Recognition by Prototypes

A scheme for recognizing 3D objects from single 2D images is introduced. The scheme proceeds in two stages. In the first stage, the categorization stage, the image is compared to prototype objects. For each prototype, the view that most resembles the image is recovered, and, if the view is found to be similar to the image, the class identity of the object is determined. In the second stage, the identification stage, the observed object is compared to the individual models of its class, where classes are expected to contain objects with relatively similar shapes. For each model, a view that matches the image is sought. If such a view is found, the object's specific identity is determined. The advantage of categorizing the object before it is identified is twofold. First, the image is compared to a smaller number of models, since only models that belong to the object's class need to be considered. Second, the cost of comparing the image to each model in a classis very low, because correspondence is computed once for the whoel class. More specifically, the correspondence and object pose computed in the categorization stage to align the prototype with the image are reused in the identification stage to align the individual models with the image. As a result, identification is reduced to a series fo simple template comparisons. The paper concludes with an algorithm for constructing optimal prototypes for classes of objects.

Recognition interactions of metal-complexing imprinted polymer

Molecularly imprinted polymer, exhibiting considerable enantioselectivity for L-mandelic acid, was prepared using metal coordination-chelation interaction. By evaluating the recognition characteristics in the chromatographic mode, the recognition interactions were proposed: specific and nonspecific metal coordination-chelation interaction and hydrophobic interaction were responsible for substrate binding on metal-complexing imprinted polymer; while the selective recognition only came from specific metal coordination-chelation interaction and specific hydrophobic interaction.

Learning Embeddings for Indexing, Retrieval, and Classification, with Applications to Object and Shape Recognition in Image Databases

Nearest neighbor retrieval is the task of identifying, given a database of objects and a query object, the objects in the database that are the most similar to the query. Retrieving nearest neighbors is a necessary component of many practical applications, in fields as diverse as computer vision, pattern recognition, multimedia databases, bioinformatics, and computer networks. At the same time, finding nearest neighbors accurately and efficiently can be challenging, especially when the database contains a large number of objects, and when the underlying distance measure is computationally expensive. This thesis proposes new methods for improving the efficiency and accuracy of nearest neighbor retrieval and classification in spaces with computationally expensive distance measures. The proposed methods are domain-independent, and can be applied in arbitrary spaces, including non-Euclidean and non-metric spaces. In this thesis particular emphasis is given to computer vision applications related to object and shape recognition, where expensive non-Euclidean distance measures are often needed to achieve high accuracy. The first contribution of this thesis is the BoostMap algorithm for embedding arbitrary spaces into a vector space with a computationally efficient distance measure. Using this approach, an approximate set of nearest neighbors can be retrieved efficiently - often orders of magnitude faster than retrieval using the exact distance measure in the original space. The BoostMap algorithm has two key distinguishing features with respect to existing embedding methods. First, embedding construction explicitly maximizes the amount of nearest neighbor information preserved by the embedding. Second, embedding construction is treated as a machine learning problem, in contrast to existing methods that are based on geometric considerations. The second contribution is a method for constructing query-sensitive distance measures for the purposes of nearest neighbor retrieval and classification. In high-dimensional spaces, query-sensitive distance measures allow for automatic selection of the dimensions that are the most informative for each specific query object. It is shown theoretically and experimentally that query-sensitivity increases the modeling power of embeddings, allowing embeddings to capture a larger amount of the nearest neighbor structure of the original space. The third contribution is a method for speeding up nearest neighbor classification by combining multiple embedding-based nearest neighbor classifiers in a cascade. In a cascade, computationally efficient classifiers are used to quickly classify easy cases, and classifiers that are more computationally expensive and also more accurate are only applied to objects that are harder to classify. An interesting property of the proposed cascade method is that, under certain conditions, classification time actually decreases as the size of the database increases, a behavior that is in stark contrast to the behavior of typical nearest neighbor classification systems. The proposed methods are evaluated experimentally in several different applications: hand shape recognition, off-line character recognition, online character recognition, and efficient retrieval of time series. In all datasets, the proposed methods lead to significant improvements in accuracy and efficiency compared to existing state-of-the-art methods. In some datasets, the general-purpose methods introduced in this thesis even outperform domain-specific methods that have been custom-designed for such datasets.

Learning Temporal Contexts and Priming-Preparation Modes for Pattern Recognition

The system presented here is based on neurophysiological and electrophysiological data. It computes three types of increasingly integrated temporal and probability contexts, in a bottom-up mode. To each of these contexts corresponds an increasingly specific top-down priming effect on lower processing stages, mostly pattern recognition and discrimination. Contextual learning of time intervals, events' temporal order or sequential dependencies and events' prior probability results from the delivery of large stimuli sequences. This learning gives rise to emergent properties which closely match the experimental data.

A cultural study on communication and technology with specific reference to media in China

This dissertation examines the role of communications technology in social change. It examines secondary data on contemporary China arguing that many interpretations of events in China are unsuitable at best and at worst conceptually damages our understanding of social change in China. This is especially the case in media studies under the ‘democratic framework’. It proposes that there is an alternative framework in studying the media and social change. This alternative conceptual framework is termed a zone of interpretative development offering a means by which to discuss events that take place in a mediated environment. Taking a theoretical foundation using the philosophy of Mikhail Bakhtin this dissertation develops a platform with which to understand communication technology from an anthropological perspective. Three media events from contemporary China are examined. The first examines the Democracy Wall event and the implications of using a public sphere framework. The second case examines the phenomenon of the Grass Mud Horse, a symbol that has gained popular purchase as a humorous expression of political dissatisfaction and develops the problems seen in the first case but with some solutions. Using a modification of Lev Vygotskiĭ’s zone of proximal development this symbol is understood as an expression of the collective recognition of a shared experience. In the second example from the popular TV talent show contests in China further expressions of collective experience are introduced. With the evidence from these media events in contemporary China this dissertation proposes that we can understand certain modes of communication as occurring in a zone of interpretative development. This proposed anthropological feature of social change via communication and technology can fruitfully describe meaning-formation in society via the expression and recognition of shared experiences.

Evaluation of a WHO-Validated Serotype-Specific Serological Assay for the Diagnosis of Pneumococcal Etiology in Children with Community-Acquired Pneumonia.

BACKGROUND: The etiologic diagnosis of community-acquired pneumonia (CAP) remains challenging in children because blood cultures have low sensitivity. Novel approaches are needed to confirm the role of Streptococcus pneumoniae. METHODS: In this study, pneumococcal aetiology was determined by serology using a subset of blood samples collected during a prospective multicentre observational study of children <15 years of age hospitalised in Belgium with X-ray-confirmed CAP. Blood samples were collected at admission and 3-4 weeks later. Pneumococcal (P)-CAP was defined in the presence of a positive blood or pleural fluid culture. Serotyping of Streptococcus pneumoniae isolates was done with the Quellung reaction. Serological diagnosis was assessed for nine serotypes using World Health Organization validated IgG and IgA serotype-specific enzyme-linked immunosorbent assays (ELISAs). RESULTS: Paired admission/convalescent sera from 163 children were evaluated by ELISA (35 with proven P-CAP and 128 with non proven P-CAP). ELISA detected pneumococci in 82.8% of patients with proven P-CAP. The serotypes identified were the same as with the Quellung reaction in 82% and 59% of cases by IgG ELISA and IgA ELISA, respectively. Overall, ELISA identified a pneumococcal aetiology in 55% of patients with non-proven P-CAP. Serotypes 1 (51.6%), 7F (19%), and 5 (15.7%) were the most frequent according to IgG ELISA. CONCLUSIONS: In conclusion, the serological assay allows recognition of pneumococcal origin in 55% of CAP patients with negative culture. This assay should improve the diagnosis of P-CAP in children and could be a useful tool for future epidemiological studies on childhood CAP etiology.

Decoding an olfactory mechanism of kin recognition and inbreeding avoidance in a primate.

BACKGROUND: Like other vertebrates, primates recognize their relatives, primarily to minimize inbreeding, but also to facilitate nepotism. Although associative, social learning is typically credited for discrimination of familiar kin, discrimination of unfamiliar kin remains unexplained. As sex-biased dispersal in long-lived species cannot consistently prevent encounters between unfamiliar kin, inbreeding remains a threat and mechanisms to avoid it beg explanation. Using a molecular approach that combined analyses of biochemical and microsatellite markers in 17 female and 19 male ring-tailed lemurs (Lemur catta), we describe odor-gene covariance to establish the feasibility of olfactory-mediated kin recognition. RESULTS: Despite derivation from different genital glands, labial and scrotal secretions shared about 170 of their respective 338 and 203 semiochemicals. In addition, these semiochemicals encoded information about genetic relatedness within and between the sexes. Although the sexes showed opposite seasonal patterns in signal complexity, the odor profiles of related individuals (whether same-sex or mixed-sex dyads) converged most strongly in the competitive breeding season. Thus, a strong, mutual olfactory signal of genetic relatedness appeared specifically when such information would be crucial for preventing inbreeding. That weaker signals of genetic relatedness might exist year round could provide a mechanism to explain nepotism between unfamiliar kin. CONCLUSION: We suggest that signal convergence between the sexes may reflect strong selective pressures on kin recognition, whereas signal convergence within the sexes may arise as its by-product or function independently to prevent competition between unfamiliar relatives. The link between an individual's genome and its olfactory signals could be mediated by biosynthetic pathways producing polymorphic semiochemicals or by carrier proteins modifying the individual bouquet of olfactory cues. In conclusion, we unveil a possible olfactory mechanism of kin recognition that has specific relevance to understanding inbreeding avoidance and nepotistic behavior observed in free-ranging primates, and broader relevance to understanding the mechanisms of vertebrate olfactory communication.

Towards Real-time Speech Emotion Recognition for Affective E-Learning

The original article is available as an open access file on the Springer website in the following link: http://link.springer.com/article/10.1007/s10639-015-9388-2

Communication, recognition and social work: Aligning the ethical theories of Habermas and Honneth

The modern world is replete with ethical challenges of Orwellian proportions. The violation of human rights and misrecognition of identities are two of the most pressing examples. In this paper, the ethical theories of Habermas and Honneth are aligned as a way of addressing these specific challenges within social work. It is suggested that these theories are complementary, mutually rectifying and concordant at the meta-ethical level of analysis. The alignment is also justified, pargmatically, through the construction of three hypothetical vignettes demonstrating different kinds of practice dilemmas. The need for egalitarian communication and the imperative to recognise human identity in all its dimensions subsequently emerge as the two foundation stones for ethical deliberation in social work.

Multimodal Biometric Human Recognition for Perceptual Human-Computer Interaction

In this paper, a novel video-based multimodal biometric verification scheme using the subspace-based low-level feature fusion of face and speech is developed for specific speaker recognition for perceptual human--computer interaction (HCI). In the proposed scheme, human face is tracked and face pose is estimated to weight the detected facelike regions in successive frames, where ill-posed faces and false-positive detections are assigned with lower credit to enhance the accuracy. In the audio modality, mel-frequency cepstral coefficients are extracted for voice-based biometric verification. In the fusion step, features from both modalities are projected into nonlinear Laplacian Eigenmap subspace for multimodal speaker recognition and combined at low level. The proposed approach is tested on the video database of ten human subjects, and the results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications. The experiment on MATLAB shows the potential of the proposed scheme to attain the real-time performance for perceptual HCI applications.

Sequence-Specific and Strand-Specific Cleavage In Oligodeoxyribonucleotides and DNA Containing 3'-Thiothymidine

Oligonucleotides containing a 3'-thiothymidine residue (T3's) at the cleavage site for the EcoRV restriction endonuclease (between the central T and A residues of the sequence GATATC) have been prepared on an automated DNA synthesizer using 5'-O-monomethoxytritylthymidine 3'-S-(2-cyanoethyl N,N-di-isopropylphosphorothioamidite). The self-complementary sequence GACGAT3'sATCGTC was completely resistant to cleavage by EcoRV, while the heteroduplex composed of 5'-TCTGAT3'sATCCTC and 5'-GAGGATATCAGA (duplex 4) was cleaved only in the unmodified strand (5'-GAGGATATCAGA). In contrast, strands containing a 3'-S-phosphorothiolate linkage could be chemically cleaved specifically at this site with Ag+. A T3's residue has also been incorporated in the (-) strand of double-stranded closed circular (RF IV) M13mp18 DNA at the cleavage site of a unique EcoRV recognition sequence by using 5'-pCGAGCTCGAT3'sATCGTAAT as a primer for polymerization on the template (+) strand of M13mp18 DNA. On treatment of this substrate with EcoRV, only one strand was cleaved to produce the RF II or nicked DNA. Taken in conjunction with the cleavage studies on the oligonucleotides, this result demonstrates that the 3'-S-phosphorothiolate linkage is resistant to scission by EcoRV. Additionally, the phosphorothiolate-containing strand of the M13mp18 DNA could be cleaved specifically at the point of modification using iodine in aqueous pyridine. The combination of enzymatic and chemical techniques provides, for the first time, a demonstrated method for the sequence-specific cleavage of either the (+) or (-) strand.

Molecular dynamics studies of the STAT3 homodimer:DNA complex: relationships between STAT3 mutations and protein-DNA recognition.

Signal Transducers and Activators of Transcription (STAT) proteins are a group of latent cytoplasmic transcription factors involved in cytokine signaling. STAT3 is a member of the STAT family and is expressed at elevated levels in a large number of diverse human cancers and is now a validated target for anticancer drug discovery.. Understanding the dynamics of the STAT3 dimer interface, accounting for both protein-DNA and protein-protein interactions, with respect to the dynamics of the latent unphosphorylated STAT3 monomer, is important for designing potential small-molecule inhibitors of the activated dimer. Molecular dynamics (MD) simulations have been used to study the activated STAT3 homodimer:DNA complex and the latent unphosphorylated STAT3 monomer in an explicit water environment. Analysis of the data obtained from MD simulations over a 50 ns time frame has suggested how the transcription factor interacts with DNA, the nature of the conformational changes, and ways in which function may be affected. Examination of the dimer interface, focusing on the protein-DNA interactions, including involvement of water molecules, has revealed the key residues contributing to the recognition events involved in STAT3 protein-DNA interactions. This has shown that the majority of mutations in the DNA-binding domain are found at the protein-DNA interface. These mutations have been mapped in detail and related to specific protein-DNA contacts. Their structural stability is described, together with an analysis of the model as a starting-point for the discovery of novel small-molecule STAT3 inhibitors.

Conserved amino acid residues found in a predicted cytosolic domain of the lipopolysaccharide biosynthetic protein WecA are implicated in the recognition of UDP-N-acetylglucosamine

WecA, an integral membrane protein that belongs to a family of polyisoprenyl phosphate N-acetylhexosamine-1-phosphate transferases, is required for the biosynthesis of O-specific LPS and enterobacterial common antigen in Escherichia coli and other enteric bacteria. WecA functions as an UDP-N-acetylglucosamine (GlcNAc):undecaprenyl-phosphate GlcNAc-1-phosphate transferase. A conserved short sequence motif (His-Ile-His-His; HIHH) and a conserved arginine were identified in WecA at positions 279-282 and 265, respectively. This region is located within a predicted cytosolic segment common to all bacterial homologues of WecA. Both HIHH279-282 and the Arg265 are reminiscent of the HIGH motif (His-Ile-Gly-His) and a nearby upstream lysine, which contribute to the three-dimensional architecture of the nucleotide-binding site among various enzymes displaying nucleotidyltransferase activity. Thus, it was hypothesized that these residues may play a role in the interaction of WecA with UDP-GlcNAc. Replacement of the entire HIHH motif by site-directed mutagenesis produced a protein that, when expressed in the E. coli wecA mutant MV501, did not complement the synthesis of O7 LPS. Membrane extracts containing the mutated protein failed to transfer UDP-GlcNAc into a lipid-rich fraction and to bind the UDP-GlcNAc analogue tunicamycin. Similar results were obtained by individually replacing the first histidine (H279) of the HIHH motif as well as the Arg265 residue. The functional importance of these residues is underscored by the high level of conservation of H279 and Arg265 among bacterial WecA homologues that utilize several different UDP-N-acetylhexosamine substrates.

Robust Audio-Visual Speech Recognition under Noisy Audio-Video Conditions

This paper presents the maximum weighted stream posterior (MWSP) model as a robust and efficient stream integration method for audio-visual speech recognition in environments, where the audio or video streams may be subjected to unknown and time-varying corruption. A significant advantage of MWSP is that it does not require any specific measurements of the signal in either stream to calculate appropriate stream weights during recognition, and as such it is modality-independent. This also means that MWSP complements and can be used alongside many of the other approaches that have been proposed in the literature for this problem. For evaluation we used the large XM2VTS database for speaker-independent audio-visual speech recognition. The extensive tests include both clean and corrupted utterances with corruption added in either/both the video and audio streams using a variety of types (e.g., MPEG-4 video compression) and levels of noise. The experiments show that this approach gives excellent performance in comparison to another well-known dynamic stream weighting approach and also compared to any fixed-weighted integration approach in both clean conditions or when noise is added to either stream. Furthermore, our experiments show that the MWSP approach dynamically selects suitable integration weights on a frame-by-frame basis according to the level of noise in the streams and also according to the naturally fluctuating relative reliability of the modalities even in clean conditions. The MWSP approach is shown to maintain robust recognition performance in all tested conditions, while requiring no prior knowledge about the type or level of noise.

Electrochemical sensor for catechol and dopamine based on a catalytic molecularly imprinted polymer-conducting polymer hybrid recognition element

One of the difficulties with using molecularly imprinted polymers (MIPs) and other electrically insulating materials as the recognition element in electrochemical sensors is the lack of a direct path for the conduction of electrons from the active sites to the electrode. We have sought to address this problem through the preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer. In this way a network of "molecular wires" assists in the conduction of electrons from the active sites within the MIP to the electrode surface. This was made possible by the design of a new monomer that combines orthogonal polymerizable functionality; comprising an aniline group and a methacrylamide. Conducting films were prepared on the surface of electrodes (Au on glass) by electropolymerization of the aniline moiety. A layer of MIP was photochemically grafted over the polyaniline, via N,N'-diethyldithiocarbamic acid benzyl ester (iniferter) activation of the methacrylamide groups. Detection of catechol by the hybrid-MIP sensor was found to be specific, and catechol oxidation was detected by cyclic voltammetry at the optimized operating conditions: potential range -0.6 V to +0.8 V (vs Ag/AgCl), scan rate 50 mV/s, PBS pH 7.4. The calibration curve for catechol was found to be linear to 144 µM, with a limit of detection of 228 nM. Catechol and dopamine were detected by the sensor, whereas analogues and potentially interfering compounds, including phenol, resorcinol, hydroquinone, serotonin, and ascorbic acid, had minimal effect (=3%) on the detection of either analyte. Nonimprinted hybrid electrodes and bare gold electrodes failed to give any response to catechol at concentrations below 0.5 mM. Finally, the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics. © 2009 American Chemical Society.