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A Mixed Learning Strategy for Finding Typical Testors in Large Datasets
[chapter]
2015
Lecture Notes in Computer Science
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This paper presents a mixed, global and local, learning strategy for finding typical testors in large datasets. The goal of the proposed strategy is to allow any search algorithm to achieve the most significant reduction possible in the search space of a typical testor-finding problem. The strategy is based on a trivial classifier which partitions the search space into four distinct classes and allows the assessment of each feature subset within it. Each class is handled by slightly different
doi:10.1007/978-3-319-25751-8_86
fatcat:f4vam4qddzbrbbu7hvhy5n7ece
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... arning actions, and induces a different reduction in the search-space of a problem. Any typical testor-finding algorithm, whether deterministic or metaheuristc, can be adapted to incorporate the proposed strategy and can take advantage of the learned information in diverse manners.
Multi-level Modeling of Manuscripts for Authorship Identification with Collective Decision Systems
[chapter]
2012
Lecture Notes in Computer Science
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In the context of forensic and criminalistics studies the problem of identifying the author of a manuscript is generally expressed as a supervisedclassification problem. In this paper a new approach for modeling a manuscript at the word and text line levels is presented. This new approach introduces an eclectic paradigm between texture-related and structure-related modeling approaches. Compared to previously published works, the proposed method significantly reduces the number and complexity of
doi:10.1007/978-3-642-33275-3_93
fatcat:ql5xdy3b5nabbitnzflc7khipi
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... the text-features to be extracted from the text. Extensive experimentation with the proposed model shows it to be faster and easier to implement than other models, making it ideal for extensive use in forensic and criminalistics studies.
Designing New CAPTCHA Models Based on the Cognitive Abilities of Artificial Agents
2017
Research in Computing Science
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A CAPTCHA is a program that allows or denies access to services by generating and grading test that humans can pass but current computer programs cannot. Captchas are generally used to protect free web services from automated programs. Also, they can provide an idea of which fields in artificial intelligence are the most explored and which could be researched in the near future. Most of the tests that are based on text recognition have been broken by optical character recognition (OCR)
doi:10.13053/rcs-138-1-13
fatcat:6qiritjakndb7otg5pdbcdmbfa
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... s while those based on images are vulnerable to machine learning attacks. Humans make use of cognitive abilities to carry out tasks in daily life, even if they are not conscious which ones or how they use them. The current state of technology is still not enough to reproduce some human cognitive abilities, and the identification of those abilities is the basis for the design of new CAPTCHA models. In this paper we introduce seven new models of CAPTCHA to test some cognitive abilities that are supposed to be beyond the capabilities of artificial agents. We use some APIs to proof that images used in the proposals are extremely difficult to be recognized by artificial agents.
Proposal for a Unified Methodology for Evaluating Supervised and Non-supervised Classification Algorithms
[chapter]
2006
Lecture Notes in Computer Science
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There is presently no unified methodology that allows the evaluation of supervised and non-supervised classification algorithms. Supervised problems are evaluated through Quality Functions that require a previously known solution for the problem, while non-supervised problems are evaluated through several Structural Indexes that do not evaluate the classification algorithm by using the same pattern similarity criteria embedded in the classification algorithm. In both cases, a lot of useful
doi:10.1007/11892755_70
fatcat:cd4ws5tmwrcqlfr35v4jg4txqu
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... mation remains hidden or is not considered by the evaluation method, such as the quality of the supervision sample or the structural change generated by the classification algorithm on the sample. This paper proposes a unified methodology to evaluate classification problems of both kinds, that offers the possibility of making comparative evaluations and yields a larger amount of information to the evaluator about the quality of the initial sample, when it exists, and regarding the change produced by the classification algorithm.
A Theoretical and Practical Framework for Assessing the Computational Behavior of Typical Testor-Finding Algorithms
[chapter]
2013
Lecture Notes in Computer Science
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Although the general relevance of Testor Theory as the theoretical ground for useful feature selection procedures is well known, there are no practical means, nor any standard methodologies, for assessing the behavior of a testor-finding algorithm when faced with specific circumstances. In this work, we present a practical framework, with proven theoretical foundation, for assessing the behavior of both deterministic and meta-heuristic testor-finding algorithms when faced with specific phenomena.
doi:10.1007/978-3-642-41822-8_44
fatcat:f47tomxiyzeojoskapfgp7cu3a
Digital Image-based Inductive Characterization and Classification for Improving the Quality Inspection of Diverse Food Products
2013
Research in Computing Science
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With the increasingly demanding international regulations for import and export of food products, as well as with the increased awareness and sophistication of consumers, the food industry needs accurate, fast and efficient quality inspection means. Each producer seeks to ensure that their products satisfy all consumer's expectations and that the appropriate quality level of each product is offered and sold to each different socio-economic consumer group. This paper presents three study cases
doi:10.13053/rcs-68-1-7
fatcat:pxkyzgqsdberxbajqfs2ublwhu
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... ere digital image analysis and inductive characterization techniques have been successfully applied to improve the quality inspection process. Three very different and unrelated basic food products are studied: Hass Avocado, Manila Mango and Corn Tortillas. Each one of these products has some special and particular features that complicate the quality inspection process, but each of these products is also very important in economical terms for the sheer volume of their production and marketing. Experimental results of each case shows that the general technique has great accuracy and significantly lower costs.
Assessing the Quality Level of Corn Tortillas with Inductive Characterization and Digital Image Analysis
[chapter]
2013
Lecture Notes in Computer Science
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Characterization and classification of corn tortillas turns out to be an extremely delicate and difficult process when dealing with regulations for import/export and production process certification. In this paper we present a method for non-invasive feature extraction, based on digital imaging and a series of procedures to characterize different qualities of corn tortillas for their later classification. The novelty in this whole method lies in the extremely reduced set of features required
doi:10.1007/978-3-642-38989-4_5
fatcat:inif6rfflrazleuvufvk3e4h7a
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... the characterization with only geometrical and color features. Nonetheless, this set of features can assess diverse quality elements like the homogeneity of the baking process and others alike. Experimental results on a sample batch of 600 tortillas show the presented method to be around 95% effective.
Efficiently Finding the Optimum Number of Clusters in a Dataset with a New Hybrid Cellular Evolutionary Algorithm
2014
Journal of Computacion y Sistemas
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A challenge in hybrid evolutionary algorithms is to employ efficient strategies to cover all the search space, applying local search only in actually promising search areas; on the other hand, clustering algorithms, a fundamental base for data mining procedures and learning techniques, suffer from the lack of efficient methods for determining the optimal number of clusters to be found in an arbitrary dataset. Some existing methods use evolutionary algorithms with cluster validation index as the
doi:10.13053/cys-18-2-1936
fatcat:thvzft5slrfgzbqolvrt6ik5zi
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... objective function. In this article, a new cellular evolutionary algorithm based on a hybrid model of global and local heuristic search is proposed for the same task, and extensive experimentation is done with different datasets and indexes.
Efficiently Finding the Optimum Number of Clusters in a Dataset with a New Hybrid Cellular Evolutionary Algorithm
2014
Journal of Computacion y Sistemas
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A challenge in hybrid evolutionary algorithms is to employ efficient strategies to cover all the search space, applying local search only in actually promising search areas; on the other hand, clustering algorithms, a fundamental base for data mining procedures and learning techniques, suffer from the lack of efficient methods for determining the optimal number of clusters to be found in an arbitrary dataset. Some existing methods use evolutionary algorithms with cluster validation index as the
doi:10.13053/cys-18-2-2014-034
fatcat:ezybllp6pvdvvdtgagqtmaz65a
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... objective function. In this article, a new cellular evolutionary algorithm based on a hybrid model of global and local heuristic search is proposed for the same task, and extensive experimentation is done with different datasets and indexes.
A New Efficient Entropy Population-Merging Parallel Model for Evolutionary Algorithms
2017
International Journal of Computational Intelligence Systems
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In this paper a coarse-grain execution model for evolutionary algorithms is proposed and used for solving numerical and combinatorial optimization problems. This model does not use migration as the solution dispersion mechanism, in its place a more efficient population-merging mechanism is used that dynamically reduces the population size as well as the total number of parallel evolving populations. Even more relevant is the fact that the proposed model incorporates an entropy measure to
doi:10.2991/ijcis.10.1.78
fatcat:nhzyllcctnejlbt3mteclujmwa
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... ne how to merge the populations such that no valuable information is lost during the evolutionary process. Extensive experimentation, using genetic algorithms over a well-known set of classical problems, shows the proposed model to be faster and more accurate than the traditional one.
Efficiently Finding the Optimum Number of Clusters in a Dataset with a New Hybrid Cellular Evolutionary Algorithm
2014
Journal of Computacion y Sistemas
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
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A challenge in hybrid evolutionary algorithms is to employ efficient strategies to cover all the search space, applying local search only in actually promising search areas; on the other hand, clustering algorithms, a fundamental base for data mining procedures and learning techniques, suffer from the lack of efficient methods for determining the optimal number of clusters to be found in an arbitrary dataset. Some existing methods use evolutionary algorithms with cluster validation index as the
doi:10.13053/cys-18-1-2014-034
fatcat:sfypjdjjeja5feakcxeyeftfym
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... objective function. In this article, a new cellular evolutionary algorithm based on a hybrid model of global and local heuristic search is proposed for the same task, and extensive experimentation is done with different datasets and indexes.
Assigning Library of Congress Classification Codes to Books Based Only on their Titles
2010
Informatica
unpublished
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Many publishers follow the Library of Congress Classification (LCC) scheme to indicate a classification code on the first pages of their books. This is useful for many libraries worldwide because it makes possible to search and retrieve books by content type, and this scheme has become a de facto standard. However, not every book has been pre-classified by the publisher; in particular, in many universities, new dissertations have to be classified manually. Although there are many systems
fatcat:u73kj7pslbg3da72g6fn3acq6u
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... le for automatic text classification, all of them use extensive information which is not always available, such as the index, abstract, or even the whole content of the work. In this work, we present our experiments on supervised classification of books by using only their title, which would allow massive automatic indexing. We propose a new text comparison measure, which mixes two well-known text classification techniques: the Lesk voting scheme and the Term Frequency (TF). In addition, we experiment with different weighing as well as logical-combinatorial methods such as ALVOT in order to determine the contribution of the title in the correct classification. We found this contribution to be approximately one third, as we correctly classified 36% (on average by each branch) of 122,431 previously unseen titles (in total) upon training with 489,726 samples (in total) of one major branch (Q) of the LCC catalogue. Povzetek: Opisan je postopek klasifikacije knjig na osnovi naslovov v ameriški kongresni knjižnici.
Micro propagación de variedades nativas de cacao (Theobroma cacao) mediante embriogénesis somática
2017
Producción Agropecuaria y Desarrollo Sostenible
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<p>El cultivo del cacao (Theobroma cacao), en épocas precolombinas, fue de importancia económica y cultural en El Salvador; pero debido a las inclemencias del tiempo sobre la población nativa, parte del ...
Debido a este problema, se decidió implementar un sistema de micropropagación de árboles de cacao nativos de El Salvador para establecer un protocolo de rescate de materiales autóctonos; y posteriormente ...
Micro propagación de variedades nativas de cacao (Theobroma cacao) mediante embriogénesis somática Henry Omar Calderón Acuña -María Elena Montes de Godoy, El Salvador ...
doi:10.5377/payds.v6i0.5721
fatcat:elmszevfpfafnbl24rljmhvrkq
EVALUADORES DEL AÑO 2010
2011
Gaceta Sanitaria
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Gené, Joan
Gestoso Pazo, Juan Francisco
Gijón Sánchez, M a Teresa
Gil-González, Diana
Gili, Miguel
Gil-Lacruz, Marta
Gil-Lacruz, Ana
Godoy, Pere
Gómez, Anna
García Gómez, Montserrat
Gómez Pérez ...
Casasnovas, Guillem
López-Nicolás, Ángel
Lorenzo, Susana
Lozano, Oscar
Lunet, Nuño
Luque
Fernández,
Miguel
Angel
Malmusi, Davide
Maqueda, Jerónimo
Mar, Javier
March, Joan Carles
Márquez-Calderón ...
doi:10.1016/j.gaceta.2011.02.003
fatcat:ph62delrprf6vizi5v33b775py
GARCÍA GODOY, M.ª Teresa (ed.). «El español del siglo XVIII. Cambios diacrónicos en el primer español moderno». Bern, New York: Peter Lang, 2012
2013
Cuadernos Dieciochistas
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García-Godoy postula que, en el español dieciochesco, vuestra merced y usted coexistieron con usos y valores divergentes. ...
En este sentido, el español nicaragüense sigue procesos evolutivos semejantes al de otros países de América Central, como El Salvador, Honduras y Guatemala. ...
doaj:65b7a8c59c2241c5a8542eda6f75f826
fatcat:u2ezrjmyrnd7rolzztucrqmjwu
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