Database Independent Human Emotion Recognition with Meta-Cognitive Neuro-Fuzzy Inference System

Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.

Creating a specialist protein resource network: a meeting report for the protein bioinformatics and community resources retreat

During 11-12 August 2014, a Protein Bioinformatics and Community Resources Retreat was held at the Wellcome Trust Genome Campus in Hinxton, UK. This meeting brought together the principal investigators of several specialized protein resources (such as CAZy, TCDB and MEROPS) as well as those from protein databases from the large Bioinformatics centres (including UniProt and RefSeq). The retreat was divided into five sessions: (1) key challenges, (2) the databases represented, (3) best practices for maintenance and curation, (4) information flow to and from large data centers and (5) communication and funding. An important outcome of this meeting was the creation of a Specialist Protein Resource Network that we believe will improve coordination of the activities of its member resources. We invite further protein database resources to join the network and continue the dialogue.

SInCRe-structural interactome computational resource for Mycobacterium tuberculosis

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein-protein and protein-small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein-protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host-pathogen protein-protein interactions. Together they provide prerequisites for identification of off-target binding.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

A fast algorithm for speech polarity detection using long-term linear prediction

Speech polarity detection is a crucial first step in many speech processing techniques. In this paper, an algorithm is proposed that improvises the existing technique using the skewness of the voice source (VS) signal. Here, the integrated linear prediction residual (ILPR) is used as the VS estimate, which is obtained using linear prediction on long-term frames of the low-pass filtered speech signal. This excludes the unvoiced regions from analysis and also reduces the computation. Further, a modified skewness measure is proposed for decision, which also considers the magnitude of the skewness of the ILPR along with its sign. With the detection error rate (DER) as the performance metric, the algorithm is tested on 8 large databases and its performance (DER=0.20%) is found to be comparable to that of the best technique (DER=0.06%) on both clean and noisy speech. Further, the proposed method is found to be ten times faster than the best technique.

Efficient Protocol for Authenticated Email Search

Executing authenticated computation on outsourced data is currently an area of major interest in cryptology. Large databases are being outsourced to untrusted servers without appreciable verification mechanisms. As adversarial server could produce erroneous output, clients should not trust the server's response blindly. Primitive set operations like union, set difference, intersection etc. can be invoked on outsourced data in different concrete settings and should be verifiable by the client. One such interesting adaptation is to authenticate email search result where the untrusted mail server has to provide a proof along with the search result. Recently Ohrimenko et al. proposed a scheme for authenticating email search. We suggest significant improvements over their proposal in terms of client computation and communication resources by properly recasting it in two-party settings. In contrast to Ohrimenko et al. we are able to make the number of bilinear pairing evaluation, the costliest operation in verification procedure, independent of the result set cardinality for union operation. We also provide an analytical comparison of our scheme with their proposal which is further corroborated through experiments.

Low Resolution Face Recognition Across Variations in Pose and Illumination

We propose a completely automatic approach for recognizing low resolution face images captured in uncontrolled environment. The approach uses multidimensional scaling to learn a common transformation matrix for the entire face which simultaneously transforms the facial features of the low resolution and the high resolution training images such that the distance between them approximates the distance had both the images been captured under the same controlled imaging conditions. Stereo matching cost is used to obtain the similarity of two images in the transformed space. Though this gives very good recognition performance, the time taken for computing the stereo matching cost is significant. To overcome this limitation, we propose a reference-based approach in which each face image is represented by its stereo matching cost from a few reference images. Experimental evaluation on the real world challenging databases and comparison with the state-of-the-art super-resolution, classifier based and cross modal synthesis techniques show the effectiveness of the proposed algorithm.

SALIENT OBJECT DETECTION VIA OBJECTNESS MEASURE

Salient object detection has become an important task in many image processing applications. The existing approaches exploit background prior and contrast prior to attain state of the art results. In this paper, instead of using background cues, we estimate the foreground regions in an image using objectness proposals and utilize it to obtain smooth and accurate saliency maps. We propose a novel saliency measure called `foreground connectivity' which determines how tightly a pixel or a region is connected to the estimated foreground. We use the values assigned by this measure as foreground weights and integrate these in an optimization framework to obtain the final saliency maps. We extensively evaluate the proposed approach on two benchmark databases and demonstrate that the results obtained are better than the existing state of the art approaches.

An Amino Acid Substitution Matrix for Protein Conformation Identification

Amino acid substitution matrices play an essential role in protein sequence alignment, a fundamental task in bioinformatics. Most widely used matrices, such as PAM matrices derived from homologous sequences and BLOSUM matrices derived from aligned segments of PROSITE, did not integrate conformation information in their construction. There are a few structure-based matrices, which are derived from limited data of structure alignment. Using databases PDB_SELECT and DSSP, we create a database of sequence-conformation blocks which explicitly represent sequence-structure relationship. Members in a block are identical in conformation and are highly similar in sequence. From this block database, we derive a conformation-specific amino acid substitution matrix CBSM60. The matrix shows an improved performance in conformational segment search and homolog detection.

Coarse-to-fine vision-based localization by indexing scale-invariant features

This paper presents a novel coarse-to-fine global localization approach inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by scale-invariant transformation feature descriptors are used as natural landmarks. They are indexed into two databases: a location vector space model (LVSM) and a location database. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the LVSM is fast, but not accurate enough, whereas localization from the location database using a voting algorithm is relatively slow, but more accurate. The integration of coarse and fine stages makes fast and reliable localization possible. If necessary, the localization result can be verified by epipolar geometry between the representative view in the database and the view to be localized. In addition, the localization system recovers the position of the camera by essential matrix decomposition. The localization system has been tested in indoor and outdoor environments. The results show that our approach is efficient and reliable. © 2006 IEEE.

Vision-based global localization using a visual vocabular

This paper presents a novel coarse-to-fine global localization approach that is inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by SIFT descriptors are used as natural land-marks. These descriptors are indexed into two databases: an inverted index and a location database. The inverted index is built based on a visual vocabulary learned from the feature descriptors. In the location database, each location is directly represented by a set of scale invariant descriptors. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the inverted index is fast but not accurate enough; whereas localization from the location database using voting algorithm is relatively slow but more accurate. The combination of coarse and fine stages makes fast and reliable localization possible. In addition, if necessary, the localization result can be verified by epipolar geometry between the representative view in database and the view to be localized. Experimental results show that our approach is efficient and reliable. ©2005 IEEE.

Projeto para a organização de dados automatizados em bancos de dados na Câmara dos Deputados : um estudo de caso

A desorganização de dados em bancos de dados automatizados implica em ineficiência operacional causada por redundâncias, inconsistências, baixo reuso, riscos informacionais, enfim, menor valor agregado da TI aos objetivos organizacionais. Apoiado por técnicas de gerenciamento de projetos, busca-se em um estudo de caso na Câmara dos Deputados a otimização da organização dos dados em bancos de dados automatizados.

Desarrollo de una solución para el acceso integrado a fuentes de información sobre Patrimonio histórico. Análisis de las alternativas e implementación de una solución basada en una aplicación de búsqueda orientada en bases de datos heterogéneas

[ES] Este proyecto surgió en el marco del proyecto de investigación:

PICES-GLOBEC International Program on Climate Change and Carrying Capacity: Report of 2001 BASS/MODEL, MONITOR and REX Workshops, and the 2002 MODEL/REX Workshop

Table of Contents [pdf, 0.22 Mb] Executive Summary [pdf, 0.31 Mb] Report of the 2001 BASS/MODEL Workshop [pdf, 0.65 Mb] To review ecosystem models for the subarctic gyres Report of the 2001 MONITOR Workshop [pdf, 0.7 Mb] To review ecosystem models for the subarctic gyres Workshop presentations: Sonia D. Batten PICES Continuous Plankton Recorder pilot project Phillip R. Mundy GEM (Exxon Valdez Oil Spill Trustee Council`s "Gulf Ecosystem Monitoring" initiative) and U.S. GOOS plans in the North Pacific Ron McLaren and Brian O`Donnell A proposal for a North Pacific Action group of the international Data Buoy Cooperation Panel Gilberto Gaxiola-Castrol and Sila Najera-Martinez The Mexican oceanographic North Pacific program: IMECOCAL Sydney Levitus Building global ocean profile and plankton databases for scientific research Report of the 2001 REX Workshop [pdf, 1.73 Mb] On temporal variations in size-at-age for fish species in coastal areas around the Pacific Rim Workshop presentations: Brian J. Pyper, Randall M. Peterman, Michael F. Lapointe and Carl J. Walters [pdf, 0.33 Mb] Spatial patterns of covariation in size-at-age of British Columbia and Alaska sockeye salmon stocks and effects of abundance and ocean temperature R. Bruce MacFarlane, Steven Ralston, Chantell Royer and Elizabeth C. Norton [pdf, 0.4 Mb] Influences of the 1997-1998 El Niño and 1999 La Niña on juvenile Chinook salmon in the Gulf of the Farallones Olga S. Temnykh and Sergey L. Marchenko [pdf, 0.5 Mb] Variability of the pink salmon sizes in relation with abundance of Okhotsk Sea stocks Ludmila A. Chernoivanova, Alexander N. Vdoven and D.V. Antonenko [pdf, 0.3 Mb] The characteristic growth rate of herring in Peter the Great Bay (Japan/East Sea) Nikolay I. Naumenko [pdf, 0.5 Mb] Temporal variations in size-at-age of the western Bering Sea herring Evelyn D. Brown [pdf, 0.45 Mb] Effects of climate on Pacific herring, Clupea pallasii, in the northern Gulf of Alaska and Prince William Sound, Alaska Jake Schweigert, Fritz Funk, Ken Oda and Tom Moore [pdf, 0.6 Mb] Herring size-at-age variation in the North Pacific Ron W. Tanasichuk [pdf, 0.3 Mb] Implications of variation in euphausiid productivity for the growth, production and resilience of Pacific herring (Clupea pallasi) from the southwest coast of Vancouver Island Chikako Watanabe, Ahihiko Yatsu and Yoshiro Watanabe [pdf, 0.3 Mb] Changes in growth with fluctuation of chub mackerel abundance in the Pacific waters off central Japan from 1970 to 1997 Yoshiro Watanabe, Yoshiaki Hiyama, Chikako Watanabe and Shiro Takayana [pdf, 0.35 Mb] Inter-decadal fluctuations in length-at-age of Hokkaido-Sakhalin herring and Japanese sardine in the Sea of Japan Pavel A. Balykin and Alexander V. Buslov [pdf, 0.4 Mb] Long-term variability in length of walley pollock in the western Bering Sea and east Kamchtka Alexander A. Bonk [pdf, 0.4 Mb] Effect of population abundance increase on herring distribution in the western Bering Sea Sergey N. Tarasyuk [pdf, 0.4 Mb] Survival of yellowfin sole (Limanda aspera Pallas) in the northern part of the Tatar Strait (Sea of Japan) during the second half of the 20th century Report of the 2002 MODEL/REX Workshop [pdf, 1.2 Mb] To develop a marine ecosystem model of the North Pacific Ocean including pelagic fishes Summary and Overview [pdf, 0.4 Mb] Workshop presentations: Bernard A. Megrey, Kenny Rose, Francisco E. Werner, Robert A. Klumb and Douglas E. Hay [pdf, 0.47 Mb] A generalized fish bioenergetics/biomass model with an application to Pacific herring Robert A. Klumb [pdf, 0.34 Mb] Review of Clupeid biology with emphasis on energetics Douglas E. Hay [pdf, 0.47 Mb] Reflections of factors affecting size-at-age and strong year classes of herring in the North Pacific Shin-ichi Ito, Yutaka Kurita, Yoshioki Oozeki, Satoshi Suyama, Hiroya Sugisaki and Yongjin Tian [pdf, 0.34 Mb] Review for Pacific saury (Cololabis saira) study under the VENFISH project lexander V. Leonov and Gennady A. Kantakov [pdf, 0.34 Mb] Formalization of interactions between chemical and biological compartments in the mathematical model describing the transformation of nitrogen, phosphorus, silicon and carbon compounds Herring group report and model results [pdf, 0.34 Mb] Saury group report and model results [pdf, 0.46 Mb] Model experiments and hypotheses Recommendations [pdf, 0.4 Mb] Achievements and future steps Acknowledgements [pdf, 0.29 Mb] References [pdf, 0.32 Mb] Appendix 1. List of Participants [pdf, 0.32 Mb] Appendices 2-5. FORTRAN codes [pdf, 0.4 Mb] (Document pdf contains 182 pages)