Instituto Tecnologico De Orizaba
Veracruz, Mexico
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Gomez-Rubio P.,University of Arizona | Meza-Montenegro M.M.,Instituto Tecnologico De Orizaba | Cantu-Soto E.,Instituto Tecnologico De Orizaba | Klimecki W.T.,University of Arizona
Journal of Applied Toxicology | Year: 2010

Differences in arsenic metabolism are known to play a role in individual variability in arsenic-induced disease susceptibility. Genetic variants in genes relevant to arsenic metabolism are considered to be partially responsible for the variation in arsenic metabolism. Specifically, variants in arsenic (3+ oxidation state) methyltransferase (AS3MT), the key gene in the metabolism of arsenic, have been associated with increased arsenic methylation efficiency. Of particular interest is the fact that different studies have reported that several of the AS3MT single nucleotide polymorphisms (SNPs) are in strong linkage-disequilibrium (LD), which also extends to a nearby gene, CYP17A1. In an effort to characterize the extent of the region in LD, we genotyped 46 SNPs in a 347 000 base region of chromosome 10 that included AS3MT in arsenic-exposed subjects from Mexico. Pairwise LD analysis showed strong LD for these polymorphisms, represented by a mean r2 of 0.82, spanning a region that includes five genes. Genetic association analysis with arsenic metabolism confirmed the previously observed association between AS3MT variants, including this large cluster of linked polymorphisms, and arsenic methylation efficiency. The existence of a large genomic region sharing strong LD with polymorphisms associated with arsenic metabolism presents a predicament because the observed phenotype cannot be unequivocally assigned to a single SNP or even a single gene. The results reported here should be carefully considered for future genomic association studies involving AS3MT and arsenic metabolism. Copyright © 2009 John Wiley & Sons, Ltd.

Colombo-Mendoza L.O.,University of Murcia | Valencia-Garcia R.,University of Murcia | Rodriguez-Gonzalez A.,University of La Rioja | Alor-Hernandez G.,Instituto Tecnologico De Orizaba | Samper-Zapater J.J.,University of Valencia
Expert Systems with Applications | Year: 2014

Recommender systems are used to provide filtered information from a large amount of elements. They provide personalized recommendations on products or services to users. The recommendations are intended to provide interesting elements to users. Recommender systems can be developed using different techniques and algorithms where the selection of these techniques depends on the area in which they will be applied. This paper proposes a recommender system in the leisure domain, specifically in the movie showtimes domain. The system proposed is called RecomMetz, and it is a context-aware mobile recommender system based on Semantic Web technologies. In detail, a domain ontology primarily serving a semantic similarity metric adjusted to the concept of "packages of single items" was developed in this research. In addition, location, crowd and time were considered as three different kinds of contextual information in RecomMetz. In a nutshell, RecomMetz has unique features: (1) the items to be recommended have a composite structure (movie theater + movie + showtime), (2) the integration of the time and crowd factors into a context-aware model, (3) the implementation of an ontology-based context modeling approach and (4) the development of a multi-platform native mobile user interface intended to leverage the hardware capabilities (sensors) of mobile devices. The evaluation results show the efficiency and effectiveness of the recommendation mechanism implemented by RecomMetz in both a cold-start scenario and a no cold-start scenario. © 2014 Elsevier Ltd. All rights reserved.

Perez-Gallardo Y.,Charles III University of Madrid | Alor-Hernandez G.,Instituto Tecnologico De Orizaba | Cortes-Robles G.,Instituto Tecnologico De Orizaba | Rodriguez-Gonzalez A.,Polytechnic University of Mozambique
Expert Systems with Applications | Year: 2013

Collective intelligence (CI) is an active field of research, which capitalizes the knowledge of human collectives in order to create, to innovate and to invent. There are two important mechanisms to implement CI: recommender and reputation systems. Recommender systems are used to provide filtered information from a large amount of elements. The recommendations are intended to provide interesting elements to users. Recommendation systems can be developed using different techniques and algorithms where the selection of these techniques depends on the area in which they will be applied. This work presents iPixel Recommender Engine, which is focused on the medical field. iPixel Recommendation Engine supports the process of differential diagnosis by recommending mammographic evaluations. Each mammogram is collectively tagged by the users' community with a semantic sense; this feature allows iPixel acquires collective knowledge. iPixel can associate more than one feature with each mammogram. This work also presents a qualitative evaluation, where the basic features that a recommendation system should have in the medical field were obtained. Finally, a comparison was carried out with other similar recommender systems in order to know the Pixel advantages. © 2012 Elsevier B.V. All rights reserved.

Rodriguez-Gonzalez A.,Polytechnic University of Mozambique | Alor-Hernandez G.,Instituto Tecnologico De Orizaba
Computers in Biology and Medicine | Year: 2013

The capability of medical diagnosis systems to provide results in different situations depends on the modeling of the knowledge base. In the case of high sensitivity systems, the capability of having an adequate model allows to increase the accuracy of the system even in situations where the number of input elements is low. In this context the concept of multi-level diagnosis emerges, where a pathology can be assumed as a diagnostic element of another pathology (acting as a finding). In this paper this concept is studied in depth from the modeling point of view, providing a solution based on rule inference techniques modeled with semantic technologies, and allowing solving the problem generated by multi-level diagnosis. © 2012 Elsevier Ltd.

Negny S.,ENSIACET | Belaud J.P.,ENSIACET | Cortes Robles G.,Instituto Tecnologico De Orizaba | Roldan Reyes E.,ENSIACET | Ferrer J.B.,ENSIACET
Journal of Cleaner Production | Year: 2012

Chemical industries have the potential to become a driving force to introduce efficient production practices for reducing the negative impact on the environment. In order to meet these environmental challenges, innovation is a key factor in turning the concept of green growth into a reality through the development of eco-friendly technologies and sustainable production. Therefore, to accelerate and improve the design of eco-inventive solutions, new approaches must be created and adapted to integrate the constraints of eco-invention in the preliminary design. The purpose of this paper is to present the first elements of a computer aided eco-innovation system to support the engineers in preliminary design. This research paper proposes a method based on a synergy between the Theory of Inventive Problem Solving (TRIZ) and the Case Based Reasoning. However, the typical level of abstraction of the TRIZ tools is modified. Indeed, TRIZ only gives way or guidelines to explore in order to find an inventive solution, which are often too abstract and hard to traduce into an inventive concept. To reduce this level of abstraction, this work proposes to apply the physical, chemical, biological, geometrical effects or phenomenon as solutions as they are more concrete. This is done thanks to a resources oriented search in order to better exploit the resources encompassed in the system. A case study on a new production process in chemical engineering illustrates the effectiveness of the proposed approach. © 2012 Elsevier Ltd. All rights reserved.

Colomo-Palacios R.,Charles III University of Madrid | Sanchez-Cervantes J.L.,Charles III University of Madrid | Alor-Hernandez G.,Instituto Tecnologico De Orizaba | Rodriguez-Gonzalez A.,Charles III University of Madrid
International Journal of Human Capital and Information Technology Professionals | Year: 2012

The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. To make the Semantic Web or Web of Data a reality, it is necessary to have a large volume of data available in a standard, reachable, and manageable format. This collection of interrelated data on the Web can also be referred to as Linked Data. Linked Data is the large scale integration of and reasoning on, data on the Web. Supporting the adoption of semantic Web technologies, there exist tools oriented to creation, publication, and management of data, and a big subset for Linked Data. However, an important weakness in this area is that it has not completely established a formal reference that integrates the necessary infrastructure in terms of components. This lack implies a slower technological adoption, covering both the public and private sectors. This paper explores the emergence of the Semantic Web and Linked Data, and their potential impact on IT industry. The main advantages of using Linked Data are discussed from an IT professional perspective where the capability of having standard technologies and techniques to access and manipulate the information is an important achievement in the application of Linked Data. Copyright © 2012, IGI Global.

Paredes-Valverde M.A.,University of Murcia | Rodriguez-Garcia M.A.,University of Murcia | Ruiz-Martinez A.,University of Murcia | Valencia-Garcia R.,University of Murcia | Alor-Hernandez G.,Instituto Tecnologico De Orizaba
Expert Systems with Applications | Year: 2015

The Semantic Web has emerged as an extension of the current Web, in which Web content has well-defined meaning through the addition of logic-based metadata. However, current mechanisms for information retrieval from semantic knowledge bases restrict their use to only experienced users. To address this gap, the natural language processing (NLP) is deemed to be very intuitive from a use point of view, due to it hides the formality of a knowledge base as well as the executable query language. This paper presents a novel ontology-based information retrieval system for DBpedia called ONLI (Ontology-based Natural Language Interface). ONLI proposes the use of an ontology model in order to represent both the syntactic question's structure and the question's context. This model allows inferring the answer type expected by the user through an established question's classification. These features allow reducing the search space thus increasing the probability of providing the correct answer. From this perspective, ONLI was evaluated in terms of their ability to find the correct answer into DBpedia's content, achieving promising results and proving to be very useful to non-experienced users. © 2015 Elsevier Ltd. All rights reserved.

Velazquez-Camilo O.,Metropolitan Autonomous University | Bolanos-Reynoso E.,Instituto Tecnologico De Orizaba | Rodriguez E.,Metropolitan Autonomous University | Alvarez-Ramirez J.,Metropolitan Autonomous University
Journal of Food Engineering | Year: 2010

Automated image analysis has emerged as a useful tool for quality evaluation and inspection of food processes and products. Image analysis techniques are aimed to the extraction of features for quantifying texture, shapes and distributions of irregular geometries recasted on a microscopy image. The monitoring of crystal growth evolution in traditional industrial processes commonly relies on the visual expertise of long-term trained operators, which limits seriously the automated operation of the process. The objective of this study was to investigate the potential usefulness of fractal metrics; namely Fourier analysis fractal dimension and lacunarity using images, as quantitative descriptors of crystallization evolution. To our knowledge this is the first reported use of lacunarity for the characterization of images of crystallization images from direct samples of crystallization slurries. Fractal dimension and lacunarity increase with the crystallization time. Increased fractal dimension was related to the formation of large clusters in the image, and was taken as an indicative of the amount of formed crystals. On the other hand, lacunarity is an index of non-uniformity of particles on the image, such that lacunarity can be considered as an indicator of the crystal shape and size diversity. In an overall sense, the results showed that fractal analysis can be incorporated as a complementary tool for monitoring the evolution of cane sugar crystallization process. © 2010 Elsevier Ltd. All rights reserved.

Rendon-Sagardi M.A.,Instituto Tecnologico De Orizaba | Sanchez-Ramirez C.,Instituto Tecnologico De Orizaba | Cortes-Robles G.,Instituto Tecnologico De Orizaba | Alor-Hernandez G.,Instituto Tecnologico De Orizaba | Cedillo-Campos M.G.,Autonomous University of Nuevo León
Applied Energy | Year: 2014

Since ethanol is considered an essential additive for biofuel production, there may be the opportunity to employ it as such in Mexico. However, an analysis of the ethanol supply chain should be performed first. Therefore, in order to analyze the main variables of the ethanol supply chain, as well as the feasibility for its use, the present research developed a System Dynamics model based on an idea suggested by SENER (Secretariat of Energy in Mexico). The model explores five possible scenarios (between 2014 and 2030), and evaluates the availability of area for the sowing of sugarcane and grain sorghum crops, the production capacity for ethanol and fuel, as well as the possible reduction of carbon dioxide emissions. The model considers the trends and parameters of the agricultural and energy industries, and produces valuable information about future conditions of the Mexican biofuel and fossil fuel production and supply. The obtained results predicted two situations. First, Mexico would face a fuel shortage in the future. Second, from the amount of fuel available by that time, the biofuel produced and accumulated would collaborate little to meet the domestic fuel demand. Also, as System Dynamics is concerned, it is demonstrated that it is a powerful methodology to simulate and understand the biofuel supply chains in emerging markets as Mexico. © 2014 Elsevier Ltd.

Cedillo-Campos M.,Autonomous University of Nuevo León | Sanchez-Ramirez C.,Instituto Tecnologico De Orizaba
Journal of Applied Research and Technology | Year: 2013

A dynamic self-assessment of performance on supply chains operating in emerging markets is proposed. Based on wellestablished key performance indicators (KPI), this paper provides a decision support aid. Although it has been validated in the automotive industry, the standardized model's approach makes it applicable to other industries. It is the result of a large literature review and identification of best practices from the automotive industry in which the lack of dynamic tools to evaluate logistics performance of suitable supply chains to the current competitive exchange rate was detected. Developed under a system dynamics approach (DS), the model analyzes different scenarios taking into account KPI and its dynamic relationships. The results obtained were validated through the statistical technique of design of experiments (DOE). This model also considers the specific features of the automotive operations in emerging countries as well as their importance in the future development of the manufacturing industry. In this context, the tool exposed is a key backup to decision making and to dynamically evaluate the variables with major influence on manufacturing supply chains. As a conclusion, findings are discussed and future researches are presented.

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