, and fold levels. Conclusions The good performance achieved by the RF-Fold demonstrates the random forest's effectiveness for protein fold recognition. PMID:25350499

  19. Impaired picture recognition in transient epileptic amnesia.

    PubMed

    Dewar, Michaela; Hoefeijzers, Serge; Zeman, Adam; Butler, Christopher; Della Sala, Sergio

    2015-01-01

    Transient epileptic amnesia (TEA) is an epileptic syndrome characterized by recurrent, brief episodes of amnesia. Transient epileptic amnesia is often associated with the rapid decline in recall of new information over hours to days (accelerated long-term forgetting - 'ALF'). It remains unknown how recognition memory is affected in TEA over time. Here, we report a systematic study of picture recognition in patients with TEA over the course of one week. Sixteen patients with TEA and 16 matched controls were presented with 300 photos of everyday life scenes. Yes/no picture recognition was tested 5min, 2.5h, 7.5h, 24h, and 1week after picture presentation using a subset of target pictures as well as similar and different foils. Picture recognition was impaired in the patient group at all test times, including the 5-minute test, but it declined normally over the course of 1week. This impairment was associated predominantly with an increased false alarm rate, especially for similar foils. High performance on a control test indicates that this impairment was not associated with perceptual or discrimination deficits. Our findings suggest that, at least in some TEA patients with ALF in verbal recall, picture recognition does not decline more rapidly than in controls over 1week. However, our findings of an early picture recognition deficit suggest that new visual memories are impoverished after minutes in TEA. This could be the result of deficient encoding or impaired early consolidation. The early picture recognition deficit observed could reflect either the early stages of the process that leads to ALF or a separable deficit of anterograde memory in TEA. Lastly, our study suggests that at least some patients with TEA are prone to falsely recognizing new everyday visual information that they have not in fact seen previously. This deficit, alongside their ALF in free recall, likely affects everyday memory performance. PMID:25506793

  20. Contextual Modulation of Biases in Face Recognition

    PubMed Central

    Felisberti, Fatima Maria; Pavey, Louisa

    2010-01-01

    Background The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. Methodology and Findings Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral) embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174). An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2). Such bias was eliminated or attenuated by making participants explicitly aware of “cooperative”, “cheating” and “neutral/indifferent” behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3). Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4). Conclusion The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context. PMID:20886086

  1. The impact of subjective recognition experiences on recognition heuristic use: a multinomial processing tree approach.

    PubMed

    Castela, Marta; Kellen, David; Erdfelder, Edgar; Hilbig, Benjamin E

    2014-10-01

    The recognition heuristic (RH) theory states that, in comparative judgments (e.g., Which of two cities has more inhabitants?), individuals infer that recognized objects score higher on the criterion (e.g., population) than unrecognized objects. Indeed, it has often been shown that recognized options are judged to outscore unrecognized ones (e.g., recognized cities are judged as larger than unrecognized ones), although different accounts of this general finding have been proposed. According to the RH theory, this pattern occurs because the binary recognition judgment determines the inference and no other information will reverse this. An alternative account posits that recognized objects are chosen because knowledge beyond mere recognition typically points to the recognized object. A third account can be derived from the memory-state heuristic framework. According to this framework, underlying memory states of objects (rather than recognition judgments) determine the extent of RH use: When two objects are compared, the one associated with a "higher" memory state is preferred, and reliance on recognition increases with the "distance" between their memory states. The three accounts make different predictions about the impact of subjective recognition experiences-whether an object is merely recognized or recognized with further knowledge-on RH use. We estimated RH use for different recognition experiences across 16 published data sets, using a multinomial processing tree model. Results supported the memory-state heuristic in showing that RH use increases when recognition is accompanied by further knowledge. PMID:24638825

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

    ERIC Educational Resources Information Center

    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…

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

    PubMed

    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.

  4. 10 CFR 431.21 - Procedures for recognition and withdrawal of recognition of accreditation bodies and...

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... of accreditation bodies and certification programs. 431.21 Section 431.21 Energy DEPARTMENT OF ENERGY... for recognition and withdrawal of recognition of accreditation bodies and certification programs. (a... Department. If the Department believes that an accreditation body or certification program that has...

  5. 10 CFR 431.21 - Procedures for recognition and withdrawal of recognition of accreditation bodies and...

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... of accreditation bodies and certification programs. 431.21 Section 431.21 Energy DEPARTMENT OF ENERGY... for recognition and withdrawal of recognition of accreditation bodies and certification programs. (a... Department. If the Department believes that an accreditation body or certification program that has...

  6. 10 CFR 431.21 - Procedures for recognition and withdrawal of recognition of accreditation bodies and...

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... of accreditation bodies and certification programs. 431.21 Section 431.21 Energy DEPARTMENT OF ENERGY... for recognition and withdrawal of recognition of accreditation bodies and certification programs. (a... Department. If the Department believes that an accreditation body or certification program that has...

  7. Aging and IQ Effects on Associative Recognition and Priming in Item Recognition

    ERIC Educational Resources Information Center

    McKoon, Gail; Ratcliff, Roger

    2012-01-01

    Two ways to examine memory for associative relationships between pairs of words were tested: an explicit method, associative recognition, and an implicit method, priming in item recognition. In an experiment with both kinds of tests, participants were asked to learn pairs of words. For the explicit test, participants were asked to decide whether…

  8. Exposure effects on music preference and recognition.

    PubMed

    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. PMID:9796224

  9. Development of individually distinct recognition cues.

    PubMed

    Mateo, Jill M

    2006-11-01

    Despite extensive research on the functions of kin recognition, little is known about ontogenetic changes in the cues mediating such recognition. In Belding's ground squirrels, Spermophilus beldingi, secretions from oral glands are both individually distinct and kin distinct, and function in social recognition across many contexts. Behavioral studies of recognition and kin preferences suggest that these cues may change across development, particularly around the time of weaning and emergence from natal burrows (around 25 days of age). I used an habituation-discrimination task with captive S. beldingi, presenting subjects with odors collected from a pair of pups at several ages across early development. I found that at 21 days of age, but not at 7 or 14, young produce detectable odors. Odors are not individually distinct, however, until 28 days of age, after young have emerged from their burrows and begun foraging. In addition, an individual's odor continues to develop after emergence: odors produced by an individual at 20 and 40 days of age are perceived as dissimilar, yet odors produced at 28 and 40 days are treated as similar. Developmental changes in odors provide a proximate explanation for why S. beldingi littermate preferences are not consolidated until after natal emergence, and demonstrate that conspecifics must update their recognition templates as young develop. PMID:17016836

  10. Recognition without awareness: Encoding and retrieval factors.

    PubMed

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

    2015-09-01

    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 present experiments sought to extend this earlier work by having participants study words in different ways and then attempt to recognize the words later in a series of 4-alternative forced-choice (4-AFC) tests, some of which contained no target word. The data of interest are cases in which a target was present and participants stated that they were guessing, yet chose the correct item. This value was greater than p = .25 in all conditions of the 4 experiments, demonstrating the phenomenon of recognition without awareness. Whereas Voss and colleagues attributed their findings with kaleidoscope patterns to enhanced processing fluency of perceptual attributes, the main factor associated with different levels of recognition without awareness in the present studies was a variable criterion for the subjective state accompanying selection of the "guess" option, depending on the overall difficulty of the recognition test. We conclude by discussing some implications of the results for the distinction between implicit and explicit memory. PMID:26010824

  11. Speech recognition: Acoustic, phonetic and lexical

    NASA Astrophysics Data System (ADS)

    Zue, V. W.

    1985-10-01

    Our long-term research goal is the development and implementation of speaker-independent continuous speech recognition systems. It is our conviction that proper utilization of speech-specific knowledge is essential for advanced speech recognition systems. With this in mind, we have continued to make progress on the acquisition of acoustic-phonetic and lexical knowledge. We have completed the development of a continuous digit recognition system. The system was constructed to investigate the utilization of acoustic phonetic knowledge in a speech recognition system. Some of the significant development of this study includes a soft-failure procedure for lexical access, and the discovery of a set of acoustic-phonetic features for verification. We have completed a study of the constraints provided by lexical stress on word recognition. We found that lexical stress information alone can, on the average, reduce the number of word candidates from a large dictionary by more than 80%. In conjunction with this study, we successfully developed a system that automatically determines the stress pattern of a word from the acoustic signal.

  12. Recall and recognition hypermnesia for Socratic stimuli.

    PubMed

    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.

  13. Can corrective feedback improve recognition memory?

    PubMed

    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.

  14. Action recognition in the visual periphery.

    PubMed

    Fademrecht, Laura; Bülthoff, Isabelle; de la Rosa, Stephan

    2016-01-01

    Recognizing whether the gestures of somebody mean a greeting or a threat is crucial for social interactions. In real life, action recognition occurs over the entire visual field. In contrast, much of the previous research on action recognition has primarily focused on central vision. Here our goal is to examine what can be perceived about an action outside of foveal vision. Specifically, we probed the valence as well as first level and second level recognition of social actions (handshake, hugging, waving, punching, slapping, and kicking) at 0° (fovea/fixation), 15°, 30°, 45°, and 60° of eccentricity with dynamic (Experiment 1) and dynamic and static (Experiment 2) actions. To assess peripheral vision under conditions of good ecological validity, these actions were carried out by a life-size human stick figure on a large screen. In both experiments, recognition performance was surprisingly high (more than 66% correct) up to 30° of eccentricity for all recognition tasks and followed a nonlinear decline with increasing eccentricities. PMID:26913625

  15. The perirhinal cortex and recognition memory interference

    PubMed Central

    Watson, H.C.; Lee, A. C. H.

    2013-01-01

    There has recently been an increase in interest in the effects of visual interference on memory processing, with the aim of eluciating the role of the perirhinal cortex (PRC) in recognition memory. One view argues that the PRC processes highly complex conjunctions of object features, and recent evidence from rodents suggests that these representations may be vital for buffering against the effects of pre-retrieval interference on object recognition memory. To investigate whether PRC-dependent object representations play a similar role in humans, we used functional magnetic resonance imaging to scan neurologically healthy participants while they carried out a novel interference-match-to-sample task. This paradigm was specifically designed to concurrently assess the impact of object vs. spatial interference, on recognition memory for objects or scenes, while keeping constant the amount of object and scene information presented across all trials. Activity at retrieval was examined, within an anatomically defined PRC region of interest, according to the demand for object or scene memory, following a period of object compared to spatial interference. Critically, we found greater PRC activity for object memory following object interference, compared to object memory following scene interference, and no difference between object and scene interference for scene recognition. These data demonstrate a role for the human PRC following a period of object, but not scene, interference, during object recognition memory, and emphasize the importance of representational content to mnemonic processing. PMID:23447626

  16. Pattern activation/recognition theory of mind.

    PubMed

    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.

  17. Speech recognition system for an automotive vehicle

    SciTech Connect

    Noso, K.; Futami, T.

    1987-01-13

    A speech recognition system is described for an automotive vehicle for activating vehicle actuators in response to predetermined spoken instructions supplied to the system via a microphone, which comprises: (a) a manually controlled record switch for deriving a record signal when activated; (b) a manually controlled recognition switch for deriving a recognition signal when activated; (c) a speech recognizer for sequentially recording reference spoken instructions whenever one reference spoken instruction is supplied to the system through the microphone while the record switch is activated, a memory having a storage area for each spoken instruction, and means for shifting access to each storage area for each spoken instruction has been recorded in the storage area provided therefore. A means is included for activating vehicle actuators sequentially whenever one recognition spoken instruction is supplied to the system via the microphone while the recognition switch is activated and when the spoken instruction to be recognized is similar to the reference spoken instruction; and (d) means for deriving skip instruction signal and for coupling the skip instruction signal to the speech recognizer to shift access from a currently accessed storage area for recording a current reference spoken instruction to a succeeding storage area for recording a succeeding reference spoken instruction even when the current reference spoken instruction is not supplied to the system through the microphone.

  18. Versatile architecture for image recognition applications

    NASA Astrophysics Data System (ADS)

    Sacramone, Anthony; Scola, Joseph; Shazeer, Dov J.

    1992-03-01

    Architectures for the development of image recognition algorithms must support the implementation of systematic procedures for solving image recognition problems. All too often, designers develop image recognition architectures in an ad hoc fashion which lacks the structure to meet long term needs. Vendors typically supply customers with standard image processing libraries and display tools. Combining these tools and formulating development strategies have remained stumbling blocks in the design of complete image recognition algorithm development environments. In this paper, an architecture is presented which provides a well defined framework, and at the same time is sufficiently flexible to accommodate images of multiple sensor and data types. The primary components of the architecture are: ground-truthing, preprocessing (which includes image processing and segmentation), feature extraction, classification, and performance analysis. Powerful and well defined data structures are exploited for each of the primary components. Groups of programs called tasks manipulate one or more of these data structures, each task belonging to one of the primary components. Multiple tasks can be executed in an unsupervised mode over an entire database of images. Results are then subjected to performance analysis and feedback. A description of the primary components and how they are integrated to facilitate the rapid prototyping and development of image recognition algorithms is presented.

  19. Brain-wave recognition of sentences

    PubMed Central

    Suppes, Patrick; Han, Bing; Lu, Zhong-Lin

    1998-01-01

    Electrical and magnetic brain waves of two subjects were recorded for the purpose of recognizing which one of 12 sentences or seven words auditorily presented was processed. The analysis consisted of averaging over trials to create prototypes and test samples, to each of which a Fourier transform was applied, followed by filtering and an inverse transformation to the time domain. The filters used were optimal predictive filters, selected for each subject. A still further improvement was obtained by taking differences between recordings of two electrodes to obtain bipolar pairs that then were used for the same analysis. Recognition rates, based on a least-squares criterion, varied, but the best were above 90%. The first words of prototypes of sentences also were cut and pasted to test, at least partially, the invariance of a word’s brain wave in different sentence contexts. The best result was above 80% correct recognition. Test samples made up only of individual trials also were analyzed. The best result was 134 correct of 288 (47%), which is promising, given that the expected recognition number by chance is just 24 (or 8.3%). The work reported in this paper extends our earlier work on brain-wave recognition of words only. The recognition rates reported here further strengthen the case that recordings of electric brain waves of words or sentences, together with extensive mathematical and statistical analysis, can be the basis of new developments in our understanding of brain processing of language. PMID:9861061

  20. Pattern activation/recognition theory of mind

    PubMed Central

    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. PMID:26236228

  1. Pattern activation/recognition theory of mind.

    PubMed

    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. PMID:26236228

  2. Robust face recognition via sparse representation.

    PubMed

    Wright, John; Yang, Allen Y; Ganesh, Arvind; Sastry, S Shankar; Ma, Yi

    2009-02-01

    We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models and argue that new theory from sparse signal representation offers the key to addressing this problem. Based on a sparse representation computed by l{1}-minimization, we propose a general classification algorithm for (image-based) object recognition. This new framework provides new insights into two crucial issues in face recognition: feature extraction and robustness to occlusion. For feature extraction, we show that if sparsity in the recognition problem is properly harnessed, the choice of features is no longer critical. What is critical, however, is whether the number of features is sufficiently large and whether the sparse representation is correctly computed. Unconventional features such as downsampled images and random projections perform just as well as conventional features such as Eigenfaces and Laplacianfaces, as long as the dimension of the feature space surpasses certain threshold, predicted by the theory of sparse representation. This framework can handle errors due to occlusion and corruption uniformly by exploiting the fact that these errors are often sparse with respect to the standard (pixel) basis. The theory of sparse representation helps predict how much occlusion the recognition algorithm can handle and how to choose the training images to maximize robustness to occlusion. We conduct extensive experiments on publicly available databases to verify the efficacy of the proposed algorithm and corroborate the above claims.

  3. Active place recognition using image signatures

    NASA Astrophysics Data System (ADS)

    Engelson, Sean P.

    1992-11-01

    For reliable navigation, a mobile robot needs to be able to recognize where it is in the world. We previously described an efficient and effective image-based representation of perceptual information for place recognition. Each place is associated with a set of stored image signatures, each a matrix of numbers derived by evaluating some measurement functions over large blocks of pixels. One difficulty, though, is the large number of inherently ambiguous signatures which bloats the database and makes recognition more difficult. Furthermore, since small differences in orientation can produce very different images, reliable recognition requires many images. These problems can be ameliorated by using active methods to select the best signatures to use for the recognition. Two criteria for good images are distinctiveness (is the scene distinguishable from others?) and stability (how much do small viewpoint motions change image recognizability?). We formulate several heuristic distinctiveness metrics which are good predictors of real image distinctiveness. These functions are then used to direct the motion of the camera to find locally distinctive views for use in recognition. This method also produces some modicum of stability, since it uses a form of local optimization. We present the results of applying this method with a camera mounted on a pan-tilt platform.

  4. Face recognition using ensemble string matching.

    PubMed

    Chen, Weiping; Gao, Yongsheng

    2013-12-01

    In this paper, we present a syntactic string matching approach to solve the frontal face recognition problem. String matching is a powerful partial matching technique, but is not suitable for frontal face recognition due to its requirement of globally sequential representation and the complex nature of human faces, containing discontinuous and non-sequential features. Here, we build a compact syntactic Stringface representation, which is an ensemble of strings. A novel ensemble string matching approach that can perform non-sequential string matching between two Stringfaces is proposed. It is invariant to the sequential order of strings and the direction of each string. The embedded partial matching mechanism enables our method to automatically use every piece of non-occluded region, regardless of shape, in the recognition process. The encouraging results demonstrate the feasibility and effectiveness of using syntactic methods for face recognition from a single exemplar image per person, breaking the barrier that prevents string matching techniques from being used for addressing complex image recognition problems. The proposed method not only achieved significantly better performance in recognizing partially occluded faces, but also showed its ability to perform direct matching between sketch faces and photo faces.

  5. Activity recognition from video using layered approach

    NASA Astrophysics Data System (ADS)

    McPherson, Charles A.; Irvine, John M.; Young, Mon; Stefanidis, Anthony

    2012-01-01

    The adversary in current threat situations can no longer be identified by what they are, but by what they are doing. This has lead to a large increase in the use of video surveillance systems for security and defense applications. With the quantity of video surveillance at the disposal of organizations responsible for protecting military and civilian lives comes issues regarding the storage and screening the data for events and activities of interest. Activity recognition from video for such applications seeks to develop automated screening of video based upon the recognition of activities of interest rather than merely the presence of specific persons or vehicle classes developed for the Cold War problem of "Find the T72 Tank". This paper explores numerous approaches to activity recognition, all of which examine heuristic, semantic, and syntactic methods based upon tokens derived from the video. The proposed architecture discussed herein uses a multi-level approach that divides the problem into three or more tiers of recognition, each employing different techniques according to their appropriateness to strengths at each tier using heuristics, syntactic recognition, and HMM's of token strings to form higher level interpretations.

  6. Automatic TLI recognition system, general description

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

    This report is a general description of an automatic target recognition system developed at the Idaho National Engineering Laboratory for the Department of Energy. A user`s manual is a separate volume, Automatic TLI Recognition System, User`s Guide, and a programmer`s manual is Automatic TLI Recognition System, Programmer`s Guide. This system was designed as an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system naturally incorporates image data fusion, and it gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. In addition to its primary function as a trainable target recognition system, this is also a versatile, general-purpose tool for image manipulation and analysis, which can be either keyboard-driven or script-driven. This report includes descriptions of three variants of the computer hardware, a description of the mathematical basis if the training process, and a description with examples of the system capabilities.

  7. Real-time, face recognition technology

    SciTech Connect

    Brady, S.

    1995-11-01

    The Institute for Scientific Computing Research (ISCR) at Lawrence Livermore National Laboratory recently developed the real-time, face recognition technology KEN. KEN uses novel imaging devices such as silicon retinas developed at Caltech or off-the-shelf CCD cameras to acquire images of a face and to compare them to a database of known faces in a robust fashion. The KEN-Online project makes that recognition technology accessible through the World Wide Web (WWW), an internet service that has recently seen explosive growth. A WWW client can submit face images, add them to the database of known faces and submit other pictures that the system tries to recognize. KEN-Online serves to evaluate the recognition technology and grow a large face database. KEN-Online includes the use of public domain tools such as mSQL for its name-database and perl scripts to assist the uploading of images.

  8. Biologically inspired emotion recognition from speech

    NASA Astrophysics Data System (ADS)

    Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

    2011-12-01

    Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  9. Face recognition using spectral and spatial information

    NASA Astrophysics Data System (ADS)

    Robila, Stefan A.; Chang, Marco; D'Amico, Nisha B.

    2011-09-01

    We present a novel unsupervised method for facial recognition using hyperspectral imaging and decision fusion. In previous work we have separately investigated the use of spectra matching and image based matching. In spectra matching, face spectra are being classified based on spectral similarities. In image based matching, we investigated various approaches based on orthogonal subspaces (such as PCA and OSP). In the current work we provide an automated unsupervised method that starts by detecting the face in the image and then proceeds to performs both spectral and image based matching. The results are fused in a single classification decision. The algorithm is tested on an experimental hyperspectral image database of 17 subjects each with five different facial expressions and viewing angles. Our results show that the decision fusion leads to improvement of recognition accuracy when compared to the individual approaches as well as to recognition based on regular imaging.

  10. Investigation of Carbohydrate Recognition via Computer Simulation

    SciTech Connect

    Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas; Shen, Tongye

    2015-04-28

    Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.

  11. Neural microgenesis of personally familiar face recognition

    PubMed Central

    Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

    2015-01-01

    Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network. PMID:26283361

  12. Investigation of Carbohydrate Recognition via Computer Simulation.

    PubMed

    Johnson, Quentin R; Lindsay, Richard J; Petridis, Loukas; Shen, Tongye

    2015-01-01

    Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Recently, interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. We focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years. PMID:25927900

  13. DNA recognition in Immunity and Disease

    PubMed Central

    Holm, Christian K.; Paludan, Søren R.; Fitzgerald, Katherine A.

    2013-01-01

    Great progress has been made in understanding how immune cells detect microbial pathogens. An area that has received particular attention is nucleic acid sensing where RNA and DNA sensing machineries have been uncovered. For DNA, TLR9 in endosomes and numerous cytoplasmic DNA binding proteins have been identified. Several of these have been proposed to couple DNA recognition to induction of type I IFNs, pro-inflammatory cytokines and/or caspase-1 activation. Given the ubiquitous expression of many of these DNA binding proteins and the significant potential for endogenous DNA to engage these molecules, it is important that DNA recognition is tightly regulated. A better understanding of DNA recognition pathways can provide new insights into infectious, inflammatory and autoimmune diseases. PMID:23313533

  14. Extraversion predicts individual differences in face recognition.

    PubMed

    Li, Jingguang; Tian, Moqian; Fang, Huizhen; Xu, Miao; Li, He; Liu, Jia

    2010-07-01

    In daily life, one of the most common social tasks we perform is to recognize faces. However, the relation between face recognition ability and social activities is largely unknown. Here we ask whether individuals with better social skills are also better at recognizing faces. We found that extraverts who have better social skills correctly recognized more faces than introverts. However, this advantage was absent when extraverts were asked to recognize non-social stimuli (e.g., flowers). In particular, the underlying facet that makes extraverts better face recognizers is the gregariousness facet that measures the degree of inter-personal interaction. In addition, the link between extraversion and face recognition ability was independent of general cognitive abilities. These findings provide the first evidence that links face recognition ability to our daily activity in social communication, supporting the hypothesis that extraverts are better at decoding social information than introverts.

  15. Cross-domain human action recognition.

    PubMed

    Bian, Wei; Tao, Dacheng; Rui, Yong

    2012-04-01

    Conventional human action recognition algorithms cannot work well when the amount of training videos is insufficient. We solve this problem by proposing a transfer topic model (TTM), which utilizes information extracted from videos in the auxiliary domain to assist recognition tasks in the target domain. The TTM is well characterized by two aspects: 1) it uses the bag-of-words model trained from the auxiliary domain to represent videos in the target domain; and 2) it assumes each human action is a mixture of a set of topics and uses the topics learned from the auxiliary domain to regularize the topic estimation in the target domain, wherein the regularization is the summation of Kullback-Leibler divergences between topic pairs of the two domains. The utilization of the auxiliary domain knowledge improves the generalization ability of the learned topic model. Experiments on Weizmann and KTH human action databases suggest the effectiveness of the proposed TTM for cross-domain human action recognition.

  16. Cognitive and artificial representations in handwriting recognition

    NASA Astrophysics Data System (ADS)

    Lenaghan, Andrew P.; Malyan, Ron

    1996-03-01

    Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

  17. License Plate Recognition System for Indian Vehicles

    NASA Astrophysics Data System (ADS)

    Sanap, P. R.; Narote, S. P.

    2010-11-01

    We consider the task of recognition of Indian vehicle number plates (also called license plates or registration plates in other countries). A system for Indian number plate recognition must cope with wide variations in the appearance of the plates. Each state uses its own range of designs with font variations between the designs. Also, vehicle owners may place the plates inside glass covered frames or use plates made of nonstandard materials. These issues compound the complexity of automatic number plate recognition, making existing approaches inadequate. We have developed a system that incorporates a novel combination of image processing and artificial neural network technologies to successfully locate and read Indian vehicle number plates in digital images. Commercial application of the system is envisaged.

  18. Investigation of Carbohydrate Recognition via Computer Simulation

    DOE PAGESBeta

    Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas; Shen, Tongye

    2015-04-28

    Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We reviewmore » the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.« less

  19. Emotion recognition and regulation in anorexia nervosa.

    PubMed

    Harrison, Amy; Sullivan, Sarah; Tchanturia, Kate; Treasure, Janet

    2009-01-01

    It is recognized that emotional problems lie at the core of eating disorders (EDs) but scant attention has been paid to specific aspects such as emotional recognition, regulation and expression. This study aimed to investigate emotion recognition using the Reading the Mind in the Eyes (RME) task and emotion regulation using the Difficulties in Emotion Regulation Scale (DERS) in 20 women with anorexia nervosa (AN) and 20 female healthy controls (HCs). Women with AN had significantly lower scores on RME and reported significantly more difficulties with emotion regulation than HCs. There was a significant negative correlation between total DERS score and correct answers from the RME. These results suggest that women with AN have difficulties with emotional recognition and regulation. It is uncertain whether these deficits result from starvation and to what extent they might be reversed by weight gain alone. These deficits may need to be targeted in treatment.

  20. Neural microgenesis of personally familiar face recognition.

    PubMed

    Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

    2015-09-01

    Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network. PMID:26283361

  1. Facial expression recognition based on improved DAGSVM

    NASA Astrophysics Data System (ADS)

    Luo, Yuan; Cui, Ye; Zhang, Yi

    2014-11-01

    For the cumulative error problem because of randomization sequence of traditional DAGSVM(Directed Acyclic Graph Support Vector Machine) classification, this paper presents an improved DAGSVM expression recognition method. The method uses the distance of class and the standard deviation as the measure of the classer, which minimize the error rate of the upper structure of the classification. At the same time, this paper uses the method which combines discrete cosine transform (Discrete Cosine Transform, DCT) with Local Binary Pattern(Local Binary Pattern - LBP) ,to extract expression feature and be the input to improve the DAGSVM classifier for recognition. Experimental results show that compared with other multi-class support vector machine method, improved DAGSVM classifier can achieve higher recognition rate. And when it's used at the platform of the intelligent wheelchair, experiments show that the method has a better robustness.

  2. Investigation of Carbohydrate Recognition via Computer Simulation.

    PubMed

    Johnson, Quentin R; Lindsay, Richard J; Petridis, Loukas; Shen, Tongye

    2015-04-28

    Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Recently, interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. We focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.

  3. A Survey on Automatic Speaker Recognition Systems

    NASA Astrophysics Data System (ADS)

    Saquib, Zia; Salam, Nirmala; Nair, Rekha P.; Pandey, Nipun; Joshi, Akanksha

    Human listeners are capable of identifying a speaker, over the telephone or an entryway out of sight, by listening to the voice of the speaker. Achieving this intrinsic human specific capability is a major challenge for Voice Biometrics. Like human listeners, voice biometrics uses the features of a person's voice to ascertain the speaker's identity. The best-known commercialized forms of voice Biometrics is Speaker Recognition System (SRS). Speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. This literature survey paper gives brief introduction on SRS, and then discusses general architecture of SRS, biometric standards relevant to voice/speech, typical applications of SRS, and current research in Speaker Recognition Systems. We have also surveyed various approaches for SRS.

  4. Robust facial expression recognition via compressive sensing.

    PubMed

    Zhang, Shiqing; Zhao, Xiaoming; Lei, Bicheng

    2012-01-01

    Recently, compressive sensing (CS) has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC). The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, Gabor wavelets representation and local binary patterns (LBP), are extracted to evaluate the performance of the SRC method. Compared with the nearest neighbor (NN), linear support vector machines (SVM) and the nearest subspace (NS), experimental results on the popular Cohn-Kanade facial expression database demonstrate that the SRC method obtains better performance and stronger robustness to corruption and occlusion on robust facial expression recognition tasks.

  5. Experiences in Pattern Recognition for Machine Olfaction

    NASA Astrophysics Data System (ADS)

    Bessant, C.

    2011-09-01

    Pattern recognition is essential for translating complex olfactory sensor responses into simple outputs that are relevant to users. Many approaches to pattern recognition have been applied in this field, including multivariate statistics (e.g. discriminant analysis), artificial neural networks (ANNs) and support vector machines (SVMs). Reviewing our experience of using these techniques with many different sensor systems reveals some useful insights. Most importantly, it is clear beyond any doubt that the quantity and selection of samples used to train and test a pattern recognition system are by far the most important factors in ensuring it performs as accurately and reliably as possible. Here we present evidence for this assertion and make suggestions for best practice based on these findings.

  6. Recognition bias and the physical attractiveness stereotype.

    PubMed

    Rohner, Jean-Christophe; Rasmussen, Anders

    2012-06-01

    Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon.

  7. Manifold based methods in facial expression recognition

    NASA Astrophysics Data System (ADS)

    Xie, Kun

    2013-07-01

    This paper describes a novel method for facial expression recognition based on non-linear manifold techniques. The graph-based algorithms are designed to treat structure in data, and regularize accordingly. This same goal is shared by several other algorithms, from linear method principal components analysis (PCA) to modern variants such as Laplacian eigenmaps. In this paper we focus on manifold learning for dimensionality reduction and clustering using Laplacian eigenmaps for facial expression recognition. We evaluate the algorithm by using all the pixels and selected features respectively and compare the performance of the proposed non-linear manifold method with the previous linear manifold approach, and the non linear method produces higher recognition rate than the facial expression representation using linear methods.

  8. Fear recognition across the menstrual cycle.

    PubMed

    Pearson, Rebecca; Lewis, Michael B

    2005-03-01

    This study assesses the mediating role of stage of menstrual cycle in the recognition of emotional expressions. It was hypothesised that fear recognition ability would be stronger at high-oestrogen stages of the menstrual cycle. The accuracy of recognising emotional expressions was compared across 50 women who were at different stages of their menstrual cycle. It was found that accuracy to recognise emotions was significantly affected by the interaction between stages of the menstrual cycle and the emotion being displayed. Further analysis revealed that for the emotion expression of fear alone, participants were significantly more accurate at the preovulatory surge (highest oestrogen levels) than at menstruation (oestrogen levels at lowest point). The results have implications for the processes that underlie fear processing and a possible insight into the sexual dimorphism of this ability and conditions that show variations in fear recognition (e.g., autism, Turner syndrome).

  9. Neural microgenesis of personally familiar face recognition.

    PubMed

    Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

    2015-09-01

    Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network.

  10. Feature quality-based multimodal unconstrained eye recognition

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi; Du, Eliza Y.; Lin, Yong; Thomas, N. Luke; Belcher, Craig; Delp, Edward J.

    2013-05-01

    Iris recognition has been tested to the most accurate biometrics using high resolution near infrared images. However, it does not work well under visible wavelength illumination. Sclera recognition, however, has been shown to achieve reasonable recognition accuracy under visible wavelengths. Combining iris and sclera recognition together can achieve better recognition accuracy. However, image quality can significantly affect the recognition accuracy. Moreover, in unconstrained situations, the acquired eye images may not be frontally facing. In this research, we proposed a feature quality-based multimodal unconstrained eye recognition method that combine the respective strengths of iris recognition and sclera recognition for human identification and can work with frontal and off-angle eye images. The research results show that the proposed method is very promising.

  11. When recognition memory is independent of hippocampal function

    PubMed Central

    Smith, Christine N.; Jeneson, Annette; Frascino, Jennifer C.; Kirwan, C. Brock; Hopkins, Ramona O.; Squire, Larry R.

    2014-01-01

    Hippocampal damage has been thought to result in broad memory impairment. Recent studies in humans, however, have raised the possibility that recognition memory for faces might be spared. In five experiments we investigated face recognition in patients with hippocampal lesions (H) or large medial temporal lobe (MTL) lesions, including patients where neurohistological information was available. Recognition of novel faces was unequivocally intact in H patients but only at a short retention interval. Recognition memory for words, buildings, inverted faces, and famous faces was impaired. For MTL patients, recognition memory was impaired for all materials and across all retention intervals. These results indicate that structures other than the hippocampus, perhaps the perirhinal cortex, can support face recognition memory in H patients under some conditions. The fact that the faces were novel when recognition memory was intact does not fully account for our findings. We propose that the role of the hippocampus in recognition memory is related to how recognition decisions are accomplished. In typical recognition tasks, participants proceed by forming an association between a study item and the study list, and the recognition decision is later made based on whether participants believe the item was on the study list. We suggest that face recognition is an exception to this principle and that, at short retention intervals, participants can make their recognition decisions without making explicit reference to the study list. Important features of faces that might make face recognition exceptional are that they are processed holistically and are difficult to verbally label. PMID:24958865

  12. Character Recognition Using Genetically Trained Neural Networks

    SciTech Connect

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

    1998-10-01

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

  13. Toward understanding the limits of gait recognition

    NASA Astrophysics Data System (ADS)

    Liu, Zongyi; Malave, Laura; Osuntogun, Adebola; Sudhakar, Preksha; Sarkar, Sudeep

    2004-08-01

    Most state of the art video-based gait recognition algorithms start from binary silhouettes. These silhouettes, defined as foreground regions, are usually detected by background subtraction methods, which results in holes or missed parts due to similarity of foreground and background color, and boundary errors due to video compression artifacts. Errors in low-level representation make it hard to understand the effect of certain conditions, such as surface and time, on gait recognition. In this paper, we present a part-level, manual silhouette database consisting of 71 subjects, over one gait cycle, with differences in surface, shoe-type, carrying condition, and time. We have a total of about 11,000 manual silhouette frames. The purpose of this manual silhouette database is twofold. First, this is a resource that we make available at http://www.GaitChallenge.org for use by the gait community to test and design better silhouette detection algorithms. These silhouettes can also be used to learn gait dynamics. Second, using the baseline gait recognition algorithm, which was specified along with the HumanID Gait Challenge problem, we show that performance from manual silhouettes is similar and only sometimes better than that from automated silhouettes detected by statistical background subtraction. Low performances when comparing sequences with differences in walking surfaces and time-variation are not fully explained by silhouette quality. We also study the recognition power in each body part and show that recognition based on just the legs is equal to that from the whole silhouette. There is also significant recognition power in the head and torso shape.

  14. [Progress of pattern recognition receptors of molluscs].

    PubMed

    Gao, Qian; Zhao, Qin-ping; Ma, Xiao-xue; Dong, Hui-fen

    2015-08-01

    Molluscs have established complete innate immunity to defense against pathogens. The pattern recognition receptors (PRRs) are the sensory receptors of molluscs to resist outside invaders, as the first reactor to initiate the innate immune response. Some PRRs have been identified in several molluscs, including Toll-like receptors (TLRs) , C-type lectins, galectins, lipopolysaccharide-β-1,3-glucan binding protein (LGBP), Clq domain-containing protein (ClqDC), and peptidoglycan recognition protein (PGRP). PRRs have various biological activities and play important roles in the defense system of molluscs. This paper reviews the research progress of PRRs in molluscs.

  15. Correlation, functional analysis and optical pattern recognition

    SciTech Connect

    Dickey, F.M.; Lee, M.L.; Stalker, K.T.

    1994-03-01

    Correlation integrals have played a central role in optical pattern recognition. The success of correlation, however, has been limited. What is needed is a mathematical operation more complex than correlation. Suitably complex operations are the functionals defined on the Hilbert space of Lebesgue square integrable functions. Correlation is a linear functional of a parameter. In this paper, we develop a representation of functionals in terms of inner products or equivalently correlation functions. We also discuss the role of functionals in neutral networks. Having established a broad relation of correlation to pattern recognition, we discuss the computation of correlation functions using acousto-optics.

  16. Human gait recognition via deterministic learning.

    PubMed

    Zeng, Wei; Wang, Cong

    2012-11-01

    Recognition of temporal/dynamical patterns is among the most difficult pattern recognition tasks. Human gait recognition is a typical difficulty in the area of dynamical pattern recognition. It classifies and identifies individuals by their time-varying gait signature data. Recently, a new dynamical pattern recognition method based on deterministic learning theory was presented, in which a time-varying dynamical pattern can be effectively represented in a time-invariant manner and can be rapidly recognized. In this paper, we present a new model-based approach for human gait recognition via the aforementioned method, specifically for recognizing people by gait. The approach consists of two phases: a training (learning) phase and a test (recognition) phase. In the training phase, side silhouette lower limb joint angles and angular velocities are selected as gait features. A five-link biped model for human gait locomotion is employed to demonstrate that functions containing joint angle and angular velocity state vectors characterize the gait system dynamics. Due to the quasi-periodic and symmetrical characteristics of human gait, the gait system dynamics can be simplified to be described by functions of joint angles and angular velocities of one side of the human body, thus the feature dimension is effectively reduced. Locally-accurate identification of the gait system dynamics is achieved by using radial basis function (RBF) neural networks (NNs) through deterministic learning. The obtained knowledge of the approximated gait system dynamics is stored in constant RBF networks. A gait signature is then derived from the extracted gait system dynamics along the phase portrait of joint angles versus angular velocities. A bank of estimators is constructed using constant RBF networks to represent the training gait patterns. In the test phase, by comparing the set of estimators with the test gait pattern, a set of recognition errors are generated, and the average L(1) norms

  17. Stereo vision with distance and gradient recognition

    NASA Astrophysics Data System (ADS)

    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.

  18. Affine Invariant Character Recognition by Progressive Removing

    NASA Astrophysics Data System (ADS)

    Iwamura, Masakazu; Horimatsu, Akira; Niwa, Ryo; Kise, Koichi; Uchida, Seiichi; Omachi, Shinichiro

    Recognizing characters in scene images suffering from perspective distortion is a challenge. Although there are some methods to overcome this difficulty, they are time-consuming. In this paper, we propose a set of affine invariant features and a new recognition scheme called “progressive removing” that can help reduce the processing time. Progressive removing gradually removes less feasible categories and skew angles by using multiple classifiers. We observed that progressive removing and the use of the affine invariant features reduced the processing time by about 60% in comparison to a trivial one without decreasing the recognition rate.

  19. Exploring Biomolecular Recognition by Modeling and Simulation

    NASA Astrophysics Data System (ADS)

    Wade, Rebecca

    2007-12-01

    Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

  20. Facial expression recognition using thermal image.

    PubMed

    Jiang, Guotai; Song, Xuemin; Zheng, Fuhui; Wang, Peipei; Omer, Ashgan

    2005-01-01

    Facial expression recognition will be studied in this paper using mathematics morphology, through drawing and analyzing the whole geometry characteristics and some geometry characteristics of the interesting area of Infrared Thermal Imaging (IRTI). The results show that geometry characteristic in the interesting region of different expression are obviously different; Facial temperature changes almost with the expression at the same time. Studies have shown feasibility of facial expression recognition on the basis of IRTI. This method can be used to monitor the facial expression in real time, which can be used in auxiliary diagnosis and medical on disease.

  1. Recognition of dementia in hospitalized older adults.

    PubMed

    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. PMID:18156858

  2. Convolution neural networks for ship type recognition

    NASA Astrophysics Data System (ADS)

    Rainey, Katie; Reeder, John D.; Corelli, Alexander G.

    2016-05-01

    Algorithms to automatically recognize ship type from satellite imagery are desired for numerous maritime applications. This task is difficult, and example imagery accurately labeled with ship type is hard to obtain. Convolutional neural networks (CNNs) have shown promise in image recognition settings, but many of these applications rely on the availability of thousands of example images for training. This work attempts to under- stand for which types of ship recognition tasks CNNs might be well suited. We report the results of baseline experiments applying a CNN to several ship type classification tasks, and discuss many of the considerations that must be made in approaching this problem.

  3. Phonematic recognition by linear prediction: Experiment

    NASA Astrophysics Data System (ADS)

    Miclet, L.; Grenier, Y.; Leroux, J.

    The recognition of speech signals analyzed by linear prediction is introduced. The principle of the channel adapted vocoder (CAV) is outlined. The learning of each channel model and adaptation to the speaker are discussed. A method stemming from the canonical analysis of correlations is given. This allows, starting with the CAV of one speaker, the calculation of that of another. The projection function is learned from a series of key words pronounced by both speakers. The reconstruction of phonemes can be explained by recognition factors arising from the vocoder. Automata associated with the channels are used for local smoothing and series of segments are treated in order to produce a phonemic lattice.

  4. The role of pattern recognition receptors in the innate recognition of Candida albicans.

    PubMed

    Zheng, Nan-Xin; Wang, Yan; Hu, Dan-Dan; Yan, Lan; Jiang, Yuan-Ying

    2015-01-01

    Candida albicans is both a commensal microorganism in healthy individuals and a major fungal pathogen causing high mortality in immunocompromised patients. Yeast-hypha morphological transition is a well known virulence trait of C. albicans. Host innate immunity to C. albicans critically requires pattern recognition receptors (PRRs). In this review, we summarize the PRRs involved in the recognition of C. albicans in epithelial cells, endothelial cells, and phagocytic cells separately. We figure out the differential recognition of yeasts and hyphae, the findings on PRR-deficient mice, and the discoveries on human PRR-related single nucleotide polymorphisms (SNPs).

  5. Pattern recognition receptors in antifungal immunity.

    PubMed

    Plato, Anthony; Hardison, Sarah E; Brown, Gordon D

    2015-03-01

    Receptors of the innate immune system are the first line of defence against infection, being able to recognise and initiate an inflammatory response to invading microorganisms. The Toll-like (TLR), NOD-like (NLR), RIG-I-like (RLR) and C-type lectin-like receptors (CLR) are four receptor families that contribute to the recognition of a vast range of species, including fungi. Many of these pattern recognition receptors (PRRs) are able to initiate innate immunity and polarise adaptive responses upon the recognition of fungal cell wall components and other conserved molecular patterns, including fungal nucleic acids. These receptors induce effective mechanisms of fungal clearance in normal hosts, but medical interventions, immunosuppression or genetic predisposition can lead to susceptibility to fungal infections. In this review, we highlight the importance of PRRs in fungal infection, specifically CLRs, which are the major PRR involved. We will describe specific PRRs in detail, the importance of receptor collaboration in fungal recognition and clearance, and describe how genetic aberrations in PRRs can contribute to disease pathology.

  6. Summary of 1971 pattern recognition program development

    NASA Technical Reports Server (NTRS)

    Whitley, S. L.

    1972-01-01

    Eight areas related to pattern recognition analysis at the Earth Resources Laboratory are discussed: (1) background; (2) Earth Resources Laboratory goals; (3) software problems/limitations; (4) operational problems/limitations; (5) immediate future capabilities; (6) Earth Resources Laboratory data analysis system; (7) general program needs and recommendations; and (8) schedule and milestones.

  7. Super-resolution benefit for face recognition

    NASA Astrophysics Data System (ADS)

    Hu, Shuowen; Maschal, Robert; Young, S. Susan; Hong, Tsai Hong; Phillips, Jonathon P.

    2011-06-01

    Vast amounts of video footage are being continuously acquired by surveillance systems on private premises, commercial properties, government compounds, and military installations. Facial recognition systems have the potential to identify suspicious individuals on law enforcement watchlists, but accuracy is severely hampered by the low resolution of typical surveillance footage and the far distance of suspects from the cameras. To improve accuracy, super-resolution can enhance suspect details by utilizing a sequence of low resolution frames from the surveillance footage to reconstruct a higher resolution image for input into the facial recognition system. This work measures the improvement of face recognition with super-resolution in a realistic surveillance scenario. Low resolution and super-resolved query sets are generated using a video database at different eye-to-eye distances corresponding to different distances of subjects from the camera. Performance of a face recognition algorithm using the super-resolved and baseline query sets was calculated by matching against galleries consisting of frontal mug shots. The results show that super-resolution improves performance significantly at the examined mid and close ranges.

  8. Recognition of Prior Vocational Learning in Sweden

    ERIC Educational Resources Information Center

    Andersson, Per; Fejes, Andreas; Ahn, Song-Ee

    2004-01-01

    Initiatives in the recognition of prior learning (RPL) have been taken in Sweden in recent years, mainly focusing on prior vocational learning among immigrants. The government started different projects to find methods for recognising a person's prior learning in the field of vocational competence. This article presents a study of how these…

  9. Recognition of Prior Learning: The Participants' Perspective

    ERIC Educational Resources Information Center

    Miguel, Marta C.; Ornelas, José H.; Maroco, João P.

    2016-01-01

    The current narrative on lifelong learning goes beyond formal education and training, including learning at work, in the family and in the community. Recognition of prior learning is a process of evaluation of those skills and knowledge acquired through life experience, allowing them to be formally recognized by the qualification systems. It is a…

  10. Test Sequence Priming in Recognition Memory

    ERIC Educational Resources Information Center

    Johns, Elizabeth E.; Mewhort, D. J. K.

    2009-01-01

    The authors examined priming within the test sequence in 3 recognition memory experiments. A probe primed its successor whenever both probes shared a feature with the same studied item ("interjacent priming"), indicating that the study item like the probe is central to the decision. Interjacent priming occurred even when the 2 probes did not…

  11. Recognition of Unfamiliar Talking Faces at Birth

    ERIC Educational Resources Information Center

    Coulon, Marion; Guellai, Bahia; Streri, Arlette

    2011-01-01

    Sai (2005) investigated the role of speech in newborns' recognition of their mothers' faces. Her results revealed that, when presented with both their mother's face and that of a stranger, newborns preferred looking at their mother only if she had previously talked to them. The present study attempted to extend these findings to any other faces.…

  12. Transfer learning for bimodal biometrics recognition

    NASA Astrophysics Data System (ADS)

    Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

    2013-10-01

    Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

  13. Facial emotion recognition in remitted depressed women.

    PubMed

    Biyik, Utku; Keskin, Duygu; Oguz, Kaya; Akdeniz, Fisun; Gonul, Ali Saffet

    2015-10-01

    Although major depressive disorder (MDD) is primarily characterized by mood symptoms, depressed patients have impairments in facial emotion recognition in many of the basic emotions (anger, fear, happiness, surprise, disgust and sadness). On the other hand, the data in remitted MDD (rMDD) patients is inconsistent and it is not clear that if those impairments persist in remission. To extend the current findings, we applied facial emotion recognition test to a group of remitted depressed women and compared to those of controls. Analyses of variance results showed a significant emotion and group interaction, and in the post hoc analyses, rMDD patients had higher accuracy rate for recognition of sadness compared to those of controls. There were no differences in the reaction time among the patients and controls across the all the basic emotions. The higher recognition rates for sad faces in rMDD patients might contribute to the impairments in social communication and the prognosis of the disease. PMID:26321673

  14. Image recognition and consistency of response

    NASA Astrophysics Data System (ADS)

    Haygood, Tamara M.; Ryan, John; Liu, Qing Mary A.; Bassett, Roland; Brennan, Patrick C.

    2012-02-01

    Purpose: To investigate the connection between conscious recognition of an image previously encountered in an experimental setting and consistency of response to the experimental question.
    Materials and Methods: Twenty-four radiologists viewed 40 frontal chest radiographs and gave their opinion as to the position of a central venous catheter. One-to-three days later they again viewed 40 frontal chest radiographs and again gave their opinion as to the position of the central venous catheter. Half of the radiographs in the second set were repeated images from the first set and half were new. The radiologists were asked of each image whether it had been included in the first set. For this study, we are evaluating only the 20 repeated images. We used the Kruskal-Wallis test and Fisher's exact test to determine the relationship between conscious recognition of a previously interpreted image and consistency in interpretation of the image.
    Results. There was no significant correlation between recognition of the image and consistency in response regarding the position of the central venous catheter. In fact, there was a trend in the opposite direction, with radiologists being slightly more likely to give a consistent response with respect to images they did not recognize than with respect to those they did recognize.
    Conclusion: Radiologists' recognition of previously-encountered images in an observer-performance study does not noticeably color their interpretation on the second encounter.

  15. Speech recognition: Acoustic, phonetic and lexical knowledge

    NASA Astrophysics Data System (ADS)

    Zue, V. W.

    1985-08-01

    During this reporting period we continued to make progress on the acquisition of acoustic-phonetic and lexical knowledge. We completed development of a continuous digit recognition system. The system was constructed to investigate the use of acoustic-phonetic knowledge in a speech recognition system. The significant achievements of this study include the development of a soft-failure procedure for lexical access and the discovery of a set of acoustic-phonetic features for verification. We completed a study of the constraints that lexical stress imposes on word recognition. We found that lexical stress information alone can, on the average, reduce the number of word candidates from a large dictionary by more than 80 percent. In conjunction with this study, we successfully developed a system that automatically determines the stress pattern of a word from the acoustic signal. We performed an acoustic study on the characteristics of nasal consonants and nasalized vowels. We have also developed recognition algorithms for nasal murmurs and nasalized vowels in continuous speech. We finished the preliminary development of a system that aligns a speech waveform with the corresponding phonetic transcription.

  16. SCIENTIFIC CREATIVITY - ITS RECOGNITION AND DEVELOPMENT.

    ERIC Educational Resources Information Center

    BARRON, FRANK; TAYLOR, CLAVIN W.

    SELECTED RESEARCH PAPERS FROM THREE CONFERENCES ON THE RECOGNITION AND DEVELOPMENT OF SCIENTIFIC CREATIVITY ARE CONTAINED IN THIS BOOK. THE CONFERENCES WERE HELD IN 1955, 1957, AND 1959 AND WERE SUPPORTED BY THE NATIONAL SCIENCE FOUNDATION. CRITERIA USED IN SELECTING PAPERS FOR INCLUSION WERE (1) NON-TECHNICAL NATURE AND GENERAL READABILITY, (2)…

  17. ORNL Biometric Eye Model for Iris Recognition

    SciTech Connect

    Santos-Villalobos, Hector J; Barstow, Del R; Karakaya, Mahmut; Chaum, Edward; Boehnen, Chris Bensing

    2012-01-01

    Iris recognition has been proven to be an accurate and reliable biometric. However, the recognition of non-ideal iris images such as off angle images is still an unsolved problem. We propose a new biometric targeted eye model and a method to reconstruct the off-axis eye to its frontal view allowing for recognition using existing methods and algorithms. This allows for existing enterprise level algorithms and approaches to be largely unmodified by using our work as a pre-processor to improve performance. In addition, we describe the `Limbus effect' and its importance for an accurate segmentation of off-axis irides. Our method uses an anatomically accurate human eye model and ray-tracing techniques to compute a transformation function, which reconstructs the iris to its frontal, non-refracted state. Then, the same eye model is used to render a frontal view of the reconstructed iris. The proposed method is fully described and results from synthetic data are shown to establish an upper limit on performance improvement and establish the importance of the proposed approach over traditional linear elliptical unwrapping methods. Our results with synthetic data demonstrate the ability to perform an accurate iris recognition with an image taken as much as 70 degrees off-axis.

  18. A Synchronization Account of False Recognition

    ERIC Educational Resources Information Center

    Johns, Brendan T.; Jones, Michael N.; Mewhort, Douglas J. K.

    2012-01-01

    We describe a computational model to explain a variety of results in both standard and false recognition. A key attribute of the model is that it uses plausible semantic representations for words, built through exposure to a linguistic corpus. A study list is encoded in the model as a gist trace, similar to the proposal of fuzzy trace theory…

  19. Optical correlation recognition based on LCOS

    NASA Astrophysics Data System (ADS)

    Tang, Mingchuan; Wu, Jianhong

    2013-08-01

    Vander-Lugt correlator[1] plays an important role in optical pattern recognition due to the characteristics of accurate positioning and high signal-to-noise ratio. The ideal Vander-Lugt correlator should have the ability of outputting strong and sharp correlation peak in allusion to the true target, in the existing Spatial Light Modulators[2], Liquid Crystal On Silicon(LCOS) has been the most competitive candidate for the matched filter owing to the continuous phase modulation peculiarity. Allowing for the distortions of the target to be identified including rotations, scaling changes, perspective changes, which can severely impact the correlation recognition results, herein, we present a modified Vander-Lugt correlator based on the LCOS by means of applying an iterative algorithm to the design of the filter so that the correlator can invariant to the distortions while maintaining good performance. The results of numerical simulation demonstrate that the filter could get the similar recognition results for all the training images. And the experiment shows that the modified correlator achieves the 180° rotating tolerance significantly improving the recognition efficiency of the correlator.

  20. Partial face recognition: alignment-free approach.

    PubMed

    Liao, Shengcai; Jain, Anil K; Li, Stan Z

    2013-05-01

    Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recognition approach that does not require face alignment by eye coordinates or any other fiducial points. We develop an alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image. In this way, any probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. A new keypoint descriptor called Gabor Ternary Pattern (GTP) is also developed for robust and discriminative face recognition. Experimental results are reported on four public domain face databases (FRGCv2.0, AR, LFW, and PubFig) under both the open-set identification and verification scenarios. Comparisons with two leading commercial face recognition SDKs (PittPatt and FaceVACS) and two baseline algorithms (PCA+LDA and LBP) show that the proposed method, overall, is superior in recognizing both holistic and partial faces without requiring alignment.

  1. Pattern Recognition by Retina-Like Devices.

    ERIC Educational Resources Information Center

    Weiman, Carl F. R.; Rothstein, Jerome

    This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

  2. Pedestrian recognition using automotive radar sensors

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

    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 insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

  3. Automatic speech recognition in air traffic control

    NASA Technical Reports Server (NTRS)

    Karlsson, Joakim

    1990-01-01

    Automatic Speech Recognition (ASR) technology and its application to the Air Traffic Control system are described. The advantages of applying ASR to Air Traffic Control, as well as criteria for choosing a suitable ASR system are presented. Results from previous research and directions for future work at the Flight Transportation Laboratory are outlined.

  4. Cockpit voice recognition program at Princeton University

    NASA Technical Reports Server (NTRS)

    Huang, C. Y.

    1983-01-01

    Voice recognition technology (VRT) is applied to aeronautics, particularly on the pilot workload alleviation. The VRT does not have to prove its maturity any longer. The feasibility of voice tuning of radio and DME are demonstrated since there are immediate advantages to the pilot and can be completed in a reasonable time.

  5. Illumination-invariant hand gesture recognition

    NASA Astrophysics Data System (ADS)

    Mendoza-Morales, América I.; Miramontes-Jaramillo, Daniel; Kober, Vitaly

    2015-09-01

    In recent years, human-computer interaction (HCI) has received a lot of interest in industry and science because it provides new ways to interact with modern devices through voice, body, and facial/hand gestures. The application range of the HCI is from easy control of home appliances to entertainment. Hand gesture recognition is a particularly interesting problem because the shape and movement of hands usually are complex and flexible to be able to codify many different signs. In this work we propose a three step algorithm: first, detection of hands in the current frame is carried out; second, hand tracking across the video sequence is performed; finally, robust recognition of gestures across subsequent frames is made. Recognition rate highly depends on non-uniform illumination of the scene and occlusion of hands. In order to overcome these issues we use two Microsoft Kinect devices utilizing combined information from RGB and infrared sensors. The algorithm performance is tested in terms of recognition rate and processing time.

  6. Face recognition increases during saccade preparation.

    PubMed

    Lin, Hai; Rizak, Joshua D; Ma, Yuan-ye; Yang, Shang-chuan; Chen, Lin; Hu, Xin-tian

    2014-01-01

    Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

  7. Influence of motion on face recognition.

    PubMed

    Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

    2012-02-01

    The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

  8. Ear recognition from one sample per person.

    PubMed

    Chen, Long; Mu, Zhichun; Zhang, Baoqing; Zhang, Yi

    2015-01-01

    Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP) available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC) ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods. PMID:26024226

  9. Word-Recognition Training: Computer versus Tutor

    ERIC Educational Resources Information Center

    Lewandowski, Lawrence; Begeny, John; Rogers, Cynthia

    2006-01-01

    The effects of tutor- or computer-assisted word recognition were assessed in a sample of third grade children. At pre-test, students' reading accuracy and fluency were evaluated on a training word list, generalization word list, and reading passages. Students were then randomly assigned to one of three group conditions--control (students practiced…

  10. Iris Recognition: The Consequences of Image Compression

    NASA Astrophysics Data System (ADS)

    Ives, Robert W.; Bishop, Daniel A.; Du, Yingzi; Belcher, Craig

    2010-12-01

    Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

  11. Word Recognition: Theoretical Issues and Instructional Hints.

    ERIC Educational Resources Information Center

    Smith, Edward E.; Kleiman, Glenn M.

    Research on adult readers' word recognition skills is used in this paper to develop a general information processing model of reading. Stages of the model include feature extraction, interpretation, lexical access, working memory, and integration. Of those stages, particular attention is given to the units of interpretation, speech recoding and…

  12. Recognition criteria vary with fluctuating uncertainty.

    PubMed

    Solomon, Joshua A; Cavanagh, Patrick; Gorea, Andrei

    2012-08-06

    In distinct experiments we examined memories for orientation and size. After viewing a randomly oriented Gabor patch (or a plain white disk of random size), observers were given unlimited time to reproduce as faithfully as possible the orientation (or size) of that standard stimulus with an adjustable Gabor patch (or disk). Then, with this match stimulus still in view, a recognition probe was presented. On half the trials, this probe was identical to the standard. We expected observers to classify the probe (a same/different task) on the basis of its difference from the match, which should have served as an explicit memory of the standard. Observers did better than that. Larger differences were classified as "same" when probe and standard were indeed identical. In some cases, recognition performance exceeded that of a simulated observer subject to the same matching errors, but forced to adopt the single most advantageous criterion difference between the probe and match. Recognition must have used information that was not or could not be exploited in the reproduction phase. One possible source for that information is observers' confidence in their reproduction (e.g., in their memory of the standard). Simulations confirm the enhancement of recognition performance when decision criteria are adjusted trial-by-trial, on the basis of the observer's estimated reproduction error.

  13. Image enhancement method for fingerprint recognition system.

    PubMed

    Li, Shunshan; Wei, Min; Tang, Haiying; Zhuang, Tiange; Buonocore, Michael

    2005-01-01

    Image enhancement plays an important role in Fingerprint Recognition System. In this paper fingerprint image enhancement method, a refined Gabor filter, is presented. This enhancement method can connect the ridge breaks, ensures the maximal gray values located at the ridge center and has the ability to compensate for the nonlinear deformations. The result shows it can improve the performance of image enhancement.

  14. A new approach for sclera vein recognition

    NASA Astrophysics Data System (ADS)

    Thomas, N. L.; Du, Yingzi; Zhou, Zhi

    2010-04-01

    The vein structure in the sclera is stable over time, unique to each person, and well suited for human identification. A few researchers have performed sclera vein pattern recognition and reported promising initial results. Sclera recognition poses several challenges: the vein structure moves and deforms with the movement of the eye; images of sclera patterns are often defocused and/or saturated; and, most importantly, the vein structure in the sclera is multi-layered and has complex non-linear deformation. In this paper, we proposed a new method for sclera recognition: First, we developed a color-based sclera region estimation scheme for sclera segmentation. Second, we designed a Gabor wavelet-based sclera pattern enhancement method, and an adaptive thresholding method to emphasize and binarize the sclera vein patterns. Third, we proposed a line descriptor-based feature extraction, registration, and matching method that is illumination-, scale-, orientation-, and deformation-invariant, and can mitigate the multi-layered deformation effects exhibited in the sclera and tolerate segmentation error. It is empirically verified using the UBIRIS database that the proposed method can perform accurate sclera recognition.

  15. Multiculturalism: Examining the Politics of Recognition.

    ERIC Educational Resources Information Center

    Taylor, Charles; And Others

    This volume focuses on the challenge of multiculturalism and the politics of recognition facing democratic societies today, concentrating on the United States and Canada in particular. The initial inquiry by Charles Taylor considers whether the institutions of liberal democratic government make room for, or even should accommodate, recognizing the…

  16. A rough set approach to speech recognition

    NASA Astrophysics Data System (ADS)

    Zhao, Zhigang

    1992-09-01

    Speech recognition is a very difficult classification problem due to the variations in loudness, speed, and tone of voice. In the last 40 years, many methodologies have been developed to solve this problem, but most lack learning ability and depend fully on the knowledge of human experts. Systems of this kind are hard to develop and difficult to maintain and upgrade. A study was conducted to investigate the feasibility of using a machine learning approach in solving speech recognition problems. The system is based on rough set theory. It first generates a set of decision rules using a set of reference words called training samples, and then uses the decision rules to recognize new words. The main feature of this system is that, under the supervision of human experts, the machine learns and applies knowledge on its own to the designated tasks. The main advantages of this system over a traditional system are its simplicity and adaptiveness, which suggest that it may have significant potential in practical applications of computer speech recognition. Furthermore, the studies presented demonstrate the potential application of rough-set based learning systems in solving other important pattern classification problems, such as character recognition, system fault detection, and trainable robotic control.

  17. Ear Recognition from One Sample Per Person

    PubMed Central

    Chen, Long; Mu, Zhichun; Zhang, Baoqing; Zhang, Yi

    2015-01-01

    Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP) available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC) ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods. PMID:26024226

  18. Multivariant technique for multiclass pattern recognition.

    PubMed

    Hester, C F; Casasent, D

    1980-06-01

    A technique for multiclass optical pattern recognition of different perspective views of an object is described. Each multiclass representation of an object is described as an orthonormal basis function expansion, and a single averaged matched spatial filter is then produced from a weighted linear combination of these functions. The technique is demonstrated for a terminal missile guidance application using IR tank imagery.

  19. Ear recognition from one sample per person.

    PubMed

    Chen, Long; Mu, Zhichun; Zhang, Baoqing; Zhang, Yi

    2015-01-01

    Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP) available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC) ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods.

  20. Models of spoken-word recognition.

    PubMed

    Weber, Andrea; Scharenborg, Odette

    2012-05-01

    All words of the languages we know are stored in the mental lexicon. Psycholinguistic models describe in which format lexical knowledge is stored and how it is accessed when needed for language use. The present article summarizes key findings in spoken-word recognition by humans and describes how models of spoken-word recognition account for them. Although current models of spoken-word recognition differ considerably in the details of implementation, there is general consensus among them on at least three aspects: multiple word candidates are activated in parallel as a word is being heard, activation of word candidates varies with the degree of match between the speech signal and stored lexical representations, and activated candidate words compete for recognition. No consensus has been reached on other aspects such as the flow of information between different processing levels, and the format of stored prelexical and lexical representations. WIREs Cogn Sci 2012, 3:387-401. doi: 10.1002/wcs.1178 For further resources related to this article, please visit the WIREs website.

  1. Speech Recognition for A Digital Video Library.

    ERIC Educational Resources Information Center

    Witbrock, Michael J.; Hauptmann, Alexander G.

    1998-01-01

    Production of the meta-data supporting the Informedia Digital Video Library interface is automated using techniques derived from artificial intelligence research. Speech recognition and natural-language processing, information retrieval, and image analysis are applied to produce an interface that helps users locate information and navigate more…

  2. Kin-informative recognition cues in ants.

    PubMed

    Nehring, Volker; Evison, Sophie E F; Santorelli, Lorenzo A; d'Ettorre, Patrizia; Hughes, William O H

    2011-07-01

    Although social groups are characterized by cooperation, they are also often the scene of conflict. In non-clonal systems, the reproductive interests of group members will differ and individuals may benefit by exploiting the cooperative efforts of other group members. However, such selfish 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 for within-colony conflicts in genetically diverse societies than previously thought.

  3. Speech Recognition Technology for Disabilities Education

    ERIC Educational Resources Information Center

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

    2005-01-01

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

  4. Recognition of Social Identity in Ants

    PubMed Central

    Bos, Nick; d’Ettorre, Patrizia

    2012-01-01

    Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend of hydrocarbons present on the cuticle of every individual (the “label”). Recognition occurs when an ant encounters another individual, and compares the label it perceives to an internal representation of its own colony odor (the “template”). A mismatch between label and template leads to rejection of the encountered individual. Although advances have been made in our understanding of how the label is produced and acquired, contradictory evidence exists about information processing of recognition cues. Here, we review the literature on template acquisition in ants and address how and when the template is formed, where in the nervous system it is localized, and the possible role of learning. We combine seemingly contradictory evidence in to a novel, parsimonious theory for the information processing of nestmate recognition cues. PMID:22461777

  5. Teaching Recognition Skills to Improve Products.

    ERIC Educational Resources Information Center

    Knight, G. William; And Others

    1990-01-01

    First year dental students (n=86) in a conservative restorations course were taught a discrimination learning paradigm to improve production quality. Evaluation of Class 1 amalgam preparations indicates the improved recognition skills corresponded with improved cavity preparation, supporting the use of this teaching model. (Author/MSE)

  6. Molecular recognition driven catalysis using polymeric nanoreactors.

    PubMed

    Cotanda, Pepa; O'Reilly, Rachel K

    2012-10-25

    The concept of using polymeric micelles to catalyze organic reactions in water is presented and compared to surfactant based micelles in the context of molecular recognition. We report for the first time enzyme-like specific catalysis by tethering the catalyst in the well-defined hydrophobic core of a polymeric micelle.

  7. Word recognition using ideal word patterns

    NASA Astrophysics Data System (ADS)

    Zhao, Sheila X.; Srihari, Sargur N.

    1994-03-01

    The word shape analysis approach to text recognition is motivated by discoveries in psychological studies of the human reading process. It attempts to describe and compare the shape of the word as a whole object without trying to segment and recognize the individual characters, so it bypasses the errors committed in character segmentation and classification. However, the large number of classes and large variation and distortion expected in all patterns belonging to the same class make it difficult for conventional, accurate, pattern recognition approaches. A word shape analysis approach using ideal word patterns to overcome the difficulty and improve recognition performance is described in this paper. A special word pattern which characterizes a word class is extracted from different sample patterns of the word class and stored in memory. Recognition of a new word pattern is achieved by comparing it with the special pattern of each word class called ideal word pattern. The process of generating the ideal word pattern of each word class is proposed. The algorithm was tested on a set of machine printed gray scale word images which included a wide range of print types and qualities.

  8. Plastic Antibodies: Molecular Recognition with Imprinted Polymers

    ERIC Educational Resources Information Center

    Rushton, Gregory T.; Furmanski, Brian; Shimizu, Ken D.

    2005-01-01

    Synthetic polymers are prepared and tested in a study for their molecular recognition properties of an adenine derivative, ethyl adenine-9-acetate (EA9A), within two laboratory periods. The procedure introduces undergraduate chemistry students to noncovalent molecular imprinting as well as the analytical techniques for assessing their recognition…

  9. Conformal Predictions in Multimedia Pattern Recognition

    ERIC Educational Resources Information Center

    Nallure Balasubramanian, Vineeth

    2010-01-01

    The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

  10. Object recognition memory and the rodent hippocampus.

    PubMed

    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 task. Rats received 12 5-min exposures to two identical objects and then received either bilateral lesions of the hippocampus or sham surgery 1 d, 4 wk, or 8 wk after the final exposure. On a retention test 2 wk after surgery, the 1-d and 4-wk hippocampal lesion groups exhibited impaired object recognition memory. In contrast, the 8-wk hippocampal lesion group performed similarly to controls, and both groups exhibited a preference for the novel object. These same rats were then given four postoperative tests using unique object pairs and a 3-h delay between the exposure phase and the test phase. Hippocampal lesions produced moderate and reliable memory impairment. The results suggest that the hippocampus is important for object recognition memory.

  11. The Neural Correlates of Everyday Recognition Memory

    ERIC Educational Resources Information Center

    Milton, F.; Muhlert, N.; Butler, C. R.; Benattayallah, A.; Zeman, A. Z.

    2011-01-01

    We used a novel automatic camera, SenseCam, to create a recognition memory test for real-life events. Adapting a "Remember/Know" paradigm, we asked healthy undergraduates, who wore SenseCam for 2 days, in their everyday environments, to classify images as strongly or weakly remembered, strongly or weakly familiar or novel, while brain activation…

  12. Simplified Pattern Recognition Based On Multiaperture Optics

    NASA Astrophysics Data System (ADS)

    Schneider, Richard T.; Lin, Shih-Chao

    1987-05-01

    Multiaperture optics systems are similar in design to the concepts applying to the insect eye. Digitizing at the detector level is inherent in these systems. The fact that each eyelet forms one pixel of the overall image lends itself to optical preprocessing. There-fore a simplified pattern recognition scheme can be used in connection with multiaperture optics systems. The pattern recognition system used is based on the conjecture that all shapes encountered can be dissected into a set of rectangles. This is accomplished by creating a binary image and comparing each row of numbers starting at the top of the frame with the next row below. A set of rules is established which decides if the binary ones of the next row are to be incorporated in the present rectangle or start a new rectangle. The number and aspect ratios of the rectangles formed constitute a recognition code. These codes are kept and updated in a library. Since the same shape may give rise to different recognition codes depending on the attitude of the shape in respect to the detector grid, all shapes are rotated and normalized prior to dissecting. The rule is that the pattern is turned to maximize the number of straight edges which line up with the detector grid. The mathematical mechanism for rotation of the shape is described. Assuming a-priori knowledge of the size of the object exists, the normalization procedure can be used for distance determination. The description of the hardware for acquisition of the image is provided.

  13. Mirror Self-Recognition beyond the Face

    ERIC Educational Resources Information Center

    Nielsen, Mark; Suddendorf, Thomas; Slaughter, Virginia

    2006-01-01

    Three studies (N=144) investigated how toddlers aged 18 and 24 months pass the surprise-mark test of self-recognition. In Study 1, toddlers were surreptitiously marked in successive conditions on their legs and faces with stickers visible only in a mirror. Rates of sticker touching did not differ significantly between conditions. In Study 2,…

  14. Gender Recognition from Point-Light Walkers

    ERIC Educational Resources Information Center

    Pollick, Frank E.; Kay, Jim W.; Heim, Katrin; Stringer, Rebecca

    2005-01-01

    Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal…

  15. Transformations in the Recognition of Visual Forms

    ERIC Educational Resources Information Center

    Charness, Neil; Bregman, Albert S.

    1973-01-01

    In a study which required college students to learn to recognize four flexible plastic shapes photographed on different backgrounds from different angles, the importance of a context-rich environment for the learning and recognition of visual patterns was illustrated. (Author)

  16. Humoral pattern recognition and the complement system.

    PubMed

    Degn, S E; Thiel, S

    2013-08-01

    In the context of immunity, pattern recognition is the art of discriminating friend from foe and innocuous from noxious. The basis of discrimination is the existence of evolutionarily conserved patterns on microorganisms, which are intrinsic to these microorganisms and necessary for their function and existence. Such immutable or slowly evolving patterns are ideal handles for recognition and have been targeted by early cellular immune defence mechanisms such as Toll-like receptors, NOD-like receptors, RIG-I-like receptors, C-type lectin receptors and by humoral defence mechanisms such as the complement system. Complement is a proteolytic cascade system comprising around 35 different soluble and membrane-bound proteins. It constitutes a central part of the innate immune system, mediating several major innate effector functions and modulating adaptive immune responses. The complement cascade proceeds via controlled, limited proteolysis and conformational changes of constituent proteins through three activation pathways: the classical pathway, the alternative pathway and the lectin pathway, which converge in common effector functions. Here, we review the nature of the pattern recognition molecules involved in complement activation, as well as their close relatives with no or unknown capacity for activating complement. We proceed to examine the composition of the pattern recognition complexes involved in complement activation, focusing on those of the lectin pathway, and arrive at a new model for their mechanism of operation, supported by recently emerging evidence.

  17. Automatic TLI recognition system beta prototype testing

    SciTech Connect

    Lassahn, G.D.

    1996-06-01

    This report describes the beta prototype automatic target recognition system ATR3, and some performance tests done with this system. This is a fully operational system, with a high computational speed. It is useful for findings any kind of target in digitized image data, and as a general purpose image analysis tool.

  18. Music Education Intervention Improves Vocal Emotion Recognition

    ERIC Educational Resources Information Center

    Mualem, Orit; Lavidor, Michal

    2015-01-01

    The current study is an interdisciplinary examination of the interplay among music, language, and emotions. It consisted of two experiments designed to investigate the relationship between musical abilities and vocal emotional recognition. In experiment 1 (N = 24), we compared the influence of two short-term intervention programs--music and…

  19. Effects of Cognitive Load on Speech Recognition

    ERIC Educational Resources Information Center

    Mattys, Sven L.; Wiget, Lukas

    2011-01-01

    The effect of cognitive load (CL) on speech recognition has received little attention despite the prevalence of CL in everyday life, e.g., dual-tasking. To assess the effect of CL on the interaction between lexically-mediated and acoustically-mediated processes, we measured the magnitude of the "Ganong effect" (i.e., lexical bias on phoneme…

  20. Multiple degree of freedom optical pattern recognition

    NASA Technical Reports Server (NTRS)

    Casasent, D.

    1987-01-01

    Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

  1. Recognition of Hits in a Target

    NASA Astrophysics Data System (ADS)

    Semerak, Vojtech; Drahansky, Martin

    This paper describes two possible ways of hit recognition in a target. First method is based on frame differencing with use of a stabilization algorithm to eliminate movements of a target. Second method uses flood fill with random seed point definition to find hits in the target scene.

  2. Toleration and Recognition: What Should We Teach?

    ERIC Educational Resources Information Center

    Jones, Peter Nigel

    2010-01-01

    Generally we think it good to tolerate and to accord recognition. Yet both are complex phenomena and our teaching must acknowledge and cope with that complexity. We tolerate only what we object to, so our message to students cannot be simply, "promote the good and prevent the bad". Much advocacy of toleration is not what it pretends to be. Nor is…

  3. Item Effects in Recognition Memory for Words

    ERIC Educational Resources Information Center

    Freeman, Emily; Heathcote, Andrew; Chalmers, Kerry; Hockley, William

    2010-01-01

    We investigate the effects of word characteristics on episodic recognition memory using analyses that avoid Clark's (1973) "language-as-a-fixed-effect" fallacy. Our results demonstrate the importance of modeling word variability and show that episodic memory for words is strongly affected by item noise (Criss & Shiffrin, 2004), as measured by the…

  4. Unpacking Recognition and Esteem in School Pedagogies

    ERIC Educational Resources Information Center

    Wulf, Christoph; Bittner, Martin; Clemens, Iris; Kellermann, Ingrid

    2012-01-01

    The article focuses on pedagogical practices of recognition and esteem (Wertschatzung) and on the question of how those practices can be appropriately studied and epistemologically grasped. The investigation involves an inner-city elementary school in a socio-economically problematic district. With regard to the communication forms in this…

  5. The Signal Recognition Particle Database (SRPDB).

    PubMed

    Larsen, N; Zwieb, C

    1996-01-01

    The Signal Recognition Particle Database (SRPDB) provides aligned SRP RNA and SRP protein sequences, annotated and phylogenetically ordered. The current release included 93 RNAs and 29 proteins representing SRP9, SRP14, SRP19, SRP21, SRP54, SRP68 and SRP72. The SRPDB can be downloaded and is accessible via the World Wide Web.

  6. Partial face recognition: alignment-free approach.

    PubMed

    Liao, Shengcai; Jain, Anil K; Li, Stan Z

    2013-05-01

    Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recognition approach that does not require face alignment by eye coordinates or any other fiducial points. We develop an alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image. In this way, any probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. A new keypoint descriptor called Gabor Ternary Pattern (GTP) is also developed for robust and discriminative face recognition. Experimental results are reported on four public domain face databases (FRGCv2.0, AR, LFW, and PubFig) under both the open-set identification and verification scenarios. Comparisons with two leading commercial face recognition SDKs (PittPatt and FaceVACS) and two baseline algorithms (PCA+LDA and LBP) show that the proposed method, overall, is superior in recognizing both holistic and partial faces without requiring alignment. PMID:23520259

  7. Object recognition with hierarchical discriminant saliency networks

    PubMed Central

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  8. Object recognition with hierarchical discriminant saliency networks.

    PubMed

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  9. Object recognition with hierarchical discriminant saliency networks.

    PubMed

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  10. Integration trumps selection in object recognition.

    PubMed

    Saarela, Toni P; Landy, Michael S

    2015-03-30

    Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

  11. Integration trumps selection in object recognition

    PubMed Central

    Saarela, Toni P.; Landy, Michael S.

    2015-01-01

    Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

  12. A neuromorphic system for video object recognition.

    PubMed

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  13. Phoneme fuzzy characterization in speech recognition systems

    NASA Astrophysics Data System (ADS)

    Beritelli, Francesco; Borrometi, Luca; Cuce, Antonino

    1997-10-01

    The acoustic approach to speech recognition has an important advantage compared with pattern recognition approach: it presents a lower complexity because it doesn't require explicit structures such as the hidden Markov model. In this work, we show how to characterize some phonetic classes of the Italian language in order to obtain a speaker and vocabulary independent speech recognition system. A phonetic data base is carried out with 200 continuous speech sentences of 12 speakers, 6 females and 6 males. The sentences are sampled at 8000 Hz and manual labelled with Asystem Sound Impression Software to obtain about 1600 units. We analyzed several speech parameters such as formants, LPC and reflection coefficients, energy, normal/differential zero crossing rate, cepstral and autocorrelation coefficients. The aim is the achievement of a phonetic recognizer to facilitate the so- called lexical access problem, that is to decode phonetic units into complete sense word strings. The knowledge is supplied to the recognizer in terms of fuzzy systems. The utilized software is called adaptive fuzzy modeler and it belongs to the rule generator family. A procedure has been implemented to integrate in the fuzzy system an 'expert' knowledge in order to obtain significant improvements in the recognition accuracy. Up to this point the tests show a recognition rate of 92% for the vocal class, 89% for the fricatives class and 94% for the nasal class, utilizing 1000 phonemes in phase of learning and 600 phonemes in phase of testing. Our intention is to complete the fuzzy recognizer extending this work to the other phonetic classes.

  14. Laptop Computer - Based Facial Recognition System Assessment

    SciTech Connect

    R. A. Cain; G. B. Singleton

    2001-03-01

    The objective of this project was to assess the performance of the leading commercial-off-the-shelf (COTS) facial recognition software package when used as a laptop application. We performed the assessment to determine the system's usefulness for enrolling facial images in a database from remote locations and conducting real-time searches against a database of previously enrolled images. The assessment involved creating a database of 40 images and conducting 2 series of tests to determine the product's ability to recognize and match subject faces under varying conditions. This report describes the test results and includes a description of the factors affecting the results. After an extensive market survey, we selected Visionics' FaceIt{reg_sign} software package for evaluation and a review of the Facial Recognition Vendor Test 2000 (FRVT 2000). This test was co-sponsored by the US Department of Defense (DOD) Counterdrug Technology Development Program Office, the National Institute of Justice, and the Defense Advanced Research Projects Agency (DARPA). Administered in May-June 2000, the FRVT 2000 assessed the capabilities of facial recognition systems that were currently available for purchase on the US market. Our selection of this Visionics product does not indicate that it is the ''best'' facial recognition software package for all uses. It was the most appropriate package based on the specific applications and requirements for this specific application. In this assessment, the system configuration was evaluated for effectiveness in identifying individuals by searching for facial images captured from video displays against those stored in a facial image database. An additional criterion was that the system be capable of operating discretely. For this application, an operational facial recognition system would consist of one central computer hosting the master image database with multiple standalone systems configured with duplicates of the master operating in

  15. Robust kernel collaborative representation for face recognition

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

    2015-05-01

    One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

  16. A neuromorphic system for video object recognition

    PubMed Central

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  17. Amygdala damage impairs emotion recognition from music.

    PubMed

    Gosselin, Nathalie; Peretz, Isabelle; Johnsen, Erica; Adolphs, Ralph

    2007-01-28

    The role of the amygdala in recognition of danger is well established for visual stimuli such as faces. A similar role in another class of emotionally potent stimuli -- music -- has been recently suggested by the study of epileptic patients with unilateral resection of the anteromedian part of the temporal lobe [Gosselin, N., Peretz, I., Noulhiane, M., Hasboun, D., Beckett, C., & Baulac, M., et al. (2005). Impaired recognition of scary music following unilateral temporal lobe excision. Brain, 128(Pt 3), 628-640]. The goal of the present study was to assess the specific role of the amygdala in the recognition of fear from music. To this aim, we investigated a rare subject, S.M., who has complete bilateral damage relatively restricted to the amygdala and not encompassing other sectors of the temporal lobe. In Experiment 1, S.M. and four matched controls were asked to rate the intensity of fear, peacefulness, happiness, and sadness from computer-generated instrumental music purposely created to express those emotions. Subjects also rated the arousal and valence of each musical stimulus. An error detection task assessed basic auditory perceptual function. S.M. performed normally in this perceptual task, but was selectively impaired in the recognition of scary and sad music. In contrast, her recognition of happy music was normal. Furthermore, S.M. judged the scary music to be less arousing and the peaceful music less relaxing than did the controls. Overall, the pattern of impairment in S.M. is similar to that previously reported in patients with unilateral anteromedial temporal lobe damage. S.M.'s impaired emotional judgments occur in the face of otherwise intact processing of musical features that are emotionally determinant. The use of tempo and mode cues in distinguishing happy from sad music was also spared in S.M. Thus, the amygdala appears to be necessary for emotional processing of music rather than the perceptual processing itself.

  18. A neuromorphic system for video object recognition.

    PubMed

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  19. Visual body recognition in a prosopagnosic patient.

    PubMed

    Moro, V; Pernigo, S; Avesani, R; Bulgarelli, C; Urgesi, C; Candidi, M; Aglioti, S M

    2012-01-01

    Conspicuous deficits in face recognition characterize prosopagnosia. Information on whether agnosic deficits may extend to non-facial body parts is lacking. Here we report the neuropsychological description of FM, a patient affected by a complete deficit in face recognition in the presence of mild clinical signs of visual object agnosia. His deficit involves both overt and covert recognition of faces (i.e. recognition of familiar faces, but also categorization of faces for gender or age) as well as the visual mental imagery of faces. By means of a series of matching-to-sample tasks we investigated: (i) a possible association between prosopagnosia and disorders in visual body perception; (ii) the effect of the emotional content of stimuli on the visual discrimination of faces, bodies and objects; (iii) the existence of a dissociation between identity recognition and the emotional discrimination of faces and bodies. Our results document, for the first time, the co-occurrence of body agnosia, i.e. the visual inability to discriminate body forms and body actions, and prosopagnosia. Moreover, the results show better performance in the discrimination of emotional face and body expressions with respect to body identity and neutral actions. Since FM's lesions involve bilateral fusiform areas, it is unlikely that the amygdala-temporal projections explain the relative sparing of emotion discrimination performance. Indeed, the emotional content of the stimuli did not improve the discrimination of their identity. The results hint at the existence of two segregated brain networks involved in identity and emotional discrimination that are at least partially shared by face and body processing.

  20. 21 CFR 26.75 - Suspension of recognition obligations.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM... COMMUNITY âFrameworkâ Provisions § 26.75 Suspension of recognition obligations. Either party may suspend...

  1. The Elementary Private School Recognition Program: Mike Mulligan's View.

    ERIC Educational Resources Information Center

    Lodish, Richard

    1986-01-01

    Describes the goals, the selection criteria, and the selection process of the Elementary Private School Recognition Program. Includes a listing, by states, of the 60 private elementary schools selected for 1985-86 recognition. (IW)

  2. Supporting Recognition of Clinical Nurses With the DAISY Award.

    PubMed

    Barnes, Bonnie; Barnes, Mark; Sweeney, Cynthia D

    2016-04-01

    What is meaningful recognition? As a nurse leader, are you prepared to answer that question? Understanding the implications and impact of recognition for nursing staff is a powerful tool for nursing leaders. The DAISY Award is used in more than 2,100 organizations around the globe to give meaning to recognition. Here is a glimpse of the power that recognition can bring to an organization, to its leaders, and most importantly to staff. PMID:27011149

  3. Semantic information can facilitate covert face recognition in congenital prosopagnosia.

    PubMed

    Rivolta, Davide; Schmalzl, Laura; Coltheart, Max; Palermo, Romina

    2010-11-01

    People with congenital prosopagnosia have never developed the ability to accurately recognize faces. This single case investigation systematically investigates covert and overt face recognition in "C.," a 69 year-old woman with congenital prosopagnosia. Specifically, we: (a) describe the first assessment of covert face recognition in congenital prosopagnosia using multiple tasks; (b) show that semantic information can contribute to covert recognition; and (c) provide a theoretical explanation for the mechanisms underlying covert face recognition.

  4. Emotion recognition following pediatric traumatic brain injury: longitudinal analysis of emotional prosody and facial emotion recognition.

    PubMed

    Schmidt, Adam T; Hanten, Gerri R; Li, Xiaoqi; Orsten, Kimberley D; Levin, Harvey S

    2010-08-01

    Children with closed head injuries often experience significant and persistent disruptions in their social and behavioral functioning. Studies with adults sustaining a traumatic brain injury (TBI) indicate deficits in emotion recognition and suggest that these difficulties may underlie some of the social deficits. The goal of the current study was to examine if children sustaining a TBI exhibit difficulties with emotion recognition in terms of emotional prosody and face emotion recognition and to determine (1) how these abilities change over time and (2) what, if any, additional factors such as sex, age, and socioeconomic status (SES) affected the findings. Results provide general support for the idea that children sustaining a TBI exhibit deficits in emotional prosody and face emotion recognition performance. Further, although some gains were noted in the TBI group over the two-years following injury, factors such as SES and age at injury influenced the trajectory of recovery. The current findings indicate the relationship between TBI and emotion recognition is complex and may be influenced by a number of developmental and environmental factors. Results are discussed in terms of their similarity to previous investigations demonstrating the influence of environmental factors on behavioral recovery following pediatric TBI, and with regard to future investigations that can further explore the link between emotion recognition deficits and long-term behavioral and psychosocial recovery.

  5. Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition

    PubMed Central

    Burns, Edwin J.; Tree, Jeremy J.; Weidemann, Christoph T.

    2014-01-01

    Dual process models of recognition memory propose two distinct routes for recognizing a face: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K) paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP) through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in eight individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG) data at the scalp. Those with DP were found to produce fewer correct “remember” responses and more false alarms than controls. EEG results showed that posterior “remember” old/new effects were delayed and restricted to the right posterior (RP) area in those with DP in comparison to the controls. A posterior “know” old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal “know” old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face-specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects. PMID:25177283

  6. Indirect readout in protein-peptide recognition: a different story from classical biomolecular recognition.

    PubMed

    Yu, Hua; Zhou, Peng; Deng, Maolin; Shang, Zhicai

    2014-07-28

    Protein-peptide interactions are prevalent and play essential roles in many living activities. Peptides recognize their protein partners by direct nonbonded interactions and indirect adjustment of conformations. Although processes of protein-peptide recognition have been comprehensively studied in both sequences and structures recently, flexibility of peptides and the configuration entropy penalty in recognition did not get enough attention. In this study, 20 protein-peptide complexes and their corresponding unbound peptides were investigated by molecular dynamics simulations. Energy analysis revealed that configurational entropy penalty introduced by restriction of the degrees of freedom of peptides in indirect readout process of protein-peptide recognition is significant. Configurational entropy penalty has become the main content of the indirect readout energy in protein-peptide recognition instead of deformation energy which is the main source of the indirect readout energy in classical biomolecular recognition phenomena, such as protein-DNA binding. These results provide us a better understanding of protein-peptide recognition and give us some implications in peptide ligand design.

  7. Semi-spectrum correlation methods for fingerprint recognition

    NASA Astrophysics Data System (ADS)

    Perju, Veacheslav L.; Casasent, David P.; Perju, Veacheslav V.; Saranciuc, Dorian I.

    2003-08-01

    There are presented the results of the investigations of the fingerprints' images correlation recognition in conditions of different distortions -- scale, angular orientation change, image's surface reducing, noises' influence. There are examined possibilities of the person's identification and their verification. There are proposed and investigated the method of the fingerprints' semi-spectrums recognition and the method of the fingerprints' space-dependent recognition.

  8. Recognition and Toleration: Conflicting Approaches to Diversity in Education?

    ERIC Educational Resources Information Center

    Laegaard, 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…

  9. Peer-to-Peer Recognition of Learning in Open Education

    ERIC Educational Resources Information Center

    Schmidt, Jan Philipp; Geith, Christine; Haklev, Stian; Thierstein, Joel

    2009-01-01

    Recognition in education is the acknowledgment of learning achievements. Accreditation is certification of such recognition by an institution, an organization, a government, a community, etc. There are a number of assessment methods by which learning can be evaluated (exam, practicum, etc.) for the purpose of recognition and accreditation, and…

  10. Culture/Religion and Identity: Social Justice versus Recognition

    ERIC Educational Resources Information Center

    Bekerman, Zvi

    2012-01-01

    Recognition is the main word attached to multicultural perspectives. The multicultural call for recognition, the one calling for the recognition of cultural minorities and identities, the one now voiced by liberal states all over and also in Israel was a more difficult one. It took the author some time to realize that calling for the recognition…

  11. 46 CFR 8.240 - Application for recognition.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-521). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification...

  12. 46 CFR 8.220 - Recognition of a classification society.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 46 Shipping 1 2011-10-01 2011-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  13. 46 CFR 8.240 - Application for recognition.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-521). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification...

  14. 46 CFR 8.260 - Revocation of classification society recognition.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 46 Shipping 1 2011-10-01 2011-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the...

  15. 46 CFR 8.260 - Revocation of classification society recognition.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the...

  16. 46 CFR 8.220 - Recognition of a classification society.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  17. 46 CFR 8.260 - Revocation of classification society recognition.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 1 2013-10-01 2013-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the...

  18. 46 CFR 8.260 - Revocation of classification society recognition.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 1 2014-10-01 2014-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the...

  19. 46 CFR 8.220 - Recognition of a classification society.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 1 2014-10-01 2014-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  20. 46 CFR 8.240 - Application for recognition.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-ENG). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification...

  1. 46 CFR 8.240 - Application for recognition.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-ENG). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification...

  2. 46 CFR 8.220 - Recognition of a classification society.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 46 Shipping 1 2012-10-01 2012-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  3. 46 CFR 8.240 - Application for recognition.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-ENG). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification...

  4. 46 CFR 8.260 - Revocation of classification society recognition.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 46 Shipping 1 2012-10-01 2012-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the...

  5. 46 CFR 8.220 - Recognition of a classification society.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 1 2013-10-01 2013-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  6. Developing Recognition Programs for Units within Student Affairs.

    ERIC Educational Resources Information Center

    Avery, Cynthia M.

    2001-01-01

    According to many psychologists, the connections between motivation and rewards and recognition are crucial to employee satisfaction. A plan for developing a multi-layered recognition program within a division of student affairs is described. These recognitions programs are designed taking into account the differences in perceptions of awards by…

  7. Recognition and Accountability: Sole Parent Postgraduates in University Conditions

    ERIC Educational Resources Information Center

    Hook, Genine A.

    2015-01-01

    This paper aims to examine some of ways sole parents sought recognition as postgraduate students in Australian universities. Judith Butler's theory of recognition notes that recognition is always partial and any account we give of ourselves must be given to another. Participants articulated that supervisors were critical in the process of…

  8. Relations among Early Object Recognition Skills: Objects and Letters

    ERIC Educational Resources Information Center

    Augustine, Elaine; Jones, Susan S.; Smith, Linda B.; Longfield, Erica

    2015-01-01

    Human visual object recognition is multifaceted and comprised of several domains of expertise. Developmental relations between young children's letter recognition and their 3-dimensional object recognition abilities are implicated on several grounds but have received little research attention. Here, we ask how preschoolers' success in recognizing…

  9. Handwritten character recognition based on hybrid neural networks

    NASA Astrophysics Data System (ADS)

    Wang, Peng; Sun, Guangmin; Zhang, Xinming

    2001-09-01

    A hybrid neural network system for the recognition of handwritten character using SOFM,BP and Fuzzy network is presented. The horizontal and vertical project of preprocessed character and 4_directional edge project are used as feature vectors. In order to improve the recognition effect, the GAT algorithm is applied. Through the hybrid neural network system, the recognition rate is improved visibly.

  10. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 31 Money and Finance:Treasury 2 2013-07-01 2013-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  11. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 31 Money and Finance: Treasury 2 2014-07-01 2014-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  12. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 31 Money and Finance:Treasury 2 2012-07-01 2012-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  13. Automatic TLI recognition system, user`s guide

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

    This report describes how to use an automatic target recognition system (version 14). In separate volumes are a general description of the ATR system, Automatic TLI Recognition System, General Description, and a programmer`s manual, Automatic TLI Recognition System, Programmer`s Guide.

  14. The Recognition Heuristic: A Review of Theory and Tests

    PubMed Central

    Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.

    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) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

  15. Improved Open-Microphone Speech Recognition

    NASA Astrophysics Data System (ADS)

    Abrash, Victor

    2002-12-01

    Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken

  16. Improved Open-Microphone Speech Recognition

    NASA Technical Reports Server (NTRS)

    Abrash, Victor

    2002-01-01

    Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken

  17. Transfer-Appropriate Processing in Recognition Memory: Perceptual and Conceptual Effects on Recognition Memory Depend on Task Demands

    ERIC Educational Resources Information Center

    Parks, Colleen M.

    2013-01-01

    Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which…

  18. Hemispheric lateralization of linguistic prosody recognition in comparison to speech and speaker recognition.

    PubMed

    Kreitewolf, Jens; Friederici, Angela D; von Kriegstein, Katharina

    2014-11-15

    Hemispheric specialization for linguistic prosody is a controversial issue. While it is commonly assumed that linguistic prosody and emotional prosody are preferentially processed in the right hemisphere, neuropsychological work directly comparing processes of linguistic prosody and emotional prosody suggests a predominant role of the left hemisphere for linguistic prosody processing. Here, we used two functional magnetic resonance imaging (fMRI) experiments to clarify the role of left and right hemispheres in the neural processing of linguistic prosody. In the first experiment, we sought to confirm previous findings showing that linguistic prosody processing compared to other speech-related processes predominantly involves the right hemisphere. Unlike previous studies, we controlled for stimulus influences by employing a prosody and speech task using the same speech material. The second experiment was designed to investigate whether a left-hemispheric involvement in linguistic prosody processing is specific to contrasts between linguistic prosody and emotional prosody or whether it also occurs when linguistic prosody is contrasted against other non-linguistic processes (i.e., speaker recognition). Prosody and speaker tasks were performed on the same stimulus material. In both experiments, linguistic prosody processing was associated with activity in temporal, frontal, parietal and cerebellar regions. Activation in temporo-frontal regions showed differential lateralization depending on whether the control task required recognition of speech or speaker: recognition of linguistic prosody predominantly involved right temporo-frontal areas when it was contrasted against speech recognition; when contrasted against speaker recognition, recognition of linguistic prosody predominantly involved left temporo-frontal areas. The results show that linguistic prosody processing involves functions of both hemispheres and suggest that recognition of linguistic prosody is based on

  19. N-methyl-D-aspartate recognition site ligands modulate activity at the coupled glycine recognition site.

    PubMed

    Hood, W F; Compton, R P; Monahan, J B

    1990-03-01

    In synaptic plasma membranes from rat forebrain, the potencies of glycine recognition site agonists and antagonists for modulating [3H]1-[1-(2-thienyl)cyclohexyl]piperidine ([3H]TCP) binding and for displacing strychnine-insensitive [3H]glycine binding are altered in the presence of N-methyl-D-aspartate (NMDA) recognition site ligands. The NMDA competitive antagonist, cis-4-phosphonomethyl-2-piperidine carboxylate (CGS 19755), reduces [3H]glycine binding, and the reduction can be fully reversed by the NMDA recognition site agonist, L-glutamate. Scatchard analysis of [3H]glycine binding shows that in the presence of CGS 19755 there is no change in Bmax (8.81 vs. 8.79 pmol/mg of protein), but rather a decrease in the affinity of glycine (KD of 0.202 microM vs. 0.129 microM). Similar decreases in affinity are observed for the glycine site agonists, D-serine and 1-aminocyclopropane-1-carboxylate, in the presence of CGS 19755. In contrast, the affinity of glycine antagonists, 1-hydroxy-3-amino-2-pyrrolidone and 1-aminocyclobutane-1-carboxylate, at this [3H]glycine recognition site increases in the presence of CGS 19755. The functional consequence of this change in affinity was addressed using the modulation of [3H]TCP binding. In the presence of L-glutamate, the potency of glycine agonists for the stimulation of [3H]TCP binding increases, whereas the potency of glycine antagonists decreases. These data are consistent with NMDA recognition site ligands, through their interactions at the NMDA recognition site, modulating activity at the associated glycine recognition site.

  20. Automated plan-recognition of chemotherapy protocols

    PubMed Central

    Bhatia, Haresh; Levy, Mia

    2011-01-01

    Cancer patients are often treated with multiple sequential chemotherapy protocols ranging in complexity from simple to highly complex patterns of multiple repeating drugs. Clinical documentation procedures that focus on details of single drug events, however, make it difficult for providers and systems to efficiently abstract the sequence and nature of treatment protocols. We have developed a data driven method for cancer treatment plan recognition that takes as input pharmacy chemotherapy dispensing records and produces the sequence of identified chemotherapy protocols. Compared to a manually annotated gold standard, our method was 75% accurate and 80% precise for a breast cancer testing set (110 patients, 2,029 drug events), and 54% accurate and 63% precise for a lung cancer testing set (53 patients, 670 drug events). This method for cancer treatment plan recognition may provide clinicians and systems an abstracted view of the patient’s treatment history. PMID:22195061

  1. Static hand gesture recognition from a video

    NASA Astrophysics Data System (ADS)

    Rokade, Rajeshree S.; Doye, Dharmpal

    2011-10-01

    A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

  2. Protein-targeted corona phase molecular recognition.

    PubMed

    Bisker, Gili; Dong, Juyao; Park, Hoyoung D; Iverson, Nicole M; Ahn, Jiyoung; Nelson, Justin T; Landry, Markita P; Kruss, Sebastian; Strano, Michael S

    2016-01-01

    Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

  3. Recall and recognition memory in Parkinson's disease.

    PubMed

    Breen, E K

    1993-03-01

    This study is concerned with recall and recognition memory in patients with Parkinson's disease. The results show that the Parkinson group was significantly impaired on tests of free recall compared to a group of age matched controls. By contrast, when given tests of recognition memory for the same items their performance was practically identical. In recall, significant main effects are reported for serial position and list presentation but no qualitative differences were observed between the two groups on these measures, both of which showed a primacy and recency effect. However, the control subjects recalled significantly more words in their original order of presentation than the patient group, a difference which appears to have occurred at the level of input. It was concluded that although the patient group was able to adopt and use similar strategies to the control subjects, they were less efficient in using these, a difficulty which was attributed to limited capacity due to mental slowness.

  4. Audio-visual affective expression recognition

    NASA Astrophysics Data System (ADS)

    Huang, Thomas S.; Zeng, Zhihong

    2007-11-01

    Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

  5. Extended target recognition in cognitive radar networks.

    PubMed

    Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

    2010-01-01

    We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

  6. Hyperspectral face recognition under variable outdoor illumination

    NASA Astrophysics Data System (ADS)

    Pan, Zhihong; Healey, Glenn E.; Prasad, Manish; Tromberg, Bruce J.

    2004-08-01

    We examine the performance of illumination-invariant face recognition in outdoor hyperspectral images using a database of 200 subjects. The hyperspectral camera acquires 31 bands over the 700-1000nm spectral range. Faces are represented by local spectral information for several tissue types. Illumination variation is modeled by low-dimensional spectral radiance subspaces. Invariant subspace projection over multiple tissue types is used for recognition. The experiments consider various face orientations and expressions. The analysis includes experiments for images synthesized using face reflectance images of 200 subjects and a database of over 7,000 outdoor illumination spectra. We also consider experiments that use a set of face images that were acquired under outdoor illumination conditions.

  7. Recognition of Monomers and Polymers by Cyclodextrins

    NASA Astrophysics Data System (ADS)

    Wenz, Gerhard

    Cyclodextrins (CDs), cyclic oligomers consisting of 6, 7, 8, or more α(1 → 4)-linked glucose units, are readily available, water-soluble organic host compounds that are able to complex organic guest molecules if the latter contain a suitable hydrophobic binding site. The main driving forces are nonpolar interactions such as hydrophobic and van der Waals interactions. CDs are able to recognize the thickness, polarity, and chirality of monomeric and polymeric guest molecules. In addition, functional groups can be covalently attached to CDs to modify or improve the molecular recognition capability of CDs. In this review, the binding potentials of the most important CDs and CD derivatives are summarized, and general rules for the recognition of monomeric and polymeric guests are derived. A supramolecular tool box of water-soluble hosts and guests is provided, which allows the assembly of many sophisticated supramolecular structures, as well as rotaxanes and polyrotaxanes.

  8. Biometric recognition using 3D ear shape.

    PubMed

    Yan, Ping; Bowyer, Kevin W

    2007-08-01

    Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and 3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario on a database of 415 subjects and 1,386 total probes.

  9. Protein-targeted corona phase molecular recognition

    PubMed Central

    Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

    2016-01-01

    Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

  10. Feature recognition applications in mesh generation

    SciTech Connect

    Tautges, T.J.; Liu, S.S.; Lu, Y.; Kraftcheck, J.; Gadh, R.

    1997-06-01

    The use of feature recognition as part of an overall decomposition-based hexahedral meshing approach is described in this paper. The meshing approach consists of feature recognition, using a c-loop or hybrid c-loop method, and the use of cutting surfaces to decompose the solid model. These steps are part of an iterative process, which proceeds either until no more features can be recognized or until the model has been completely decomposed into meshable sub-volumes. This method can greatly reduce the time required to generate an all-hexahedral mesh, either through the use of more efficient meshing algorithms on more of the geometry or by reducing the amount of manual decomposition required to mesh a volume.

  11. Attention, biological motion, and action recognition.

    PubMed

    Thompson, James; Parasuraman, Raja

    2012-01-01

    Interacting with others in the environment requires that we perceive and recognize their movements and actions. Neuroimaging and neuropsychological studies have indicated that a number of brain regions, particularly the superior temporal sulcus, are involved in a number of processes essential for action recognition, including the processing of biological motion and processing the intentions of actions. We review the behavioral and neuroimaging evidence suggesting that while some aspects of action recognition might be rapid and effective, they are not necessarily automatic. Attention is particularly important when visual information about actions is degraded or ambiguous, or if competing information is present. We present evidence indicating that neural responses associated with the processing of biological motion are strongly modulated by attention. In addition, behavioral and neuroimaging evidence shows that drawing inferences from the actions of others is attentionally demanding. The role of attention in action observation has implications for everyday social interactions and workplace applications that depend on observing, understanding and interpreting actions. PMID:21640836

  12. Photoswitchable gel assembly based on molecular recognition.

    PubMed

    Yamaguchi, Hiroyasu; Kobayashi, Yuichiro; Kobayashi, Ryosuke; Takashima, Yoshinori; Hashidzume, Akihito; Harada, Akira

    2012-01-03

    The formation of effective and precise linkages in bottom-up or top-down processes is important for the development of self-assembled materials. Self-assembly through molecular recognition events is a powerful tool for producing functionalized materials. Photoresponsive molecular recognition systems can permit the creation of photoregulated self-assembled macroscopic objects. Here we demonstrate that macroscopic gel assembly can be highly regulated through photoisomerization of an azobenzene moiety that interacts differently with two host molecules. A photoregulated gel assembly system is developed using polyacrylamide-based hydrogels functionalized with azobenzene (guest) or cyclodextrin (host) moieties. Reversible adhesion and dissociation of the host gel from the guest gel may be controlled by photoirradiation. The differential affinities of α-cyclodextrin or β-cyclodextrin for the trans-azobenzene and cis-azobenzene are employed in the construction of a photoswitchable gel assembly system.

  13. Photoswitchable gel assembly based on molecular recognition

    PubMed Central

    Yamaguchi, Hiroyasu; Kobayashi, Yuichiro; Kobayashi, Ryosuke; Takashima, Yoshinori; Hashidzume, Akihito; Harada, Akira

    2012-01-01

    The formation of effective and precise linkages in bottom-up or top-down processes is important for the development of self-assembled materials. Self-assembly through molecular recognition events is a powerful tool for producing functionalized materials. Photoresponsive molecular recognition systems can permit the creation of photoregulated self-assembled macroscopic objects. Here we demonstrate that macroscopic gel assembly can be highly regulated through photoisomerization of an azobenzene moiety that interacts differently with two host molecules. A photoregulated gel assembly system is developed using polyacrylamide-based hydrogels functionalized with azobenzene (guest) or cyclodextrin (host) moieties. Reversible adhesion and dissociation of the host gel from the guest gel may be controlled by photoirradiation. The differential affinities of α-cyclodextrin or β-cyclodextrin for the trans-azobenzene and cis-azobenzene are employed in the construction of a photoswitchable gel assembly system. PMID:22215078

  14. Average Gait Differential Image Based Human Recognition

    PubMed Central

    Chen, Jinyan; Liu, Jiansheng

    2014-01-01

    The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI) is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI), AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA) is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition. PMID:24895648

  15. Automatic stereoscopic system for person recognition

    NASA Astrophysics Data System (ADS)

    Murynin, Alexander B.; Matveev, Ivan A.; Kuznetsov, Victor D.

    1999-06-01

    A biometric access control system based on identification of human face is presented. The system developed performs remote measurements of the necessary face features. Two different scenarios of the system behavior are implemented. The first one assumes the verification of personal data entered by visitor from console using keyboard or card reader. The system functions as an automatic checkpoint, that strictly controls access of different visitors. The other scenario makes it possible to identify visitors without any person identifier or pass. Only person biometrics are used to identify the visitor. The recognition system automatically finds necessary identification information preliminary stored in the database. Two laboratory models of recognition system were developed. The models are designed to use different information types and sources. In addition to stereoscopic images inputted to computer from cameras the models can use voice data and some person physical characteristics such as person's height, measured by imaging system.

  16. Photonics: From target recognition to lesion detection

    NASA Technical Reports Server (NTRS)

    Henry, E. Michael

    1994-01-01

    Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

  17. Nickel recognition by bacterial importer proteins.

    PubMed

    Chivers, Peter T

    2015-04-01

    Nickel supports the growth of microbes from a variety of very different growth environments that affect nickel speciation. The mechanisms of nickel uptake and the molecular bases for the selectivity of this process are emerging. The recent surge of Ni-importer protein structures provides an understanding of Ni-recognition in the initial binding step of the import process. This review compares the structural basis for Ni-recognition in the complexes (ABC and ECF-type) that dominate primary (ATP-dependent) transport, with a focus on how the structures suggest mechanisms for Ni selectivity. The structures raise key questions about the mechanisms of nickel-transfer reactions involved in import. There is also a discussion of key experimental approaches necessary to help establish the physiological importance of these structures.

  18. Mental transformation in a visual recognition task.

    PubMed

    Bartusevicius, E; Vanagas, V; Radil-Weiss, T

    1981-01-01

    Rectangular geometrical patterns with equal number of lines, identical relations between their vertical and horizontal components, identical angles, line crossing knots and free ends of lines were presented tachistoscopically to human subjects with a restricted recognition time caused by backward masking. Symmetrical linear transformation with respect to the Y or X axes and rotations of the patterns were performed and the correctness of their reproduction was measured in psychophysical experiments. A mental pattern transformation was a fast operation (under 100 ms) not directly linked to a graphic or a verbal expression of the results of reproduction. Mental transformation is probably determined by the recognition process. Symmetrical transformations are easier than rotational, whereas the most difficult is a detection of a pattern differing in its form from those considered within a predetermined group of samples.

  19. Word recognition performance in various background competitors.

    PubMed

    Sperry, J L; Wiley, T L; Chial, M R

    1997-04-01

    Word recognition performance was measured for 18 normal-hearing subjects using the female talker version of the Northwestern University Auditory Test No. 6 (NU-6) in the presence of three background competitors: (1) a meaningful multitalker competing message consisting of three male and three female talkers (forward multitalker competing message [FCM]), (2) the same multitalker competing message recorded in reverse to eliminate semantic content (backward multitalker competing message [BCM]), and (3) an amplitude-modulated speech-spectrum noise (SSN) having the same long-term average spectrum and amplitude fluctuations as the meaningful multitalker competing message. The meaningful competitor had a significantly more deleterious effect on recognition performance compared to performance for the two nonmeaningful competitors. Furthermore, the nonmeaningful speech competitor produced a significantly greater degradation in performance than that for the SSN.

  20. Employee recognition: a key to motivation.

    PubMed

    Magnus, M

    1981-02-01

    Productivity--why it's low and how to enhance it--is on everyone's mind these days. A major component of productivity is employee satisfaction. If an employee is dissatisfied, feels unappreciated or under-compensated, that employee will not perform to the best of his or her ability. How is the personnel administrator to address this pressing problem? One answer that emerges is employee recognition programs. In many cases, properly run recognition programs can boost awareness of the organization, build employee pride, raise morale and, ultimately, increase productivity. As some of our respondents observed, higher salary is not the best answer. While a larger paycheck is always appreciated, everyone's pride is boosted by a public demonstration of appreciation.

  1. Supramolecular Polymerization Engineered with Molecular Recognition.

    PubMed

    Haino, Takeharu

    2015-10-01

    Supramolecular polymeric assemblies represent an emerging, promising class of molecular assemblies with enormous versatility compared with their covalent polymeric counterparts. Although a large number of host-guest motifs have been produced over the history of supramolecular chemistry, only a limited number of recognition motifs have been utilized as supramolecular connections in polymeric assemblies. This account describes the molecular recognition of host molecules based on calix[5]arene and bisporphyrin that demonstrate unique guest encapsulations; subsequently, these host-guest motifs are applied to the synthesis of supramolecular polymers that display polymer-like properties in solution and solid states. In addition, new bisresorcinarenes are developed to form supramolecular polymers that are connected via a rim-to-rim hydrogen-bonded dimeric structure, which is composed of two resorcinarene moieties. PMID:26178364

  2. Pattern-recognition receptors in pulp defense.

    PubMed

    Staquet, M-J; Carrouel, F; Keller, J-F; Baudouin, C; Msika, P; Bleicher, F; Kufer, T A; Farges, J-C

    2011-07-01

    Initial sensing of infection is mediated by germline-encoded pattern-recognition receptors (PRRs), the activation of which leads to the expression of inflammatory mediators responsible for the elimination of pathogens and infected cells. PRRs act as immune sensors that provide immediate cell responses to pathogen invasion or tissue injury. Here, we review the expression of PRRs in human dental pulp cells, namely, receptors from the Toll-like (TLR) and Nod-like NLR families, by which cells recognize bacteria. Particular attention is given to odontoblasts, which are the first cells encountered by pathogens and represent, in the tooth, the first line of defense for the host. Understanding cellular and molecular mechanisms associated with the recognition of bacterial pathogens by odontoblasts is critical for the development of therapeutic strategies that aim at preventing excessive pulp inflammation and related deleterious effects.

  3. Pattern recognition and control in manipulation

    NASA Technical Reports Server (NTRS)

    Bejczy, A. K.; Tomovic, R.

    1976-01-01

    A new approach to the use of sensors in manipulator or robot control is discussed. The concept addresses the problem of contact or near-contact type of recognition of three-dimensional forms of objects by proprioceptive and/or exteroceptive sensors integrated with the terminal device. This recognition of object shapes both enhances and simplifies the automation of object handling. Several examples have been worked out for the 'Belgrade hand' and for a parallel jaw terminal device, both equipped with proprioceptive (position) and exteroceptive (proximity) sensors. The control applications are discussed in the framework of a multilevel man-machine system control. The control applications create interesting new issues which, in turn, invite novel theoretical considerations. An important issue is the problem of stability in control when the control is referenced to patterns.

  4. Recognition of online handwritten mathematical expressions.

    PubMed

    Garain, Utpal; Chaudhuri, B B

    2004-12-01

    This paper aims at automatic understanding of online handwritten mathematical expressions (MEs) written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. Combination of two different classifiers have been used to achieve high accuracy for the recognition of symbols. Several online and offline features are used in the structural analysis phase to identify the spatial relationships among symbols. A context-free grammar has been designed to convert the input expressions into their corresponding T(E)X strings which are subsequently converted into MathML format. Contextual information has been used to correct several structure interpretation errors. A new method for evaluating performance of the proposed system has been formulated. Experiments on a dataset of considerable size strongly support the feasibility of the proposed system. PMID:15619936

  5. Recognition of online handwritten mathematical expressions.

    PubMed

    Garain, Utpal; Chaudhuri, B B

    2004-12-01

    This paper aims at automatic understanding of online handwritten mathematical expressions (MEs) written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. Combination of two different classifiers have been used to achieve high accuracy for the recognition of symbols. Several online and offline features are used in the structural analysis phase to identify the spatial relationships among symbols. A context-free grammar has been designed to convert the input expressions into their corresponding T(E)X strings which are subsequently converted into MathML format. Contextual information has been used to correct several structure interpretation errors. A new method for evaluating performance of the proposed system has been formulated. Experiments on a dataset of considerable size strongly support the feasibility of the proposed system.

  6. Enhanced kin recognition through population estimation.

    PubMed

    Krupp, Daniel Brian; Taylor, Peter D

    2013-05-01

    Kin recognition systems enable organisms to predict genetic relatedness. In so doing, they help to maximize the fitness consequences of social actions. Recognition based on phenotypic similarity-a process known as phenotype matching-is thought to depend upon information about one's own phenotype and the phenotypes of one's partners. We provide a simple model of genetic relatedness conditioned upon phenotypic information, however, that demonstrates that individuals additionally require estimates of the distributions of phenotypes and genotypes in the population. Following the results of our model, we develop an expanded concept of phenotype matching that brings relatedness judgments closer in line with relatedness as it is currently understood and provides a heuristic mechanism by which individuals can discriminate positive from negative relatives, thereby increasing opportunities for the evolution of altruism and spite. Finally, we propose ways in which organisms might acquire population estimates and identify research that supports their use in phenotype matching.

  7. Photoswitchable gel assembly based on molecular recognition.

    PubMed

    Yamaguchi, Hiroyasu; Kobayashi, Yuichiro; Kobayashi, Ryosuke; Takashima, Yoshinori; Hashidzume, Akihito; Harada, Akira

    2012-01-01

    The formation of effective and precise linkages in bottom-up or top-down processes is important for the development of self-assembled materials. Self-assembly through molecular recognition events is a powerful tool for producing functionalized materials. Photoresponsive molecular recognition systems can permit the creation of photoregulated self-assembled macroscopic objects. Here we demonstrate that macroscopic gel assembly can be highly regulated through photoisomerization of an azobenzene moiety that interacts differently with two host molecules. A photoregulated gel assembly system is developed using polyacrylamide-based hydrogels functionalized with azobenzene (guest) or cyclodextrin (host) moieties. Reversible adhesion and dissociation of the host gel from the guest gel may be controlled by photoirradiation. The differential affinities of α-cyclodextrin or β-cyclodextrin for the trans-azobenzene and cis-azobenzene are employed in the construction of a photoswitchable gel assembly system. PMID:22215078

  8. Pyroelectric linear array sensor for object recognition

    NASA Astrophysics Data System (ADS)

    Chari, Srikant; Jacobs, Eddie L.; Choudhary, Divya

    2014-02-01

    This paper presents a proof of concept sensor system based on a linear array of pyroelectric detectors for recognition of moving objects. The utility of this prototype sensor is demonstrated by its use in trail monitoring and perimeter protection applications for classifying humans against animals with object motion transverse to the field of view of the sensor array. Data acquisition using the system was performed under varied terrains and using a wide variety of animals and humans. With the objective of eventually porting the algorithms onto a low resource computational platform, simple signal processing, feature extraction, and classification techniques are used. The object recognition algorithm uses a combination of geometrical and texture features to provide limited insensitivity to range and speed. Analysis of system performance shows its effectiveness in discriminating humans and animals with high classification accuracy.

  9. White matter tracts critical for recognition of sarcasm.

    PubMed

    Davis, Cameron L; Oishi, Kenichi; Faria, Andreia V; Hsu, John; Gomez, Yessenia; Mori, Susumu; Hillis, Argye E

    2016-01-01

    Failure to recognize sarcasm can lead to important miscommunications. Few previous studies have identified brain lesions associated with impaired recognition of sarcasm. We tested the hypothesis that percent damage to specific white matter tracts, age, and education together predict accuracy in sarcasm recognition. Using multivariable linear regression, with age, education, and percent damage to each of eight white matter tracts as independent variables, and percent accuracy on sarcasm recognition as the dependent variable, we developed a model for predicting sarcasm recognition. Percent damage to the sagittal stratum had the greatest weight and was the only independent predictor of sarcasm recognition.

  10. Combined Hand Gesture — Speech Model for Human Action Recognition

    PubMed Central

    Cheng, Sheng-Tzong; Hsu, Chih-Wei; Li, Jian-Pan

    2013-01-01

    This study proposes a dynamic hand gesture detection technology to effectively detect dynamic hand gesture areas, and a hand gesture recognition technology to improve the dynamic hand gesture recognition rate. Meanwhile, the corresponding relationship between state sequences in hand gesture and speech models is considered by integrating speech recognition technology with a multimodal model, thus improving the accuracy of human behavior recognition. The experimental results proved that the proposed method can effectively improve human behavior recognition accuracy and the feasibility of system applications. Experimental results verified that the multimodal gesture-speech model provided superior accuracy when compared to the single modal versions. PMID:24351628

  11. Event identification by acoustic signature recognition

    SciTech Connect

    Dress, W.B.; Kercel, S.W.

    1995-07-01

    Many events of interest to the security commnnity produce acoustic emissions that are, in principle, identifiable as to cause. Some obvious examples are gunshots, breaking glass, takeoffs and landings of small aircraft, vehicular engine noises, footsteps (high frequencies when on gravel, very low frequencies. when on soil), and voices (whispers to shouts). We are investigating wavelet-based methods to extract unique features of such events for classification and identification. We also discuss methods of classification and pattern recognition specifically tailored for acoustic signatures obtained by wavelet analysis. The paper is divided into three parts: completed work, work in progress, and future applications. The completed phase has led to the successful recognition of aircraft types on landing and takeoff. Both small aircraft (twin-engine turboprop) and large (commercial airliners) were included in the study. The project considered the design of a small, field-deployable, inexpensive device. The techniques developed during the aircraft identification phase were then adapted to a multispectral electromagnetic interference monitoring device now deployed in a nuclear power plant. This is a general-purpose wavelet analysis engine, spanning 14 octaves, and can be adapted for other specific tasks. Work in progress is focused on applying the methods previously developed to speaker identification. Some of the problems to be overcome include recognition of sounds as voice patterns and as distinct from possible background noises (e.g., music), as well as identification of the speaker from a short-duration voice sample. A generalization of the completed work and the work in progress is a device capable of classifying any number of acoustic events-particularly quasi-stationary events such as engine noises and voices and singular events such as gunshots and breaking glass. We will show examples of both kinds of events and discuss their recognition likelihood.

  12. Biochip microsystem for bioinformatics recognition and analysis

    NASA Technical Reports Server (NTRS)

    Lue, Jaw-Chyng (Inventor); Fang, Wai-Chi (Inventor)

    2011-01-01

    A system with applications in pattern recognition, or classification, of DNA assay samples. Because DNA reference and sample material in wells of an assay may be caused to fluoresce depending upon dye added to the material, the resulting light may be imaged onto an embodiment comprising an array of photodetectors and an adaptive neural network, with applications to DNA analysis. Other embodiments are described and claimed.

  13. New FASB standard addresses revenue recognition considerations.

    PubMed

    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.

  14. VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Lue, Jaw-Chyng

    2009-01-01

    A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

  15. A Fuzzy Aproach For Facial Emotion Recognition

    NASA Astrophysics Data System (ADS)

    Gîlcă, Gheorghe; Bîzdoacă, Nicu-George

    2015-09-01

    This article deals with an emotion recognition system based on the fuzzy sets. Human faces are detected in images with the Viola - Jones algorithm and for its tracking in video sequences we used the Camshift algorithm. The detected human faces are transferred to the decisional fuzzy system, which is based on the variable fuzzyfication measurements of the face: eyebrow, eyelid and mouth. The system can easily determine the emotional state of a person.

  16. Recognition of psychotherapy effectiveness: the APA resolution.

    PubMed

    Campbell, Linda F; Norcross, John C; Vasquez, Melba J T; Kaslow, Nadine J

    2013-03-01

    In August 2012, the American Psychological Association (APA) Council of Representatives voted overwhelmingly to adopt as APA policy a Resolution on the Recognition of Psychotherapy Effectiveness. This invited article traces the origins and intentions of that resolution and its protracted journey through the APA governance labyrinth. We summarize the planned dissemination and projected results of the resolution and identify several lessons learned through the entire process.

  17. Motivation of animal care technicians through recognition.

    PubMed

    Symonowicz, Cammie; Critelli, Linda; Straeter, Pamela

    2006-01-01

    Keeping employees motivated is a challenge faced by managers in the field of laboratory animal science and in the business world at large. Using Maslow's 'Hierarchy of Needs' theory as a guide, the authors describe how managers can create a recognition program to keep employees feeling happy and rewarded. They discuss programs used at Bristol-Myers Squibb and share lessons learned from various programs.

  18. Speech Recognition in Natural Background Noise

    PubMed Central

    Meyer, Julien; Dentel, Laure; Meunier, Fanny

    2013-01-01

    In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR). Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A), reference at 1 meter) at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (−8.8 dB to −18.4 dB). Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda). Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for future studies

  19. Gait recognition based on Kinect sensor

    NASA Astrophysics Data System (ADS)

    Ahmed, Mohammed; Al-Jawad, Naseer; Sabir, Azhin T.

    2014-05-01

    This paper presents gait recognition based on human skeleton and trajectory of joint points captured by Microsoft Kinect sensor. In this paper Two sets of dynamic features are extracted during one gait cycle: the first is Horizontal Distance Features (HDF) that is based on the distances between (Ankles, knees, hands, shoulders), the second set is the Vertical Distance Features (VDF) that provide significant information of human gait extracted from the height to the ground of (hand, shoulder, and ankles) during one gait cycle. Extracting these two sets of feature are difficult and not accurate based on using traditional camera, therefore the Kinect sensor is used in this paper to determine the precise measurements. The two sets of feature are separately tested and then fused to create one feature vector. A database has been created in house to perform our experiments. This database consists of sixteen males and four females. For each individual, 10 videos have been recorded, each record includes in average two gait cycles. The Kinect sensor is used here to extract all the skeleton points, and these points are used to build up the feature vectors mentioned above. K-nearest neighbor is used as the classification method based on Cityblock distance function. Based on the experimental result the proposed method provides 56% as a recognition rate using HDF, while VDF provided 83.5% recognition accuracy. When fusing both of the HDF and VDF as one feature vector, the recognition rate increased to 92%, the experimental result shows that our method provides significant result compared to the existence methods.

  20. The Magnet Nursing Services Recognition Program

    PubMed Central

    Aiken, Linda H.; Havens, Donna S.; Sloane, Douglas M.

    2015-01-01

    OVERVIEW In an environment rife with controversy about patient safety in hospitals, medical error rates, and nursing shortages, consumers need to know how good the care is at their local hospitals. Nursing’s best kept secret is the single most effective mechanism for providing that type of comparative information to consumers, a seal of approval for quality nursing care: designation of magnet hospital status by the American Nurses Credentialing Center (ANCC). Magnet designation, or recognition of the “best” hospitals, was conceived in the early 1980s when the American Academy of Nursing (AAN) conducted a study to identify which hospitals attracted and retained nurses and which organizational features were shared by these successful hospitals, referred to as magnet hospitals. In the 1990s, the American Nurses Association (ANA), through the ANCC, established a formal program to acknowledge excellence in nursing services: the Magnet Nursing Services Recognition Program. The purpose of the current study is to examine whether hospitals selected for recognition by the ANCC application process—ANCC-accredited hospitals—are as successful in creating environments in which excellent nursing care is provided as the original AAN magnet hospitals were. We found that at ANCC-recognized magnet hospitals nurses had lower burnout rates and higher levels of job satisfaction and gave the quality of care provided at their hospitals higher ratings than did nurses at the AAN magnet hospitals. Our findings validate the ability of the Magnet Nursing Services Recognition Program to successfully identify hospitals that provide high-quality nursing care. PMID:19641439

  1. Mapping the development of facial expression recognition.

    PubMed

    Rodger, Helen; Vizioli, Luca; Ouyang, Xinyi; Caldara, Roberto

    2015-11-01

    Reading the non-verbal cues from faces to infer the emotional states of others is central to our daily social interactions from very early in life. Despite the relatively well-documented ontogeny of facial expression recognition in infancy, our understanding of the development of this critical social skill throughout childhood into adulthood remains limited. To this end, using a psychophysical approach we implemented the QUEST threshold-seeking algorithm to parametrically manipulate the quantity of signals available in faces normalized for contrast and luminance displaying the six emotional expressions, plus neutral. We thus determined observers' perceptual thresholds for effective discrimination of each emotional expression from 5 years of age up to adulthood. Consistent with previous studies, happiness was most easily recognized with minimum signals (35% on average), whereas fear required the maximum signals (97% on average) across groups. Overall, recognition improved with age for all expressions except happiness and fear, for which all age groups including the youngest remained within the adult range. Uniquely, our findings characterize the recognition trajectories of the six basic emotions into three distinct groupings: expressions that show a steep improvement with age - disgust, neutral, and anger; expressions that show a more gradual improvement with age - sadness, surprise; and those that remain stable from early childhood - happiness and fear, indicating that the coding for these expressions is already mature by 5 years of age. Altogether, our data provide for the first time a fine-grained mapping of the development of facial expression recognition. This approach significantly increases our understanding of the decoding of emotions across development and offers a novel tool to measure impairments for specific facial expressions in developmental clinical populations.

  2. New FASB standard addresses revenue recognition considerations.

    PubMed

    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. PMID:26793947

  3. Characterizing ultrasonic transducers using pattern recognition techniques

    SciTech Connect

    Ekis, J.W.

    1992-04-01

    This project's goal was to develop an automated ultrasonic transducer characterization system. A computer-based test system collected the test data for each of the given transducers. This data set was then processed by a number of pattern recognition algorithms. The results from these classifications placed the transducers into groups of similar units. All the transducers in a group will have similar performance characteristics. Each group was isolated from the others. 49 refs.

  4. Securing iris recognition systems against masquerade attacks

    NASA Astrophysics Data System (ADS)

    Galbally, Javier; Gomez-Barrero, Marta; Ross, Arun; Fierrez, Julian; Ortega-Garcia, Javier

    2013-05-01

    A novel two-stage protection scheme for automatic iris recognition systems against masquerade attacks carried out with synthetically reconstructed iris images is presented. The method uses different characteristics of real iris images to differentiate them from the synthetic ones, thereby addressing important security flaws detected in state-of-the-art commercial systems. Experiments are carried out on the publicly available Biosecure Database and demonstrate the efficacy of the proposed security enhancing approach.

  5. Mapping the development of facial expression recognition.

    PubMed

    Rodger, Helen; Vizioli, Luca; Ouyang, Xinyi; Caldara, Roberto

    2015-11-01

    Reading the non-verbal cues from faces to infer the emotional states of others is central to our daily social interactions from very early in life. Despite the relatively well-documented ontogeny of facial expression recognition in infancy, our understanding of the development of this critical social skill throughout childhood into adulthood remains limited. To this end, using a psychophysical approach we implemented the QUEST threshold-seeking algorithm to parametrically manipulate the quantity of signals available in faces normalized for contrast and luminance displaying the six emotional expressions, plus neutral. We thus determined observers' perceptual thresholds for effective discrimination of each emotional expression from 5 years of age up to adulthood. Consistent with previous studies, happiness was most easily recognized with minimum signals (35% on average), whereas fear required the maximum signals (97% on average) across groups. Overall, recognition improved with age for all expressions except happiness and fear, for which all age groups including the youngest remained within the adult range. Uniquely, our findings characterize the recognition trajectories of the six basic emotions into three distinct groupings: expressions that show a steep improvement with age - disgust, neutral, and anger; expressions that show a more gradual improvement with age - sadness, surprise; and those that remain stable from early childhood - happiness and fear, indicating that the coding for these expressions is already mature by 5 years of age. Altogether, our data provide for the first time a fine-grained mapping of the development of facial expression recognition. This approach significantly increases our understanding of the decoding of emotions across development and offers a novel tool to measure impairments for specific facial expressions in developmental clinical populations. PMID:25704672

  6. Personal recognition using hand shape and texture.

    PubMed

    Kumar, Ajay; Zhang, David

    2006-08-01

    This paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), k-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems. PMID:16900698

  7. Very low resolution face recognition problem.

    PubMed

    Zou, Wilman W W; Yuen, Pong C

    2012-01-01

    This paper addresses the very low resolution (VLR) problem in face recognition in which the resolution of the face image to be recognized is lower than 16 × 16. With the increasing demand of surveillance camera-based applications, the VLR problem happens in many face application systems. Existing face recognition algorithms are not able to give satisfactory performance on the VLR face image. While face super-resolution (SR) methods can be employed to enhance the resolution of the images, the existing learning-based face SR methods do not perform well on such a VLR face image. To overcome this problem, this paper proposes a novel approach to learn the relationship between the high-resolution image space and the VLR image space for face SR. Based on this new approach, two constraints, namely, new data and discriminative constraints, are designed for good visuality and face recognition applications under the VLR problem, respectively. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases. PMID:21775262

  8. Quantifying facial expression recognition across viewing conditions.

    PubMed

    Goren, Deborah; Wilson, Hugh R

    2006-04-01

    Facial expressions are key to social interactions and to assessment of potential danger in various situations. Therefore, our brains must be able to recognize facial expressions when they are transformed in biologically plausible ways. We used synthetic happy, sad, angry and fearful faces to determine the amount of geometric change required to recognize these emotions during brief presentations. Five-alternative forced choice conditions involving central viewing, peripheral viewing and inversion were used to study recognition among the four emotions. Two-alternative forced choice was used to study affect discrimination when spatial frequency information in the stimulus was modified. The results show an emotion and task-dependent pattern of detection. Facial expressions presented with low peak frequencies are much harder to discriminate from neutral than faces defined by either mid or high peak frequencies. Peripheral presentation of faces also makes recognition much more difficult, except for happy faces. Differences between fearful detection and recognition tasks are probably due to common confusions with sadness when recognizing fear from among other emotions. These findings further support the idea that these emotions are processed separately from each other. PMID:16364393

  9. Spectral face recognition using orthogonal subspace bases

    NASA Astrophysics Data System (ADS)

    Wimberly, Andrew; Robila, Stefan A.; Peplau, Tansy

    2010-04-01

    We present an efficient method for facial recognition using hyperspectral imaging and orthogonal subspaces. Projecting the data into orthogonal subspaces has the advantage of compactness and reduction of redundancy. We focus on two approaches: Principal Component Analysis and Orthogonal Subspace Projection. Our work is separated in three stages. First, we designed an experimental setup that allowed us to create a hyperspectral image database of 17 subjects under different facial expressions and viewing angles. Second, we investigated approaches to employ spectral information for the generation of fused grayscale images. Third, we designed and tested a recognition system based on the methods described above. The experimental results show that spectral fusion leads to improvement of recognition accuracy when compared to regular imaging. The work expands on previous band extraction research and has the distinct advantage of being one of the first that combines spatial information (i.e. face characteristics) with spectral information. In addition, the techniques are general enough to accommodate differences in skin spectra.

  10. Emotion recognition (sometimes) depends on horizontal orientations

    PubMed Central

    Huynh, Carol M; Balas, Benjamin

    2014-01-01

    Face recognition depends critically on horizontal orientations (Goffaux & Dakin, 2010). Face images that lack horizontal features are harder to recognize than those that have that information preserved. Presently, we asked if facial emotional recognition also exhibits this dependency by asking observers to categorize orientation-filtered happy and sad expressions. Furthermore, we aimed to dissociate image-based orientation energy from object-based orientation by rotating images 90-degrees in the picture-plane. In our first experiment, we showed that the perception of emotional expression does depend on horizontal orientations and that object-based orientation constrained performance more than image-based orientation. In Experiment 2 we showed that mouth openness (i.e. open versus closed-mouths) also influenced the emotion-dependent reliance on horizontal information. Lastly, we describe a simple computational analysis that demonstrates that the impact of mouth openness was not predicted by variation in the distribution of orientation energy across horizontal and vertical orientation bands. Overall, our results suggest that emotion recognition does largely depend on horizontal information defined relative to the face, but that this bias is modulated by multiple factors that introduce variation in appearance across and within distinct emotions. PMID:24664854

  11. Gait Recognition and Walking Exercise Intensity Estimation

    PubMed Central

    Lin, Bor-Shing; Liu, Yu-Ting; Yu, Chu; Jan, Gene Eu; Hsiao, Bo-Tang

    2014-01-01

    Cardiovascular patients consult doctors for advice regarding regular exercise, whereas obese patients must self-manage their weight. Because a system for permanently monitoring and tracking patients’ exercise intensities and workouts is necessary, a system for recognizing gait and estimating walking exercise intensity was proposed. For gait recognition analysis, αβ filters were used to improve the recognition of athletic attitude. Furthermore, empirical mode decomposition (EMD) was used to filter the noise of patients’ attitude to acquire the Fourier transform energy spectrum. Linear discriminant analysis was then applied to this energy spectrum for training and recognition. When the gait or motion was recognized, the walking exercise intensity was estimated. In addition, this study addressed the correlation between inertia and exercise intensity by using the residual function of the EMD and quadratic approximation to filter the effect of the baseline drift integral of the acceleration sensor. The increase in the determination coefficient of the regression equation from 0.55 to 0.81 proved that the accuracy of the method for estimating walking exercise intensity proposed by Kurihara was improved in this study. PMID:24714057

  12. Molecular Recognition and Free Energy Simulations

    NASA Astrophysics Data System (ADS)

    Cannon, William Robert

    This dissertation describes the study of molecular recognition processes by free energy computer simulations. The introductory chapter briefly outlines the scientific development and significance of molecular recognition, and then describes statistical thermodynamic approaches to computer simulations. Chapter 1 analyzes the relationship of small guest molecules to a synthetic host in which one guest molecule is preorganized to be structurally complementary to the host while the second guest molecule must organize itself in order to obtain the same complementarity. The preferential recognition of imidazolidone over N,N^' -dimethylurea to the host is described in terms of the energetic cost of preorganizing the N,N^' -dimethylurea which can exist in several rotationally isomeric states. Chapter 2 describes the development of potential functions for molecular simulations and analyzes the structural, dynamic and thermodynamic aspects of sulfate anion solvation. Finally, chapter 3 describes the binding of sulfate anion to a periplasmic receptor and analyzes three mutants that have anomalous binding affinities for sulfate. Two of the mutants that have a greater than expected affinity for the anion are proposed to recognize and bind a water-anion complex rather than the anion alone, and the third mutant is proposed to have a dramatically decreased affinity for the anion due to steric and polarization effects.

  13. Face recognition: a model specific ability.

    PubMed

    Wilmer, Jeremy B; Germine, Laura T; Nakayama, Ken

    2014-01-01

    In our everyday lives, we view it as a matter of course that different people are good at different things. It can be surprising, in this context, to learn that most of what is known about cognitive ability variation across individuals concerns the broadest of all cognitive abilities; an ability referred to as general intelligence, general mental ability, or just g. In contrast, our knowledge of specific abilities, those that correlate little with g, is severely constrained. Here, we draw upon our experience investigating an exceptionally specific ability, face recognition, to make the case that many specific abilities could easily have been missed. In making this case, we derive key insights from earlier false starts in the measurement of face recognition's variation across individuals, and we highlight the convergence of factors that enabled the recent discovery that this variation is specific. We propose that the case of face recognition ability illustrates a set of tools and perspectives that could accelerate fruitful work on specific cognitive abilities. By revealing relatively independent dimensions of human ability, such work would enhance our capacity to understand the uniqueness of individual minds.

  14. Tracheal activity recognition based on acoustic signals.

    PubMed

    Olubanjo, Temiloluwa; Ghovanloo, Maysam

    2014-01-01

    Tracheal activity recognition can play an important role in continuous health monitoring for wearable systems and facilitate the advancement of personalized healthcare. Neck-worn systems provide access to a unique set of health-related data that other wearable devices simply cannot obtain. Activities including breathing, chewing, clearing the throat, coughing, swallowing, speech and even heartbeat can be recorded from around the neck. In this paper, we explore tracheal activity recognition using a combination of promising acoustic features from related work and apply simplistic classifiers including K-NN and Naive Bayes. For wearable systems in which low power consumption is of primary concern, we show that with a sub-optimal sampling rate of 16 kHz, we have achieved average classification results in the range of 86.6% to 87.4% using 1-NN, 3-NN, 5-NN and Naive Bayes. All classifiers obtained the highest recognition rate in the range of 97.2% to 99.4% for speech classification. This is promising to mitigate privacy concerns associated with wearable systems interfering with the user's conversations.

  15. Human body contour data based activity recognition.

    PubMed

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

    2013-01-01

    This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate. PMID:24111015

  16. Recognition of stereoscopic images among elderly people

    NASA Astrophysics Data System (ADS)

    Omori, Masako; Watanabe, Tomoyuki; Miyao, Masaru; Sato, Yuzo; Ishihara, Shin-fya

    2002-06-01

    We tested 130 subjects including elderly people using two types of stereogram. One was a 3D image of a repeating parallel pattern showing balloons, from a software program called Stretch Eye. This program adopts a shift method in which the balloons diverge just at the point that causes a single shift between the right and left eyes, so that they appear to be more distant than the monitor screen. The Stretch Eye image was shown on a color LCD. The other image was a paper stereogram. Both used the same image of balloons. Using these 2 types of 3D image, we analyzed the recognition of stereoscopic images among elderly people. The subjects were 130 people aged 18 to 86 years, including 60 people over 60 years of age. The subjects' visual functions of cataract cloudiness (CC) and pupil distance were measured. Comparisons were carried out for the two targets of the paper stereograms and color LCDs. Subjects were divided into four groups according to the severity of CC. Two-way ANOVA was used for the statistical analysis in order to compare the influence of the target types, age and cataract cloudiness on the ability, distance and time of stereoscopic recognition. In a two-way ANOVA, two kinds of dependant variables, recognized speed (RS) and recognized distance (RD) were used for the subjects' stereoscopic recognition performance.

  17. Emotion recognition in girls with conduct problems.

    PubMed

    Schwenck, Christina; Gensthaler, Angelika; Romanos, Marcel; Freitag, Christine M; Schneider, Wolfgang; Taurines, Regina

    2014-01-01

    A deficit in emotion recognition has been suggested to underlie conduct problems. Although several studies have been conducted on this topic so far, most concentrated on male participants. The aim of the current study was to compare recognition of morphed emotional faces in girls with conduct problems (CP) with elevated or low callous-unemotional (CU+ vs. CU-) traits and a matched healthy developing control group (CG). Sixteen girls with CP-CU+, 16 girls with CP-CU- and 32 controls (mean age: 13.23 years, SD=2.33 years) were included. Video clips with morphed faces were presented in two runs to assess emotion recognition. Multivariate analysis of variance with the factors group and run was performed. Girls with CP-CU- needed more time than the CG to encode sad, fearful, and happy faces and they correctly identified sadness less often. Girls with CP-CU+ outperformed the other groups in the identification of fear. Learning effects throughout runs were the same for all groups except that girls with CP-CU- correctly identified fear less often in the second run compared to the first run. Results need to be replicated with comparable tasks, which might result in subgroup-specific therapeutic recommendations. PMID:23568422

  18. Aerial Scene Recognition using Efficient Sparse Representation

    SciTech Connect

    Cheriyadat, Anil M

    2012-01-01

    Advanced scene recognition systems for processing large volumes of high-resolution aerial image data are in great demand today. However, automated scene recognition remains a challenging problem. Efficient encoding and representation of spatial and structural patterns in the imagery are key in developing automated scene recognition algorithms. We describe an image representation approach that uses simple and computationally efficient sparse code computation to generate accurate features capable of producing excellent classification performance using linear SVM kernels. Our method exploits unlabeled low-level image feature measurements to learn a set of basis vectors. We project the low-level features onto the basis vectors and use simple soft threshold activation function to derive the sparse features. The proposed technique generates sparse features at a significantly lower computational cost than other methods~\\cite{Yang10, newsam11}, yet it produces comparable or better classification accuracy. We apply our technique to high-resolution aerial image datasets to quantify the aerial scene classification performance. We demonstrate that the dense feature extraction and representation methods are highly effective for automatic large-facility detection on wide area high-resolution aerial imagery.

  19. Privacy protection schemes for fingerprint recognition systems

    NASA Astrophysics Data System (ADS)

    Marasco, Emanuela; Cukic, Bojan

    2015-05-01

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

  20. Human body contour data based activity recognition.

    PubMed

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

    2013-01-01

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

  1. Pattern Recognition in Pharmacokinetic Data Analysis.

    PubMed

    Gabrielsson, Johan; Meibohm, Bernd; Weiner, Daniel

    2016-01-01

    Pattern recognition is a key element in pharmacokinetic data analyses when first selecting a model to be regressed to data. We call this process going from data to insight and it is an important aspect of exploratory data analysis (EDA). But there are very few formal ways or strategies that scientists typically use when the experiment has been done and data collected. This report deals with identifying the properties of a kinetic model by dissecting the pattern that concentration-time data reveal. Pattern recognition is a pivotal activity when modeling kinetic data, because a rigorous strategy is essential for dissecting the determinants behind concentration-time courses. First, we extend a commonly used relationship for calculation of the number of potential model parameters by simultaneously utilizing all concentration-time courses. Then, a set of points to consider are proposed that specifically addresses exploratory data analyses, number of phases in the concentration-time course, baseline behavior, time delays, peak shifts with increasing doses, flip-flop phenomena, saturation, and other potential nonlinearities that an experienced eye catches in the data. Finally, we set up a series of equations related to the patterns. In other words, we look at what causes the shapes that make up the concentration-time course and propose a strategy to construct a model. By practicing pattern recognition, one can significantly improve the quality and timeliness of data analysis and model building. A consequence of this is a better understanding of the complete concentration-time profile.

  2. Video face recognition against a watch list

    NASA Astrophysics Data System (ADS)

    Abbas, Jehanzeb; Dagli, Charlie K.; Huang, Thomas S.

    2007-10-01

    Due to a large increase in the video surveillance data recently in an effort to maintain high security at public places, we need more robust systems to analyze this data and make tasks like face recognition a realistic possibility in challenging environments. In this paper we explore a watch-list scenario where we use an appearance based model to classify query faces from low resolution videos into either a watch-list or a non-watch-list face. We then use our simple yet a powerful face recognition system to recognize the faces classified as watch-list faces. Where the watch-list includes those people that we are interested in recognizing. Our system uses simple feature machine algorithms from our previous work to match video faces against still images. To test our approach, we match video faces against a large database of still images obtained from a previous work in the field from Yahoo News over a period of time. We do this matching in an efficient manner to come up with a faster and nearly real-time system. This system can be incorporated into a larger surveillance system equipped with advanced algorithms involving anomalous event detection and activity recognition. This is a step towards more secure and robust surveillance systems and efficient video data analysis.

  3. Verification watermarks on fingerprint recognition and retrieval

    NASA Astrophysics Data System (ADS)

    Yeung, Minerva M.; Pankanti, Sharatchandra

    2000-10-01

    Current `invisible' watermarking techniques aim at producing watermarked data that suffer no or little quality degradation and are perceptually identical to the original versions. The most common utility of a watermarked image is (1) for image viewing and display, and (2) for extracting the embedded watermark in subsequent copy protection applications. The issue is often centered on the robustness of the watermark for detection and extraction. In addition to robustness studies, a fundamental question will center on the utilization value of the watermarked images beyond perceptual quality evaluation. Essentially we have to study how the watermarks inserted affect the subsequent processing and utility of images, and what watermarking schemes we can develop that will cater to these processing tasks. This work focuses on the study of watermarking on images used in automatic personal identification technology based on fingerprints. We investigate the effects of watermarking fingerprint images on the recognition and retrieval accuracy using a proposed invisible fragile watermarking technique for image verification applications on a specific fingerprint recognition system. We shall also describe the watermarking scheme, fingerprint recognition and feature extraction techniques used. We believe that watermarking of images will provide value-added protection, as well as copyright notification capability, to the fingerprint data collection processes and subsequent usage.

  4. Verification watermarks on fingerprint recognition and retrieval

    NASA Astrophysics Data System (ADS)

    Pankanti, Sharatchandra; Yeung, Minerva M.

    1999-04-01

    Current 'invisible' watermarking techniques aim at producing watermarked data that suffer no or little quality degradation and perceptually identical to the original versions. The most common utility of a watermarked image is (1) for image viewing and display, and (2) for extracting the embedded watermark in subsequent copy protection applications. The issue is often centered on the robustness of the watermark for detection and extraction. In addition to robustness studies, a fundamental question will center on the utilization value of the watermarked images beyond perceptual quality evaluation. Essentially we have to study how the watermarks inserted affect the subsequent processing and utility of images, and what watermarking schemes we can develop that will cater to these processing tasks. This work focuses on the study of watermarking on images used in automatic personal identification technology based fingerprints. We investigate the effects of watermarking fingerprint images on the recognition and retrieval accuracy using a proposed invisible fragile watermarking technique for image verification applications on a specific fingerprint recognition system. We shall also describe the watermarking scheme, fingerprint recognition and feature extraction techniques used. We believe that watermarking of images will provided value-added protection, as well as copyright notification capability, to the fingerprint data collection processes and subsequent usage.

  5. Multimodal approaches for emotion recognition: a survey

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

  6. Multimodal approaches for emotion recognition: a survey

    NASA Astrophysics Data System (ADS)

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

    2005-01-01

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

  7. Image processing and recognition for biological images

    PubMed Central

    Uchida, Seiichi

    2013-01-01

    This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. PMID:23560739

  8. Genetic feature selection for gait recognition

    NASA Astrophysics Data System (ADS)

    Tafazzoli, Faezeh; Bebis, George; Louis, Sushil; Hussain, Muhammad

    2015-01-01

    Many research studies have demonstrated that gait can serve as a useful biometric modality for human identification at a distance. Traditional gait recognition systems, however, have mostly been evaluated without explicitly considering the most relevant gait features, which might have compromised performance. We investigate the problem of selecting a subset of the most relevant gait features for improving gait recognition performance. This is achieved by discarding redundant and irrelevant gait features while preserving the most informative ones. Motivated by our previous work on feature subset selection using genetic algorithms (GAs), we propose using GAs to select an optimal subset of gait features. First, features are extracted using kernel principal component analysis (KPCA) on spatiotemporal projections of gait silhouettes. Then, GA is applied to select a subset of eigenvectors in KPCA space that best represents a subject's identity. Each gait pattern is then represented by projecting it only on the eigenvectors selected by the GA. To evaluate the effectiveness of the selected features, we have experimented with two different classifiers: k nearest-neighbor and Naïve Bayes classifier. We report considerable gait recognition performance improvements on the Georgia Tech and CASIA databases.

  9. Antifungal innate immunity: recognition and inflammatory networks.

    PubMed

    Becker, Katharina L; Ifrim, Daniela C; Quintin, Jessica; Netea, Mihai G; van de Veerdonk, Frank L

    2015-03-01

    A large variety of fungi are present in the environment, among which a proportion colonizes the human body, usually without causing any harm. However, depending on the host immune status, commensals can become opportunistic pathogens that induce diseases ranging from superficial non-harmful infection to life-threatening systemic disease. The interplay between the host and the fungal commensal flora is being orchestrated by an efficient recognition of the microorganisms, which in turn ensures a proper balance between tolerance of the normal fungal flora and induction of immune defense mechanisms when invasion occurs. Pattern recognition receptors (PRRs) play a significant role in maintaining this balance due to their capacity to sense fungi and induce host responses such as the induction of proinflammatory cytokines involved in the activation of innate and adaptive immune responses. In the present review, we will discuss the most recent findings regarding the recognition of Candida albicans and Aspergillus fumigatus and the different types of immune cells that play a role in antifungal host defense. PMID:25527294

  10. Emotion recognition from speech: tools and challenges

    NASA Astrophysics Data System (ADS)

    Al-Talabani, Abdulbasit; Sellahewa, Harin; Jassim, Sabah A.

    2015-05-01

    Human emotion recognition from speech is studied frequently for its importance in many applications, e.g. human-computer interaction. There is a wide diversity and non-agreement about the basic emotion or emotion-related states on one hand and about where the emotion related information lies in the speech signal on the other side. These diversities motivate our investigations into extracting Meta-features using the PCA approach, or using a non-adaptive random projection RP, which significantly reduce the large dimensional speech feature vectors that may contain a wide range of emotion related information. Subsets of Meta-features are fused to increase the performance of the recognition model that adopts the score-based LDC classifier. We shall demonstrate that our scheme outperform the state of the art results when tested on non-prompted databases or acted databases (i.e. when subjects act specific emotions while uttering a sentence). However, the huge gap between accuracy rates achieved on the different types of datasets of speech raises questions about the way emotions modulate the speech. In particular we shall argue that emotion recognition from speech should not be dealt with as a classification problem. We shall demonstrate the presence of a spectrum of different emotions in the same speech portion especially in the non-prompted data sets, which tends to be more "natural" than the acted datasets where the subjects attempt to suppress all but one emotion.

  11. Making Activity Recognition Robust against Deceptive Behavior.

    PubMed

    Saeb, Sohrab; Körding, Konrad; Mohr, David C

    2015-01-01

    Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected from their activity tracking devices. Therefore, there is an increasing motivation for individuals to cheat, by making activity trackers detect activities that increase their benefits rather than the ones they actually do. In this study, we used a novel method to make activity recognition robust against deceptive behavior. We asked 14 subjects to attempt to trick our smartphone-based activity classifier by making it detect an activity other than the one they actually performed, for example by shaking the phone while seated to make the classifier detect walking. If they succeeded, we used their motion data to retrain the classifier, and asked them to try to trick it again. The experiment ended when subjects could no longer cheat. We found that some subjects were not able to trick the classifier at all, while others required five rounds of retraining. While classifiers trained on normal activity data predicted true activity with ~38% accuracy, training on the data gathered during the deceptive behavior increased their accuracy to ~84%. We conclude that learning the deceptive behavior of one individual helps to detect the deceptive behavior of others. Thus, we can make current activity recognition robust to deception by including deceptive activity data from a few individuals. PMID:26659118

  12. Maximum Correntropy Criterion for Robust Face Recognition.

    PubMed

    He, Ran; Zheng, Wei-Shi; Hu, Bao-Gang

    2011-08-01

    In this paper, we present a sparse correntropy framework for computing robust sparse representations of face images for recognition. Compared with the state-of-the-art l(1)norm-based sparse representation classifier (SRC), which assumes that noise also has a sparse representation, our sparse algorithm is developed based on the maximum correntropy criterion, which is much more insensitive to outliers. In order to develop a more tractable and practical approach, we in particular impose nonnegativity constraint on the variables in the maximum correntropy criterion and develop a half-quadratic optimization technique to approximately maximize the objective function in an alternating way so that the complex optimization problem is reduced to learning a sparse representation through a weighted linear least squares problem with nonnegativity constraint at each iteration. Our extensive experiments demonstrate that the proposed method is more robust and efficient in dealing with the occlusion and corruption problems in face recognition as compared to the related state-of-the-art methods. In particular, it shows that the proposed method can improve both recognition accuracy and receiver operator characteristic (ROC) curves, while the computational cost is much lower than the SRC algorithms.

  13. Face recognition: a model specific ability.

    PubMed

    Wilmer, Jeremy B; Germine, Laura T; Nakayama, Ken

    2014-01-01

    In our everyday lives, we view it as a matter of course that different people are good at different things. It can be surprising, in this context, to learn that most of what is known about cognitive ability variation across individuals concerns the broadest of all cognitive abilities; an ability referred to as general intelligence, general mental ability, or just g. In contrast, our knowledge of specific abilities, those that correlate little with g, is severely constrained. Here, we draw upon our experience investigating an exceptionally specific ability, face recognition, to make the case that many specific abilities could easily have been missed. In making this case, we derive key insights from earlier false starts in the measurement of face recognition's variation across individuals, and we highlight the convergence of factors that enabled the recent discovery that this variation is specific. We propose that the case of face recognition ability illustrates a set of tools and perspectives that could accelerate fruitful work on specific cognitive abilities. By revealing relatively independent dimensions of human ability, such work would enhance our capacity to understand the uniqueness of individual minds. PMID:25346673

  14. Children's recognition of emotions from vocal cues.

    PubMed

    Sauter, Disa A; Panattoni, Charlotte; Happé, Francesca

    2013-03-01

    Emotional cues contain important information about the intentions and feelings of others. Despite a wealth of research into children's understanding of facial signals of emotions, little research has investigated the developmental trajectory of interpreting affective cues in the voice. In this study, 48 children ranging between 5 and 10 years were tested using forced-choice tasks with non-verbal vocalizations and emotionally inflected speech expressing different positive, neutral and negative states. Children as young as 5 years were proficient in interpreting a range of emotional cues from vocal signals. Consistent with previous work, performance was found to improve with age. Furthermore, the two tasks, examining recognition of non-verbal vocalizations and emotionally inflected speech, respectively, were sensitive to individual differences, with high correspondence of performance across the tasks. From this demonstration of children's ability to recognize emotions from vocal stimuli, we also conclude that this auditory emotion recognition task is suitable for a wide age range of children, providing a novel, empirical way to investigate children's affect recognition skills. PMID:23331109

  15. Bilingual word recognition in a sentence context.

    PubMed

    Assche, Eva Van; Duyck, Wouter; Hartsuiker, Robert J

    2012-01-01

    This article provides an overview of bilingualism research on visual word recognition in isolation and in sentence context. Many studies investigating the processing of words out-of-context have shown that lexical representations from both languages are activated when reading in one language (language-non-selective lexical access). A newly developed research line asks whether language-non-selective access generalizes to word recognition in sentence contexts, providing a language cue and/or semantic constraint information for upcoming words. Recent studies suggest that the language of the preceding words is insufficient to restrict lexical access to words of the target language, even when reading in the native language. Eye tracking studies revealing the time course of word activation further showed that semantic constraint does not restrict language-non-selective access at early reading stages, but there is evidence that it has a relatively late effect. The theoretical implications for theories of bilingual word recognition are discussed in light of the Bilingual Interactive Activation+ model (Dijkstra and van Heuven, 2002).

  16. Odor recognition: familiarity, identifiability, and encoding consistency.

    PubMed

    Rabin, M D; Cain, W S

    1984-04-01

    The investigation examined the association between the perceived identity of odorous stimuli and the ability to recognize the previous occurrence of them. The stimuli comprised 20 relatively familiar odorous objects such as chocolate, leather, popcorn, and soy sauce. Participants rated the familiarity of the odors and sought to identify them. At various intervals up to 7 days after initial inspection, the participants sought to recognize the odors among sets of distractor odors that included such items as soap, cloves, pipe tobacco, and so on. The recognition response entailed a confidence rating as to whether or not an item had appeared in the original set. At the time of testing, the participants also sought to identify the stimuli again. The results upheld previous findings of excellent initial recognition memory for environmentally relevant odors and slow forgetting. The results also uncovered, for the first time, a strong association between recognition memory and identifiability, rated familiarity, and the ability to use an odor label consistently at inspection and subsequent testing. Encodability seems to enhance rather than to permit recognizability. Even items identified incorrectly or inconsistently were recognized at levels above chance.

  17. Visual place recognition with repetitive structures.

    PubMed

    Torii, Akihiko; Sivic, Josef; Okutomi, Masatoshi; Pajdla, Tomas

    2015-11-01

    Repeated structures such as building facades, fences or road markings often represent a significant challenge for place recognition. Repeated structures are notoriously hard for establishing correspondences using multi-view geometry. They violate the feature independence assumed in the bag-of-visual-words representation which often leads to over-counting evidence and significant degradation of retrieval performance. In this work we show that repeated structures are not a nuisance but, when appropriately represented, they form an important distinguishing feature for many places. We describe a representation of repeated structures suitable for scalable retrieval and geometric verification. The retrieval is based on robust detection of repeated image structures and a suitable modification of weights in the bag-of-visual-word model. We also demonstrate that the explicit detection of repeated patterns is beneficial for robust visual word matching for geometric verification. Place recognition results are shown on datasets of street-level imagery from Pittsburgh and San Francisco demonstrating significant gains in recognition performance compared to the standard bag-of-visual-words baseline as well as the more recently proposed burstiness weighting and Fisher vector encoding. PMID:26440272

  18. Making Activity Recognition Robust against Deceptive Behavior

    PubMed Central

    Saeb, Sohrab; Körding, Konrad; Mohr, David C.

    2015-01-01

    Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected from their activity tracking devices. Therefore, there is an increasing motivation for individuals to cheat, by making activity trackers detect activities that increase their benefits rather than the ones they actually do. In this study, we used a novel method to make activity recognition robust against deceptive behavior. We asked 14 subjects to attempt to trick our smartphone-based activity classifier by making it detect an activity other than the one they actually performed, for example by shaking the phone while seated to make the classifier detect walking. If they succeeded, we used their motion data to retrain the classifier, and asked them to try to trick it again. The experiment ended when subjects could no longer cheat. We found that some subjects were not able to trick the classifier at all, while others required five rounds of retraining. While classifiers trained on normal activity data predicted true activity with ~38% accuracy, training on the data gathered during the deceptive behavior increased their accuracy to ~84%. We conclude that learning the deceptive behavior of one individual helps to detect the deceptive behavior of others. Thus, we can make current activity recognition robust to deception by including deceptive activity data from a few individuals. PMID:26659118

  19. Restoration and recognition of distant, blurry irises.

    PubMed

    Stoker, David S; Wedd, Jonathan; Lavelle, Eric; van der Laan, Jan

    2013-03-20

    Raw iris images collected outdoors at standoff distances exceeding 25 m are susceptible to noise and atmospheric blur and even under ideal imaging conditions are too degraded to carry out recognition with high accuracy. Traditionally, atmospherically distorted images have been corrected through the use of unique hardware components such as adaptive optics. Here we apply a pure digital image restoration approach to correct for optical aberrations. Image restoration was applied to both single images and image sequences. We propose both a single-frame denoising and deblurring approach, and a multiframe fusion and deblurring approach. To compare performance of the proposed methods, iris recognitions were carried out using the approach of Daugman. Hamming distances (HDs) of computed binary iris codes were measured before and after the restoration. We found the HD decreased from >0.46 prior to a mean value of <0.39 for random single images. The multiframe fusion approach produced the most robust restoration and achieved a mean HD for all subjects in our data set of 0.33 while known false matches remained at 0.44. These results show that, when used properly, image restoration approaches do significantly increase recognition performance for known true positives with low increase in false positive detections, and irises can be recognized in turbulent atmospheric conditions. PMID:23518730

  20. Unconstrained handprint recognition using a limited lexicon

    NASA Astrophysics Data System (ADS)

    Garris, Michael D.

    1994-03-01

    A word recognition system has been developed at NIST to read free-formatted text paragraphs containing handprinted characters. The system has been developed and tested using binary images containing 2,100 different writers' printings of the Preamble to the U.S. Constitution. Each writer was asked to print these sentences in an empty 70 mm by 175 mm box. The Constitution box contains no guidelines for the placement and spacing of the handprinted text, nor are there guidelines to instruct the writer where to stop printing one line and to begin the next. While the layout of the handprint in these paragraphs is unconstrained, a limited-size lexicon may be applied to reduce the complexity of the recognition application. The system's four components have been combined into an end-to-end hybrid system that executes across a UNIX file server and a massively parallel SIMD computer. The recognition system achieves a word error rate of 49% across all 2,100 printings of the Preamble (109,096 words). This performance is achieved with a neural network character classifier that has a substitution error rate of 14% on its 22,823 training patterns.

  1. Face and body recognition show similar improvement during childhood.

    PubMed

    Bank, Samantha; Rhodes, Gillian; Read, Ainsley; Jeffery, Linda

    2015-09-01

    Adults are proficient in extracting identity cues from faces. This proficiency develops slowly during childhood, with performance not reaching adult levels until adolescence. Bodies are similar to faces in that they convey identity cues and rely on specialized perceptual mechanisms. However, it is currently unclear whether body recognition mirrors the slow development of face recognition during childhood. Recent evidence suggests that body recognition develops faster than face recognition. Here we measured body and face recognition in 6- and 10-year-old children and adults to determine whether these two skills show different amounts of improvement during childhood. We found no evidence that they do. Face and body recognition showed similar improvement with age, and children, like adults, were better at recognizing faces than bodies. These results suggest that the mechanisms of face and body memory mature at a similar rate or that improvement of more general cognitive and perceptual skills underlies improvement of both face and body recognition.

  2. Graded Effects of Social Conformity on Recognition Memory

    PubMed Central

    Axmacher, Nikolai; Gossen, Anna; Elger, Christian E.; Fell, Juergen

    2010-01-01

    Previous studies have shown that the opinion of confederates in a group influences recognition memory, but inconsistent results have been obtained concerning the question of whether recognition of items as old and new are affected similarly, possibly because only one or two confederates are present during the recognition phase. Here, we present data from a study where recognition of novel faces was tested in the presence of four confederates. In a long version of this experiment, recognition of items as old and new was similarly affected by group responses. However, in the short version, recognition of old items depended proportionally on the number of correct group responses, while rejection of new items only decreased significantly when all confederates gave an incorrect response. These findings indicate that differential effects of social conformity on recognition of items as old and new occur in situations with an intermediate level of group pressure. PMID:20174641

  3. A smoothness constraint on the development of object recognition.

    PubMed

    Wood, Justin N

    2016-08-01

    Understanding how the brain learns to recognize objects is one of the ultimate goals in the cognitive sciences. To date, however, we have not yet characterized the environmental factors that cause object recognition to emerge in the newborn brain. Here, I present the results of a high-throughput controlled-rearing experiment that examined whether the development of object recognition requires experience with temporally smooth visual objects. When newborn chicks (Gallus gallus) were raised with virtual objects that moved smoothly over time, the chicks developed accurate color recognition, shape recognition, and color-shape binding abilities. In contrast, when newborn chicks were raised with virtual objects that moved non-smoothly over time, the chicks' object recognition abilities were severely impaired. These results provide evidence for a "smoothness constraint" on newborn object recognition. Experience with temporally smooth objects facilitates the development of object recognition. PMID:27208825

  4. Improving robustness of speech recognition systems

    NASA Astrophysics Data System (ADS)

    Mitra, Vikramjit

    2010-11-01

    Current Automatic Speech Recognition (ASR) systems fail to perform nearly as good as human speech recognition performance due to their lack of robustness against speech variability and noise contamination. The goal of this dissertation is to investigate these critical robustness issues, put forth different ways to address them and finally present an ASR architecture based upon these robustness criteria. Acoustic variations adversely affect the performance of current phone-based ASR systems, in which speech is modeled as 'beads-on-a-string', where the beads are the individual phone units. While phone units are distinctive in cognitive domain, they are varying in the physical domain and their variation occurs due to a combination of factors including speech style, speaking rate etc.; a phenomenon commonly known as 'coarticulation'. Traditional ASR systems address such coarticulatory variations by using contextualized phone-units such as triphones. Articulatory phonology accounts for coarticulatory variations by modeling speech as a constellation of constricting actions known as articulatory gestures. In such a framework, speech variations such as coarticulation and lenition are accounted for by gestural overlap in time and gestural reduction in space. To realize a gesture-based ASR system, articulatory gestures have to be inferred from the acoustic signal. At the initial stage of this research an initial study was performed using synthetically generated speech to obtain a proof-of-concept that articulatory gestures can indeed be recognized from the speech signal. It was observed that having vocal tract constriction trajectories (TVs) as intermediate representation facilitated the gesture recognition task from the speech signal. Presently no natural speech database contains articulatory gesture annotation; hence an automated iterative time-warping architecture is proposed that can annotate any natural speech database with articulatory gestures and TVs. Two natural

  5. A modular framework for biomedical concept recognition

    PubMed Central

    2013-01-01

    Background Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Results This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88

  6. Behavioral model of visual perception and recognition

    NASA Astrophysics Data System (ADS)

    Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

    1993-09-01

    In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and

  7. The recognition of biomaterials: pattern recognition of medical polymers and their adsorbed biomolecules.

    PubMed

    Love, Ryan J; Jones, Kim S

    2013-09-01

    All biomedical materials are recognized as foreign entities by the host immune system despite the substantial range of different materials that have been developed by material scientists and engineers. Hydrophobic biomaterials, hydrogels, biomaterials with low protein binding surfaces, and those that readily adsorb a protein layer all seem to incite similar host responses in vivo that may differ in magnitude, but ultimately result in encapsulation by fibrotic tissue. The recognition of medical materials by the host is explained by the very intricate pattern recognition system made up of integrins, toll-like receptors, scavenger receptors, and other surface proteins that enable leukocytes to perceive almost any foreign body. In this review, we describe the various pattern recognition receptors and processes that occur on biomedical material surfaces that permit detection of a range of materials within the host.

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

    PubMed Central

    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. PMID:26346654

  9. Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

    NASA Astrophysics Data System (ADS)

    Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

    2006-05-01

    Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

  10. Structures of pattern recognition receptors reveal molecular mechanisms of autoinhibition, ligand recognition and oligomerization.

    PubMed

    Chuenchor, Watchalee; Jin, Tengchuan; Ravilious, Geoffrey; Xiao, T Sam

    2014-02-01

    Pattern recognition receptors (PRRs) are essential sentinels for pathogens or tissue damage and integral components of the innate immune system. Recent structural studies have provided unprecedented insights into the molecular mechanisms of ligand recognition and signal transduction by several PRR families at distinct subcellular compartments. Here we highlight some of the recent discoveries and summarize the common themes that are emerging from these exciting studies. Better mechanistic understanding of the structure and function of the PRRs will improve future prospects of therapeutic targeting of these important innate immune receptors.

  11. Facial emotion recognition impairments in individuals with HIV.

    PubMed

    Clark, Uraina S; Cohen, Ronald A; Westbrook, Michelle L; Devlin, Kathryn N; Tashima, Karen T

    2010-11-01

    Characterized by frontostriatal dysfunction, human immunodeficiency virus (HIV) is associated with cognitive and psychiatric abnormalities. Several studies have noted impaired facial emotion recognition abilities in patient populations that demonstrate frontostriatal dysfunction; however, facial emotion recognition abilities have not been systematically examined in HIV patients. The current study investigated facial emotion recognition in 50 nondemented HIV-seropositive adults and 50 control participants relative to their performance on a nonemotional landscape categorization control task. We examined the relation of HIV-disease factors (nadir and current CD4 levels) to emotion recognition abilities and assessed the psychosocial impact of emotion recognition abnormalities. Compared to control participants, HIV patients performed normally on the control task but demonstrated significant impairments in facial emotion recognition, specifically for fear. HIV patients reported greater psychosocial impairments, which correlated with increased emotion recognition difficulties. Lower current CD4 counts were associated with poorer anger recognition. In summary, our results indicate that chronic HIV infection may contribute to emotion processing problems among HIV patients. We suggest that disruptions of frontostriatal structures and their connections with cortico-limbic networks may contribute to emotion recognition abnormalities in HIV. Our findings also highlight the significant psychosocial impact that emotion recognition abnormalities have on individuals with HIV.

  12. [Face recognition in patients with autism spectrum disorders].

    PubMed

    Kita, Yosuke; Inagaki, Masumi

    2012-07-01

    The present study aimed to review previous research conducted on face recognition in patients with autism spectrum disorders (ASD). Face recognition is a key question in the ASD research field because it can provide clues for elucidating the neural substrates responsible for the social impairment of these patients. Historically, behavioral studies have reported low performance and/or unique strategies of face recognition among ASD patients. However, the performance and strategy of ASD patients is comparable to those of the control group, depending on the experimental situation or developmental stage, suggesting that face recognition of ASD patients is not entirely impaired. Recent brain function studies, including event-related potential and functional magnetic resonance imaging studies, have investigated the cognitive process of face recognition in ASD patients, and revealed impaired function in the brain's neural network comprising the fusiform gyrus and amygdala. This impaired function is potentially involved in the diminished preference for faces, and in the atypical development of face recognition, eliciting symptoms of unstable behavioral characteristics in these patients. Additionally, face recognition in ASD patients is examined from a different perspective, namely self-face recognition, and facial emotion recognition. While the former topic is intimately linked to basic social abilities such as self-other discrimination, the latter is closely associated with mentalizing. Further research on face recognition in ASD patients should investigate the connection between behavioral and neurological specifics in these patients, by considering developmental changes and the spectrum clinical condition of ASD.

  13. Aging and solid shape recognition: Vision and haptics.

    PubMed

    Norman, J Farley; Cheeseman, Jacob R; Adkins, Olivia C; Cox, Andrea G; Rogers, Connor E; Dowell, Catherine J; Baxter, Michael W; Norman, Hideko F; Reyes, Cecia M

    2015-10-01

    The ability of 114 younger and older adults to recognize naturally-shaped objects was evaluated in three experiments. The participants viewed or haptically explored six randomly-chosen bell peppers (Capsicum annuum) in a study session and were later required to judge whether each of twelve bell peppers was "old" (previously presented during the study session) or "new" (not presented during the study session). When recognition memory was tested immediately after study, the younger adults' (Experiment 1) performance for vision and haptics was identical when the individual study objects were presented once. Vision became superior to haptics, however, when the individual study objects were presented multiple times. When 10- and 20-min delays (Experiment 2) were inserted in between study and test sessions, no significant differences occurred between vision and haptics: recognition performance in both modalities was comparable. When the recognition performance of older adults was evaluated (Experiment 3), a negative effect of age was found for visual shape recognition (younger adults' overall recognition performance was 60% higher). There was no age effect, however, for haptic shape recognition. The results of the present experiments indicate that the visual recognition of natural object shape is different from haptic recognition in multiple ways: visual shape recognition can be superior to that of haptics and is affected by aging, while haptic shape recognition is less accurate and unaffected by aging.

  14. Laser range profiling for small target recognition

    NASA Astrophysics Data System (ADS)

    Steinvall, Ove; Tulldahl, Michael

    2016-05-01

    The detection and classification of small surface and airborne targets at long ranges is a growing need for naval security. Long range ID or ID at closer range of small targets has its limitations in imaging due to the demand on very high transverse sensor resolution. It is therefore motivated to look for 1D laser techniques for target ID. These include vibrometry, and laser range profiling. Vibrometry can give good results but is also sensitive to certain vibrating parts on the target being in the field of view. Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector. The same laser can also be used for active imaging when the target comes closer and is angular resolved. The present paper will show both experimental and simulated results for laser range profiling of small boats out to 6-7 km range and a UAV mockup at close range (1.3 km). We obtained good results with the profiling system both for target detection and recognition. Comparison of experimental and simulated range waveforms based on CAD models of the target support the idea of having a profiling system as a first recognition sensor and thus narrowing the search space for the automatic target recognition based on imaging at close ranges. The naval experiments took place in the Baltic Sea with many other active and passive EO sensors beside the profiling system. Discussion of data fusion between laser profiling and imaging systems will be given. The UAV experiments were made from the rooftop laboratory at FOI.

  15. Block error correction codes for face recognition

    NASA Astrophysics Data System (ADS)

    Hussein, Wafaa R.; Sellahewa, Harin; Jassim, Sabah A.

    2011-06-01

    Face recognition is one of the most desirable biometric-based authentication schemes to control access to sensitive information/locations and as a proof of identity to claim entitlement to services. The aim of this paper is to develop block-based mechanisms, to reduce recognition errors that result from varying illumination conditions with emphasis on using error correction codes. We investigate the modelling of error patterns in different parts/blocks of face images as a result of differences in illumination conditions, and we use appropriate error correction codes to deal with the corresponding distortion. We test the performance of our proposed schemes using the Extended Yale-B Face Database, which consists of face images belonging to 5 illumination subsets depending on the direction of light source from the camera. In our experiments each image is divided into three horizontal regions as follows: region1, three rows above the eyebrows, eyebrows and eyes; region2, nose region and region3, mouth and chin region. By estimating statistical parameters for errors in each region we select suitable BCH error correction codes that yield improved recognition accuracy for that particular region in comparison to applying error correction codes to the entire image. Discrete Wavelet Transform (DWT) to a depth of 3 is used for face feature extraction, followed by global/local binarization of coefficients in each subbands. We shall demonstrate that the use of BCH improves separation of the distribution of Hamming distances of client-client samples from the distribution of Hamming distances of imposter-client samples.

  16. Algorithms for adaptive nonlinear pattern recognition

    NASA Astrophysics Data System (ADS)

    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

  17. Self-face recognition in social context.

    PubMed

    Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

    2012-06-01

    The concept of "social self" is often described as a representation of the self-reflected in the eyes or minds of others. Although the appearance of one's own face has substantial social significance for humans, neuroimaging studies have failed to link self-face recognition and the likely neural substrate of the social self, the medial prefrontal cortex (MPFC). We assumed that the social self is recruited during self-face recognition under a rich social context where multiple other faces are available for comparison of social values. Using functional magnetic resonance imaging (fMRI), we examined the modulation of neural responses to the faces of the self and of a close friend in a social context. We identified an enhanced response in the ventral MPFC and right occipitoparietal sulcus in the social context specifically for the self-face. Neural response in the right lateral parietal and inferior temporal cortices, previously claimed as self-face-specific, was unaffected for the self-face but unexpectedly enhanced for the friend's face in the social context. Self-face-specific activation in the pars triangularis of the inferior frontal gyrus, and self-face-specific reduction of activation in the left middle temporal gyrus and the right supramarginal gyrus, replicating a previous finding, were not subject to such modulation. Our results thus demonstrated the recruitment of a social self during self-face recognition in the social context. At least three brain networks for self-face-specific activation may be dissociated by different patterns of response-modulation in the social context, suggesting multiple dynamic self-other representations in the human brain.

  18. Cataract influence on iris recognition performance

    NASA Astrophysics Data System (ADS)

    Trokielewicz, Mateusz; Czajka, Adam; Maciejewicz, Piotr

    2014-11-01

    This paper presents the experimental study revealing weaker performance of the automatic iris recognition methods for cataract-affected eyes when compared to healthy eyes. There is little research on the topic, mostly incorporating scarce databases that are often deficient in images representing more than one illness. We built our own database, acquiring 1288 eye images of 37 patients of the Medical University of Warsaw. Those images represent several common ocular diseases, such as cataract, along with less ordinary conditions, such as iris pattern alterations derived from illness or eye trauma. Images were captured in near-infrared light (used in biometrics) and for selected cases also in visible light (used in ophthalmological diagnosis). Since cataract is a disorder that is most populated by samples in the database, in this paper we focus solely on this illness. To assess the extent of the performance deterioration we use three iris recognition methodologies (commercial and academic solutions) to calculate genuine match scores for healthy eyes and those influenced by cataract. Results show a significant degradation in iris recognition reliability manifesting by worsening the genuine scores in all three matchers used in this study (12% of genuine score increase for an academic matcher, up to 175% of genuine score increase obtained for an example commercial matcher). This increase in genuine scores affected the final false non-match rate in two matchers. To our best knowledge this is the only study of such kind that employs more than one iris matcher, and analyzes the iris image segmentation as a potential source of decreased reliability

  19. Carbohydrate Recognition Properties of Human Ficolins

    PubMed Central

    Gout, Evelyne; Garlatti, Virginie; Smith, David F.; Lacroix, Monique; Dumestre-Pérard, Chantal; Lunardi, Thomas; Martin, Lydie; Cesbron, Jean-Yves; Arlaud, Gérard J.; Gaboriaud, Christine; Thielens, Nicole M.

    2010-01-01

    Ficolins are oligomeric innate immune recognition proteins consisting of a collagen-like region and a fibrinogen-like recognition domain that bind to pathogen- and apoptotic cell-associated molecular patterns. To investigate their carbohydrate binding specificities, serum-derived L-ficolin and recombinant H- and M-ficolins were fluorescently labeled, and their carbohydrate binding ability was analyzed by glycan array screening. L-ficolin preferentially recognized disulfated N-acetyllactosamine and tri- and tetrasaccharides containing terminal galactose or N-acetylglucosamine. Binding was sensitive to the position and orientation of the bond between N-acetyllactosamine and the adjacent carbohydrate. No significant binding of H-ficolin to any of the 377 glycans probed could be detected, providing further evidence for its poor lectin activity. M-ficolin bound preferentially to 9-O-acetylated 2-6-linked sialic acid derivatives and to various glycans containing sialic acid engaged in a 2-3 linkage. To further investigate the structural basis of sialic acid recognition by M-ficolin, point mutants were produced in which three residues of the fibrinogen domain were replaced by their counterparts in L-ficolin. Mutations G221F and A256V inhibited binding to the 9-O-acetylated sialic acid derivatives, whereas Y271F abolished interaction with all sialic acid-containing glycans. The crystal structure of the Y271F mutant fibrinogen domain was solved, showing that the mutation does not alter the structure of the ligand binding pocket. These analyses reveal novel ficolin ligands such as sulfated N-acetyllactosamine (L-ficolin) and gangliosides (M-ficolin) and provide precise insights into the sialic acid binding specificity of M-ficolin, emphasizing the essential role of Tyr271 in this respect. PMID:20032467

  20. Spoken word recognition without a TRACE

    PubMed Central

    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