938 resultados para AVICAR database
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USC-TIMIT is an extensive database of multimodal speech production data, developed to complement existing resources available to the speech research community and with the intention of being continuously refined and augmented. The database currently includes real-time magnetic resonance imaging data from five male and five female speakers of American English. Electromagnetic articulography data have also been presently collected from four of these speakers. The two modalities were recorded in two independent sessions while the subjects produced the same 460 sentence corpus used previously in the MOCHA-TIMIT database. In both cases the audio signal was recorded and synchronized with the articulatory data. The database and companion software are freely available to the research community. (C) 2014 Acoustical Society of America.
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Background: Haemophilus influenzae (H. Influenzae) is the causative agent of pneumonia, bacteraemia and meningitis. The organism is responsible for large number of deaths in both developed and developing countries. Even-though the first bacterial genome to be sequenced was that of H. Influenzae, there is no exclusive database dedicated for H. Influenzae. This prompted us to develop the Haemophilus influenzae Genome Database (HIGDB). Methods: All data of HIGDB are stored and managed in MySQL database. The HIGDB is hosted on Solaris server and developed using PERL modules. Ajax and JavaScript are used for the interface development. Results: The HIGDB contains detailed information on 42,741 proteins, 18,077 genes including 10 whole genome sequences and also 284 three dimensional structures of proteins of H. influenzae. In addition, the database provides ``Motif search'' and ``GBrowse''. The HIGDB is freely accessible through the URL:http://bioserverl.physicslisc.ernetin/HIGDB/. Discussion: The HIGDB will be a single point access for bacteriological, clinical, genomic and proteomic information of H. influenzae. The database can also be used to identify DNA motifs within H. influenzae genomes and to compare gene or protein sequences of a particular strain with other strains of H. influenzae. (C) 2014 Elsevier Ltd. All rights reserved.
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Streptococcus pneumoniae causes pneumonia, septicemia and meningitis. S. pneumoniae is responsible for significant mortality both in children and in the elderly. In recent years, the whole genome sequencing of various S. pneumoniae strains have increased manifold and there is an urgent need to provide organism specific annotations to the scientific community. This prompted us to develop the Streptococcus pneumoniae Genome Database (SPGDB) to integrate and analyze the completely sequenced and available S. pneumoniae genome sequences. Further, links to several tools are provided to compare the pool of gene and protein sequences, and proteins structure across different strains of S. pneumoniae. SPGDB aids in the analysis of phenotypic variations as well as to perform extensive genomics and evolutionary studies with reference to S. pneumoniae. (C) 2014 Elsevier Inc. All rights reserved.
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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.
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Hydrilla ( Hydrilla verticillata (L.f.) Royle), an invasive aquatic weed, continues to spread to new regions in the United States. Two biotypes, one a female dioecious and the other monoecious have been identified. Management of the spread of hydrilla requires understanding the mechanisms of introduction and transport, an ability to map and make available information on distribution, and tools to distinguish the known U.S. biotypes as well as potential new introductions. Review of the literature and discussions with aquatic scientists and resource managers point to the aquarium and water garden plant trades as the primary past mechanism for the regional dispersal of hydrilla while local dispersal is primarily carried out by other mechanisms such as boat traffic, intentional introductions, and waterfowl. The Nonindigenous Aquatic Species (NAS) database is presented as a tool for assembling, geo-referencing, and making available information on the distribution of hydrilla. A map of the current range of dioecious and monoecious hydrilla by drainage is presented. Four hydrilla samples, taken from three discrete, non-contiguous regions (Pennsylvania, Connecticut, and Washington State) were examined using two RAPD assays. The first, generated using primer Operon G17, and capable of distinguishing the dioecious and monoecious U.S. biotypes, indicated all four samples were of the monoecious biotype. Results of the second assay using the Stoffel fragment and 5 primers, produced 111 markers, indicated that these samples do not represent new foreign introductions. The differences in the monoecious and dioecious growth habits and management are discussed.
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Validated by comparison with DNS, numerical database of turbulent channel flows is yielded by Large Eddy Simulation (LES). Three conventional techniques: uv quadrant 2, VITA and mu-level techniques for detecting turbulent bursts are applied to the identification of turbulent bursts. With a grouping parameter introduced by Bogard & Tiedemann (1986) or Luchik & Tiederman (1987), multiple ejections detected by these techniques which originate from a single burst can be grouped into a single-burst event. The results are compared with experimental results, showing that all techniques yield reasonable average burst period. However, uv quadrant 2 and mu-level are found to be superior to VITA in having large threshold-independent range.
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Cambodia is one of the poorest countries in the world; much of its population live in rural areas and many live below the local poverty line. The management of common property aquatic resources is of over-riding importance to food security and sustainable rural development in Cambodia. Aquatic resources are utilized principally by subsistence fishers and the landless, for whom aquatic resource use is an important livelihood activity. Subsistence fishers access mainly the rivers, lakes and inundated forests in Tonle Sap provinces, the lower Mekong and Bassac regions and the upper part of the Mekong. Freshwater capture fisheries probably contribute more to national food security and the national economy in Cambodia than in any other country in the world. (PDF contains 52 pages)
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The paper traces the history of the different documentation media used for information dissemination. Such early media are clay tablets, papyrus, and vellum or parchment codex. The invention of printing however revolutionized the information industry, enabling the production of books in multiple copies. Photography came into documentation mainly to preserve rare materials and those that easily deteriorate. This paper reports the efforts of National Institute for Freshwater Fisheries Research (NIFFR) and Kainji Lake Fisheries Promotion Project (KLFPPP), Nigeria, to develop an Object Oriented Database (OOD) using photographs. The photographs are stored in digitized form on commercial computers, using the program ACDSee 32 for classification, description and retrieval. Specifically the paper focuses on photographs in fisheries as visual communication and expression. Presently, the database contains photo documents about the following aspects of Kainji Lake fisheries: fishing gears and crafts, fish preservation methods
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The paper viewed the decline in information provision in Nigeria to poor library development, which could be attributed to poor funding. The consequence is that current journal and books are not available in nigerian fisheries libraries. Information which can be regarded as the first factor of production on which other factors like land, labour and capital depend, can only be provided at the right time when libraries are better founded. For now if there must be increase in fish production, poverty alleviation and food security in Nigeria, our fisheries scientists and policy makers will have to rely on international sources of information using the advantage of internet connectivity. Some of such sources discussed in this paper are ASFA, AGORA, FAO DOAJ, FISHBASE, IAMSLIC, INASP, INASP-PERI, INASP-AJOL, ODINAFRICA, SIFAR, WAS, and ABASFR. However, reliance on international sources must not be at the total neglect of harnessing nigerian fisheries information. For the Nigerian Fisheries and Aquatic Sciences Database being developed by NIFFR to attain an international status like those enumerated above, scientists and publishers are requested to take the pain of depositing copies of their publications with NIFFR for inclusion in the Database