DESARROLLO DE UNA APLICACIÓN EN LENGUAJE JAVA UTILIZANDO LA METODOLOGÍA ANÁLISIS ESTRUCTURADO MODERNO

El objetivo de este trabajo fue implementar paso a paso la metodología de Edward Yourdon para el diseño de software; se aplicó a un caso práctico de desarrollo de software para determinar el nivel de riesgo ergonómico en puestos de trabajo utilizando el método REBA y lógica difusa. El software construido se probó en cuatro casos de estudio con un total de 16 posturas y permitió calcular de forma rápida el nivel de riesgo ergonómico para cada postura específica del trabajador.Palabras clave: Análisis estructurado, programación orientada a objetos, riesgo ergonómico, lógica difusa

Stackelberg game design and operation of a non-cooperative Bi-Level H2 supply chain under cournot equilibrium

This paper proposes a hybrid solution algorithm for the mixed-integer bi-level programming problem (MIBLP) as a mathematical model of the Stackelberg game with the novelty inclusion of multi-followers in competition. The solution strategy considers the MIBLP as a multi-parametric problem knowing that the feasible set of the lower level problem (LLP) of a bi-level programming problem (BLPP) is parametric in terms of the optimization variables of the upper level problem (ULP), under those circumstances is possible to solve each level with a different approach. To tackle the oligopoly (multi-player) competition in the LLP, a general static Cournot equilibrium model is proposed, with the particularities of non-differentiated product with asymmetric cost. The proposed hybrid algorithm implements Differential Evolution to solve the ULP while each feasible population member of each generation execute a MILP Solver to search for feasible LLP individuals sharing the market and looking to maximize their individual profit. The algorithm, which is a new method for the resolution of MIBLP, is illustrated through a modified numerical example from the literature adapted to Energy Markets. Competitive energy markets are the best way to keep prices as low as possible and create a climate that encourages economic growth, job creation and innovation. Demand and supply of energy are best determined through fair and competitive markets, meaning, well-designed competititve markets deliver better results than traditional monopoly markets. Until now, most of the Hydrogen Supply Chains (HSC) designs are treated as problems with single or multiple objectives without any hierarchical conflict, mainly in a centralized monopolic view point. Computational results prove the functionality of the proposed hybrid algoreithm on a ficticious HSC, the evidence highlights the impact between choosing a monopoly or an oligopoly production model.Peer ReviewedPostprint (author's final draft

Integration of Sentiment Analysis of Social Media in the Strategic Planning Process to Generate the Balanced Scorecard

Strategic planning (SP) requires attention and constant updating and is a crucial process for guaranteeing the efficient performance of companies. This article proposes a novel approach applied in a case study whereby a balanced scorecard (BSC) was generated that integrated sentiment analysis (SA) of social media (SM) and took advantage of the valuable knowledge of these sources. In this study, opinions were consolidated in the main dataset to incorporate sentiments regarding the strategic part of a restaurant in a tourist city. The proposed methodology began with the selection of the company. Information was then acquired to apply pre-processing, processing, evaluation, and validation that is capitalized in a BSC to support strategic decision-making. Python support was used in the model and comprised lexicon and machine learning approaches for the SA. The significant knowledge in the comments was automatically oriented toward the key performance indicators (KPIs) and perspectives of a BSC that were previously determined by a group of opinion leaders of the company. The methods, techniques, and algorithms of SA and SP showed that unstructured textual information can be processed and capitalized efficiently for optimal management and decision-making. The results revealed an improvement (reduced effort and time) to produce a more robust and comprehensive BSC with the support and validation of experts. Moreover, new resources and approaches were developed to implement more efficient SP. The model was based on the efficient coupling of both fields of study

A hybrid strategy for mixed integer bi-level optimization applied to hydrogen energy supply chain management

This paper addresses a supply chain management problem with consideration of production and distribution activities. The formulation is based on a mixed-integer bi-level programming approach as a mathematical model of the leader-follower game. A hybrid evolutionary-deterministic strategy has been developed and the performance of the solution method is evaluated by numerical experiments based on a ficticious hydrogen energy system. The experimental results obtained show that the resolution method is efficient and promising for dealing with multi-objective optimization cases.The National Council of Science and Technology of Mexico (Consejo Nacional de Ciencia y Tecnologia, CONACYT). Bourse reference: 2018-000003-01EXTF-00046, supported this work.Peer ReviewedPostprint (author's final draft

Integration of Sentiment Analysis of Social Media in the Strategic Planning Process to Generate the Balanced Scorecard

Strategic planning (SP) requires attention and constant updating and is a crucial process for guaranteeing the efficient performance of companies. This article proposes a novel approach applied in a case study whereby a balanced scorecard (BSC) was generated that integrated sentiment analysis (SA) of social media (SM) and took advantage of the valuable knowledge of these sources. In this study, opinions were consolidated in the main dataset to incorporate sentiments regarding the strategic part of a restaurant in a tourist city. The proposed methodology began with the selection of the company. Information was then acquired to apply pre-processing, processing, evaluation, and validation that is capitalized in a BSC to support strategic decision-making. Python support was used in the model and comprised lexicon and machine learning approaches for the SA. The significant knowledge in the comments was automatically oriented toward the key performance indicators (KPIs) and perspectives of a BSC that were previously determined by a group of opinion leaders of the company. The methods, techniques, and algorithms of SA and SP showed that unstructured textual information can be processed and capitalized efficiently for optimal management and decision-making. The results revealed an improvement (reduced effort and time) to produce a more robust and comprehensive BSC with the support and validation of experts. Moreover, new resources and approaches were developed to implement more efficient SP. The model was based on the efficient coupling of both fields of study

Green Supplier Selection in the Agro-Food Industry with Contract Farming: A Multi-Objective Optimization Approach

An important contribution to the environmental impact of agro-food supply chains is related to the agricultural technology and practices used in the fields during raw material production. This problem can be framed from the point of view of the Focal Company (FC) as a raw material Green Supplier Selection Problem (GSSP). This paper describes an extension of the GSSP methodology that integrates life cycle assessment, environmental collaborations, and contract farming in order to gain social and environmental benefits. In this approach, risk and gains are shared by both parties, as well as information related to agricultural practices through which the FC can optimize global performance by deciding which suppliers to contract, capacity and which practices to use at each supplying field in order to optimize economic performance and environmental impact. The FC provides the knowledge and technology needed by the supplier to reach these objectives via a contract farming scheme. A case study is developed in order to illustrate and a step-by-step methodology is described. A multi-objective optimization strategy based on Genetic Algorithms linked to a MCDM approach to the solution selection step is proposed. Scenarios of optimization of the selection process are studied to demonstrate the potential improvement gains in performance

Development of an Expert System as a Diagnostic Support of Cervical Cancer in Atypical Glandular Cells, Based on Fuzzy Logics and Image Interpretation

Cervical cancer is the second largest cause of death among women worldwide. Nowadays, this disease is preventable and curable at low cost and low risk when an accurate diagnosis is done in due time, since it is the neoplasm with the highest prevention potential. This work describes the development of an expert system able to provide a diagnosis to cervical neoplasia (CN) precursor injuries through the integration of fuzzy logics and image interpretation techniques. The key contribution of this research focuses on atypical cases, specifically on atypical glandular cells (AGC). The expert system consists of 3 phases: (1) risk diagnosis which consists of the interpretation of a patient’s clinical background and the risks for contracting CN according to specialists; (2) cytology images detection which consists of image interpretation (IM) and the Bethesda system for cytology interpretation, and (3) determination of cancer precursor injuries which consists of in retrieving the information from the prior phases and integrating the expert system by means of a fuzzy logics (FL) model. During the validation stage of the system, 21 already diagnosed cases were tested with a positive correlation in which 100% effectiveness was obtained. The main contribution of this work relies on the reduction of false positives and false negatives by providing a more accurate diagnosis for CN

Functional Evaluation Using Fuzzy FMEA for a Non-Invasive Measurer for Methane and Carbone Dioxide

This paper combines the use of two tools: Failure Mode and Effect Analysis (FMEA) and Fuzzy Logic (FL), to evaluate the functionality of a quantifier prototype of Methane gas (CH4) and Carbon Dioxide (CO2), developed specifically to measure the emissions generated by cattle. Unlike previously reported models for the same purpose, this device reduces damage to the integrity of the animal and does not interfere with the activities of livestock in their development medium. FMEA and FL are used to validate the device’s functionality, which involves identifying possible failure modes that represent a more significant impact on the operation and prevent the prototype from fulfilling the function for which it was created. As a result, this document presents the development of an intelligent fuzzy system type Mamdani, supported in the Fuzzy Inference System Toolbox of MatLabR2018b®, for generating a risk priority index. A Fuzzy FMEA model was obtained to validate the prototype for measuring Methane and Carbon Dioxide emissions, which allows considering this prototype as a reliable alternative for the reliable measurement of these gases. This study was necessary as a complementary part in the validation of the design of the prototype quantifier of CH4 and CO2 emissions. The methods used (classic FMEA and Fuzzy FMEA) to evaluate the RPN show asymmetric graphs due to data disparity. Values in the classical method are mostly lower than the Mamdani model results due to the description of the criteria with which it is evaluated

Effects of Ornamental Plant Density and Mineral/Plastic Media on the Removal of Domestic Wastewater Pollutants by Home Wetlands Technology

Wastewater treatment (WWT) is a priority around the world; conventional treatments are not widely used in rural areas owing to the high operating and maintenance costs. In Mexico, for instance, only 40% of wastewater is treated. One sustainable option for WWT is through the use of constructed wetlands (CWs) technology, which may remove pollutants using cells filled with porous material and vegetation that works as a natural filter. Knowing the optimal material and density of plants used per square meter in CWs would allow improving their WWT effect. In this study, the effect of material media (plastic/mineral) and plant density on the removal of organic/inorganic pollutants was evaluated. Low (three plants), medium (six plants) and high (nine plants) densities were compared in a surface area of 0.3 m2 of ornamental plants (Alpinia purpurata, Canna hybrids and Hedychium coronarium) used in polycultures at the mesocosm level of household wetlands, planted on the two different substrates. Regarding the removal of contaminants, no significant differences were found between substrates (p ≥ 0.05), indicating the use of plastic residues (reusable) is an economical option compared to typical mineral materials. However, differences (p = 0.001) in removal of pollutants were found between different plant densities. For both substrates, the high density planted CWs were able to remove COD in a range of 86–90%, PO4-P 22–33%, NH4-N in 84–90%, NO3-N 25–28% and NO2-N 38–42%. At medium density, removals of 79–81%, 26–32, 80–82%, 24–26%, and 39–41%, were observed, whereas in CWs with low density, the detected removals were 65–68%, 20–26%, 79–80%, 24–26% and 31–40%, respectively. These results revealed that higher COD and ammonia were removed at high plant density than at medium or low densities. Other pollutants were removed similarly in all plant densities (22–42%), indicating the necessity of hybrid CWs to increase the elimination of PO4-P, NO3-N and NO2-N. Moreover, high density favored 10 to 20% more the removal of pollutants than other plant densities. In addition, in cells with high density of plants and smaller planting distance, the development of new plant shoots was limited. Thus, it is suggested that the appropriate distance for this type of polyculture plants should be from 40 to 50 cm in expansion to real-scale systems in order to take advantage of the harvesting of species in these and allow species of greater foliage, favoring its growth and new shoots with the appropriate distance to compensate, in the short time, the removal of nutrients