14 resultados para Songs, Catalan -- Databases

em Indian Institute of Science - Bangalore - Índia


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Computation of the dependency basis is the fundamental step in solving the membership problem for functional dependencies (FDs) and multivalued dependencies (MVDs) in relational database theory. We examine this problem from an algebraic perspective. We introduce the notion of the inference basis of a set M of MVDs and show that it contains the maximum information about the logical consequences of M. We propose the notion of a dependency-lattice and develop an algebraic characterization of inference basis using simple notions from lattice theory. We also establish several interesting properties of dependency-lattices related to the implication problem. Founded on our characterization, we synthesize efficient algorithms for (a): computing the inference basis of a given set M of MVDs; (b): computing the dependency basis of a given attribute set w.r.t. M; and (c): solving the membership problem for MVDs. We also show that our results naturally extend to incorporate FDs also in a way that enables the solution of the membership problem for both FDs and MVDs put together. We finally show that our algorithms are more efficient than existing ones, when used to solve what we term the ‘generalized membership problem’.

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Functional dependencies in relational databases are investigated. Eight binary relations, viz., (1) dependency relation, (2) equipotence relation, (3) dissidence relation, (4) completion relation, and dual relations of each of them are described. Any one of these eight relations can be used to represent the functional dependencies in a database. Results from linear graph theory are found helpful in obtaining these representations. The dependency relation directly gives the functional dependencies. The equipotence relation specifies the dependencies in terms of attribute sets which functionally determine each other. The dissidence relation specifies the dependencies in terms of saturated sets in a very indirect way. Completion relation represents the functional dependencies as a function, the range of which turns out to be a lattice. Depletion relation which is the dual of the completion relation can also represent functional dependencies and similarly can the duals of dependency, equipotence, and dissidence relations. The class of depleted sets, which is the dual of saturated sets, is defined and used in the study of depletion relations.

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Functional dependencies in relational databases are investigated. Eight binary relations, viz., (1) dependency relation, (2) equipotence relation, (3) dissidence relation, (4) completion relation, and dual relations of each of them are described. Any one of these eight relations can be used to represent the functional dependencies in a database. Results from linear graph theory are found helpful in obtaining these representations. The dependency relation directly gives the functional dependencies. The equipotence relation specifies the dependencies in terms of attribute sets which functionally determine each other. The dissidence relation specifies the dependencies in terms of saturated sets in a very indirect way. Completion relation represents the functional dependencies as a function, the range of which turns out to be a lattice. Depletion relation which is the dual of the completion relation can also represent functional dependencies and similarly can the duals of dependency, equipotence, and dissidence relations. The class of depleted sets, which is the dual of saturated sets, is defined and used in the study of depletion relations.

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As research becomes more and more interdisciplinary, literature search from CD-ROM databases is often carried out on more than one CD-ROM database. This results in retrieving duplicate records due to same literature being covered (indexed) in more than one database. The retrieval software does not identify such duplicate records. Three different programs have been written to accomplish the task of identifying the duplicate records. These programs are executed from a shell script to minimize manual intervention. The various fields that have been used (extracted) to identify the duplicate records include the article title, year, volume number, issue number and pagination. The shell script when executed prompts for input file that may contain duplicate records. The programs identify the duplicate records and write them to a new file.

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CDS/ISIS is an advanced non-numerical information storage and retrieval software developed by UNESCO since 1985 to satisfy the need expressed by many institutions, especially in developing countries, to be able to streamline their information processing activities by using modern (and relatively inexpensive) technologies [1]. CDS/ISIS is available for MS-DOS, Windows and Unix operating system platforms. The formatting language of CDS/ISIS is one of its several strengths. It is not only used for formatting records for display but is also used for creating customized indexes. CDS/ISIS by itself does not facilitate in publishing its databases on the Internet nor does it facilitate in publishing on CD-ROMs. However, numbers of open source tools are now available, which enables in publishing CDS/ISIS databases on the Internet and also on CD-ROMs. In this paper, we have discussed the ways and means of integrating CDS/ISIS databases with GSDL, an open source digital library (DL) software.

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CDS/ISIS, an advanced non-numerical information storage and retrieval software was developed by UNESCO. With the emergence of WWW technology, most of the information activities are becoming Web-centric. Libraries and information providers are taking advantage of these Internet developments to provide access to their resources/information on the Web. A number of tools are now available for publishing CDS/ISIS databases on the Internet. One such tool is the WWWISIS Web gateway software, developed by BIREME, Brazil. This paper illustrates porting of sample records from a bibliographic database into CDS/ISIS, and then publishing this database on the Internet using WWWISIS.

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With the emergence of Internet, the global connectivity of computers has become a reality. Internet has progressed to provide many user-friendly tools like Gopher, WAIS, WWW etc. for information publishing and access. The WWW, which integrates all other access tools, also provides a very convenient means for publishing and accessing multimedia and hypertext linked documents stored in computers spread across the world. With the emergence of WWW technology, most of the information activities are becoming Web-centric. Once the information is published on the Web, a user can access this information from any part of the world. A Web browser like Netscape or Internet Explorer is used as a common user interface for accessing information/databases. This will greatly relieve a user from learning the search syntax of individual information systems. Libraries are taking advantage of these developments to provide access to their resources on the Web. CDS/ISIS is a very popular bibliographic information management software used in India. In this tutorial we present details of integrating CDS/ISIS with the WWW. A number of tools are now available for making CDS/ISIS database accessible on the Internet/Web. Some of these are 1) the WAIS_ISIS Server. 2) the WWWISIS Server 3) the IQUERY Server. In this tutorial, we have explained in detail the steps involved in providing Web access to an existing CDS/ISIS database using the freely available software, WWWISIS. This software is developed, maintained and distributed by BIREME, the Latin American & Caribbean Centre on Health Sciences Information. WWWISIS acts as a server for CDS/ISIS databases in a WWW client/server environment. It supports functions for searching, formatting and data entry operations over CDS/ISIS databases. WWWISIS is available for various operating systems. We have tested this software on Windows '95, Windows NT and Red Hat Linux release 5.2 (Appolo) Kernel 2. 0. 36 on an i686. The testing was carried out using IISc's main library's OPAC containing more than 80,000 records and Current Contents issues (bibliographic data) containing more than 25,000 records. WWWISIS is fully compatible with CDS/ISIS 3.07 file structure. However, on a system running Unix or its variant, there is no guarantee of this compatibility. It is therefore safe to recreate the master and the inverted files, using utilities provided by BIREME, under Unix environment.

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Emerging high-dimensional data mining applications needs to find interesting clusters embeded in arbitrarily aligned subspaces of lower dimensionality. It is difficult to cluster high-dimensional data objects, when they are sparse and skewed. Updations are quite common in dynamic databases and they are usually processed in batch mode. In very large dynamic databases, it is necessary to perform incremental cluster analysis only to the updations. We present a incremental clustering algorithm for subspace clustering in very high dimensions, which handles both insertion and deletions of datapoints to the backend databases.

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Practical usage of machine learning is gaining strategic importance in enterprises looking for business intelligence. However, most enterprise data is distributed in multiple relational databases with expert-designed schema. Using traditional single-table machine learning techniques over such data not only incur a computational penalty for converting to a flat form (mega-join), even the human-specified semantic information present in the relations is lost. In this paper, we present a practical, two-phase hierarchical meta-classification algorithm for relational databases with a semantic divide and conquer approach. We propose a recursive, prediction aggregation technique over heterogeneous classifiers applied on individual database tables. The proposed algorithm was evaluated on three diverse datasets. namely TPCH, PKDD and UCI benchmarks and showed considerable reduction in classification time without any loss of prediction accuracy. (C) 2012 Elsevier Ltd. All rights reserved.

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Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

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Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

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NrichD ( ext-link-type=''uri'' xlink:href=''http://proline.biochem.iisc.ernet.in/NRICHD/'' xlink:type=''simple''>http://proline.biochem.iisc.ernet.in/NRICHD/)< /named-content> is a database of computationally designed protein-like sequences, augmented into natural sequence databases that can perform hops in protein sequence space to assist in the detection of remote relationships. Establishing protein relationships in the absence of structural evidence or natural `intermediately related sequences' is a challenging task. Recently, we have demonstrated that the computational design of artificial intermediary sequences/linkers is an effective approach to fill naturally occurring voids in protein sequence space. Through a large-scale assessment we have demonstrated that such sequences can be plugged into commonly employed search databases to improve the performance of routinely used sequence search methods in detecting remote relationships. Since it is anticipated that such data sets will be employed to establish protein relationships, two databases that have already captured these relationships at the structural and functional domain level, namely, the SCOP database and the Pfam database, have been `enriched' with these artificial intermediary sequences. NrichD database currently contains 3 611 010 artificial sequences that have been generated between 27 882 pairs of families from 374 SCOP folds. The data sets are freely available for download. Additional features include the design of artificial sequences between any two protein families of interest to the user.

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In this paper we derive an approach for the effective utilization of thermodynamic data in phase-field simulations. While the most widely used methodology for multi-component alloys is following the work by Eiken et al. (2006), wherein, an extrapolative scheme is utilized in conjunction with the TQ interface for deriving the driving force for phase transformation, a corresponding simplistic method based on the formulation of a parabolic free-energy model incorporating all the thermodynamics has been laid out for binary alloys in the work by Folch and Plapp (2005). In the following, we extend this latter approach for multi-component alloys in the framework of the grand-potential formalism. The coupling is applied for the case of the binary eutectic solidification in the Cr-Ni alloy and two-phase solidification in the ternary eutectic alloy (Al-Cr-Ni). A thermodynamic justification entails the basis of the formulation and places it in context of the bigger picture of Integrated Computational Materials Engineering. (C) 2015 Elsevier Ltd. All rights reserved.