Diseño de un modelo para mejorar los procesos de estimación de costos de software para las empresas desarrolladoras de software /

El presente proyecto de investigación que tiene como objetivo mejorar los procesos de estimación de costos de software para las empresas desarrolladoras con el propósito hacerlas más competitividad y realizar estimaciones más exacta, se llevará a cabo teniendo en cuenta los siguientes aspectos metodológicos: Primeramente, se procederá a estudiar los diferentes métodos de estimación de costos de software, sus ventajas y desventajas. Explorar el estado de las estimaciones de software en otros países, con el fin de obtener información de posibles mejoras para los métodos y proceso de estimación de costos. Se identificará la situación actual de Colombia en cuanto a la planificación de proyectos de software, teniendo en cuenta tiempo de entrega, cronograma y presupuesto establecido. En el siguiente capítulo, se explicará detalladamente la metodología utilizada, que es la base para diseñar el modelo de mejora de procesos de estimación de costos de software, realizando una evaluación de los diferentes escenarios o tendencias propuestos por medio del método Delphi. Al recopilar la información de valoración y clasificación de todos los expertos, se realiza un análisis estadístico por medio de un diseño experimental, arrojando una tendencia y consenso de los escenarios mejor evaluados. Para comprobar el modelo estadístico, se realizaron pruebas de independencia, igualdad de varianza y análisis de residuos. En el quinto capítulo, se estructuran los componentes con sus respectivos factores y niveles del modelo propuesto. Se explica cómo cada uno de los componentes interactúa a lo largo de vida del desarrollo del software y se establece la matriz del modelo para identificar los niveles por factores.Incluye anexos, glosarioIncluye bibliografí

Determinantes de eco-innovación en clústers industriales. Una aplicación empírica en el departamento del Atlántico

[ES] La eco-innovación se define como el desarrollo de productos y procesos que contribuyen al respeto y avance en ámbito medioambiental, aplicando estrategias hacia la búsqueda de soluciones de diferenciación y posicionamiento en el mercado de manera sostenible. La eco-innovación en clústers industriales tiene como objetivo unir competitividad y sostenibilidad, convirtiendo a los agentes del clúster en unidades vivas de la economía. Entre las ventajas del clúster se denota la especialización y efecto derrame que, al introducir la eco-innovación, logra mucho más rápido la expansión de ventajas ambientales y beneficios a todas las empresas integradas en este, logrando un equilibrio entre la competencia y la colaboración de actividades eco-innovadoras. El objetivo de este estudio es determinar cuáles son esos determinantes o factores que generar eco-innovación en los clústers industriales. Para el estudio empírico, se escogió el clúster metalmecánico de la ciudad de Barranquilla en Colombia, considerado un clúster artificial o iniciativa clúster, siendo su reto principal mejorar la integración, especialización y competitividad por su carácter único y su importancia en la región. Para desarrollar esta tesis doctoral, tras una detallada revisión de la bibliografía, se plantearon 15 hipótesis, que se analizaron a través de la regresión multivariante y de productos cruzados. Se diseñó y aplicó un cuestionario a 40 empresas del clúster industrial metalmecánico compuesto por 44 preguntas, divididas a su vez en 8 factores. La aplicación de los modelos de regresión permitió comprobar la fiabilidad y validez de los constructos establecidos, pero no la comprobación de las hipótesis propuestas, ya que la consistencia era muy débil; es decir se contaba con resultados asimétricos. Se recurrió entonces al análisis de productos cruzados hacia delante para intentar mejorar la asimetría en el análisis de variables, aunque los resultados seguían siendo poco significativos. Finalmente, se aplicó el análisis cualitativo comparativo FsQCA, que trabaja datos asimétricos y relaciones causales. La aplicación de la técnica FsQCA, permitió establecer un conjunto de combinaciones causales que logran generar altos niveles de eco-innovación. Utilizando el Análisis Cualitativo Comparativo de Conjuntos Difusos (FsQCA), se persigue identificar si existe algún factor que sea condición necesaria para la eco-innovación, así como combinaciones de antecedentes causales capaces de explicar la eco-innovación en clúster industriales. Los resultados conducen a que no existe una condición necesaria por sí misma y que existen diversos conjuntos de soluciones suficientes que conducen a niveles altos y bajos de eco-innovación y varían conforme a lograr resultados de tipo económico, ambiental y de acceso a nuevos mercados para las empresas del clúster. Así, los resultados indican que: demanda, presión competitiva y las políticas, son ingredientes importantes para lograr efectos de innovación ambiental en el clúster, atendiendo al nivel de consistencia en los resultados (90%). Entre los resultados más destacables se observa que, al combinar los factores de capacidad, presión competitiva y desarrollo e implementación de políticas y regulaciones ambientales, se constata una influencia positiva para las empresas del clúster en los aspectos relativos al acceso a nuevos mercados, siendo esta la combinación con mayor consistencia (con un 91% de las cuatro configuraciones suficientes para lograr acceder a nuevos mercados). Por otra parte, para lograr altos niveles de resultados económicos en el clúster se destaca la combinación causal de ausencia de capacidades, cooperación y ausencia de presión competitiva como factores importantes en esta receta. El análisis arroja una consistencia del 87% y es de notar que, aunque existan niveles bajos de capacidades, y competitividad y poca presión competitiva, basta con que exista alto nivel de cooperación entre las empresa[CA] L'ecoinnovació es defineix com el desenvolupament de productes i processos que contribueixen al respecte i avanç en l'àmbit mediambiental, aplicant estratègies cap a la cerca de solucions de diferenciació i posicionament en el mercat de manera sostenible. L'ecoinnovació en clústers industrials té com objectiu unir competitivitat i sostenibilitat, convertint als agents del clúster en unitats vives de l'economia. Entre els avantatges del clúster es denota l'especialització i efecte vesse que, en introduir l'ecoinnovació, aconsegueix molt més ràpid l'expansió d'avantatges ambientals i beneficis a totes les empreses integrades en aquest, aconseguint un equilibri entre la competència i la col·laboració d'activitats eco-innovadores. L'objectiu d'aquest estudi és determinar quins són aqueixos determinants o factors que generar ecoinnovació en els clústers industrials. Per a l'estudi empíric, es va triar el clúster metalmecánico de la ciutat de Barranquilla a Colòmbia, considerat un clúster artificial o iniciativa clúster, sent el seu repte principal millorar la integració, especialització i competitivitat pel seu caràcter únic i la seua importància a la regió. Per a desenvolupar aquesta tesi doctoral, després d¿una detallada revisió de la bibliografia, es van plantejar 15 hipòtesi, que es van analitzar a través de la regressió multivariant i de productes creuats. Es va dissenyar i va aplicar un qüestionari a 40 empreses del clúster industrial metalmecánico compost per 44 preguntes, dividides al seu torn en 8 factors. L'aplicació dels models de regressió va permetre comprovar la fiabilitat i validesa dels constructes establits, però no la comprovació de les hipòtesis proposades, ja que la consistència era molt feble; és a dir es comptava amb resultats asimètrics. Es va recórrer llavors a l'anàlisi de productes creuats cap avant per a intentar millorar l'asimetria en l'anàlisi de variables, encara que els resultats continuaven sent poc significatius. Finalment, es va aplicar l'anàlisi qualitativa comparativa FsQCA, que treballa dades asimètriques i relacions causals. L'aplicació de la tècnica FsQCA, va permetre establir un conjunt de combinacions causals que aconsegueixen generar alts nivells d'ecoinnovació. Utilitzant l'Anàlisi Qualitativa Comparativa de Conjunts Difusos (FsQCA), es persegueix identificar si existeix algun factor que siga condició necessària per a l'ecoinnovació, així com combinacions d'antecedents causals capaços d'explicar l'ecoinnovació en clúster industrials. Els resultats condueixen al fet que no existeix una condició necessària per si mateixa i que existeixen diversos conjunts de solucions suficients que condueixen a nivells alts i baixos d'ecoinnovació i varien conforme a aconseguir resultats de tipus econòmic, ambiental i d'accés a nous mercats per a les empreses del clúster. Així, els resultats indiquen que: demanda, pressió competitiva i les polítiques, són ingredients importants per a aconseguir efectes d'innovació ambiental en el clúster, atés el nivell de consistència en els resultats (90%). Entre els resultats més destacables s'observa que, en combinar els factors de capacitat, pressió competitiva i desenvolupament i implementació de polítiques i regulacions ambientals, es constata una influència positiva per a les empreses del clúster en els aspectes relatius a l'accés a nous mercats, sent aquesta la combinació amb major consistència (amb un 91% de les quatre configuracions suficients per a aconseguir accedir a nous mercats). D'altra banda, per a aconseguir alts nivells de resultats econòmics en el clúster es destaca la combinació causal d'absència de capacitats, cooperació i absència de pressió competitiva com a factors importants en aquesta recepta.[EN] Eco-innovation is defined as the development of products and processes that contribute to respect and progress in the environmental field, applying strategies towards the search for differentiation solutions and positioning in the market in a sustainable way. Eco-innovation in industrial clusters has the objective of uniting competitiveness and sustainability, of converting the agents of the cluster into living units of the economy. Among the advantages of the cluster is the specialization and spillover effect, which by introducing eco-innovation achieves much faster the expansion of environmental advantages and benefits to all the companies attached to it, achieving a balance between competition and a high collaboration of eco-innovative activities. The objective of this study is to determine which are those determinants or factors that generate eco-innovation in industrial clusters. For the empirical study, the metal-mechanical cluster of the city of Barranquilla in Colombia was chosen. This cluster is considered an artificial cluster or cluster initiative, its main challenge being to improve integration, specialization and competitiveness due to its unique nature and its importance in the region. To develop this study, an eco-innovation model in industrial clusters was proposed, consisting of 15 hypotheses analyzed by multivariate regression and cross products, a questionnaire was designed and applied to 40 companies of the metal-mechanical industrial cluster with 44 questions, divided into 8 factors. The application of the regression models allowed to verify the reliability and validity of the established constructs, but not the verification (acceptance or rejection) of the proposed hypotheses, since the consistency was very weak. In other words, there were asymmetric results, so forward cross-product analysis was used to try to improve the asymmetry in the analysis of variables, but it was still not very significant. Finally, the FsQCA comparative qualitative analysis was used, which works with asymmetric data and causal relationships. The application of FsQCA allowed to establish a set of causal combinations that in combination manage to generate high levels of eco-innovation. Using the Fuzzy Sets Comparative Qualitative Analysis (FsQCA) an attempt was made to identify whether there is any factor that is a necessary condition for cluster eco-innovation, as well as combinations of causal antecedents capable of explaining industrial clustering eco-innovation. The results lead to the fact that there is no necessary condition by itself and that there are several sets of sufficient solutions that lead to high and low levels of eco-innovation and vary according to achieving economic, environmental and access to new markets results for the cluster companies.The results indicate that demand, competitive pressure, and policies due to their level of consistency in results (90%) are important ingredients to achieve environmental innovation effects in the cluster. By combining the factors of capacity, competitive pressure and the development and implementation of environmental policies and regulations, a positive influence is presented for the cluster companies to access new markets; This being the most consistent combination with 91% of the four configurations sufficient to gain access to new markets. On the other hand, to achieve high levels of economic results in the cluster, the causal combination of the absence of capacities, cooperation and the absence of competitive pressure stands out as important factors in this recipe. The analysis shows a consistency of 87% and it is noteworthy that, although there are low levels of skills and competitiveness and little competitive pressure, it is enough that there is a high level of cooperation between the cluster companies to be able to generate economic results.Mercado Caruso, NN. (2022). Determinantes de eco-innovación en clústers industriales. Una aplicación empírica en el departamento del Atlántico [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181583TESI

Managing human resources resistance to organizational change in the context of innovation

Current global and complex economies demand change and restructuring processes. Besides the usual continuous change in their personal lives, when talking about changes in their working environment, employees offer considerable resistance. Difficulties related to managing this resistance on the part of the company will ultimately lead to organizational failure. Aimed at filling this gap, the present research provides a management model addressing both implicit and explicit resistance. The model comprises six key factors: leadership, communication, valuable HR retention, training, participation, and flexibility. Besides the theoretical model, it has been carried out a case study of a multinational company in the mechanical engineering sector, providing researchers and professionals with a roadmap of actions to manage the identified key factors. Furthermore, results reveal that Human Resources are no longer operational support. Instead, they represent a crucial asset to achieve the expected results in innovation and obtaining a sustainable competitive advantag

Factors that describe the use of digital devices in Latin American universities

Mobile digital devices are at the same time a tool for social interaction, an individual learning resource and can be a valuable contribution in the context of higher education to develop and promote new teaching and learning models. Recent studies show that both the more traditional pedagogical models of face-to-face teaching and distance teaching mediated by Virtual Learning Environments (VLE) can be enhanced by the use of these devices on and off campus. Likewise, the current context of Higher Education urges university institutions to promote a series of generic and specific competencies, where the use of these devices in a personal, academic and professional way acquires an outstanding value in the European Higher Education Area (EHEA), and represents an enrichment of university educational practice. This paper presents a study of the didactic and social use made by Hispanic American university students in 10 universities in several areas in order to establish common and divergent patterns of use so that useful conclusions can be extrapolated to improve the educational context of Higher Education in the Hispanic world

Artificial techniques applied to the improvement of the previous signals in the power amplifiers

A rapid evolution in electronic systems has been experienced in recent years, and one of the fields where this development has been notorious is the telecommunication systems in which users demand more and better services and with higher data transfer speeds. This has generated the need to develop new devices, algorithms and systems that manage to satisfy the requirements demanded y new technologies. An example of the above is the front-end of telecommunication systems. Systems need to be more efficient, but some elements of the systems, as the power amplifier, present nonlinearity when operating in its most efficient region, causing that it has to make a commitment between efficiency and linearity. This paper presents a comparison of different artificial neural network architectures, as a behavioral modeling method, to perform digital predistortion of power amplifiers

Design of a Network with wireless sensor applied to data transmission based on IEEE 802.15.4 standard

The problem of data transmission in wireless sensor networks (WSN), with real time guarantees, is an issue that has important references in the international scientific community, but that still does not have a solution that can completely satisfy this requirement [1]. Therefore, real time data transmission with WSN is considered an open issue with many possibilities of improvement. In this sense, this document presents a new procedure to ensure this type of transmission with WSN, particularly from the planning of the resources available for data transmission in the network, taking as a reference the IEEE 802.15.4 standard

Unbalanced data processing using oversampling: machine Learning

Nowadays, the DL algorithms show good results when used in the solution of different problems which present similar characteristics as the great amount of data and high dimensionality. However, one of the main challenges that currently arises is the classification of high dimensionality databases, with very few samples and high-class imbalance. Biomedical databases of gene expression microarrays present the characteristics mentioned above, presenting problems of class imbalance, with few samples and high dimensionality. The problem of class imbalance arises when the set of samples belonging to one class is much larger than the set of samples of the other class or classes. This problem has been identified as one of the main challenges of the algorithms applied in the context of Big Data. The objective of this research is the study of genetic expression databases, using conventional methods of sub and oversampling for the balance of classes such as RUS, ROS and SMOTE. The databases were modified by applying an increase in their imbalance and in another case generating artificial noise

Identifying Endogenous and Exogenous Indicators to Measure Eco-Innovation within Clusters

Scientific and business environment literature shows that green, sustainable innovation or eco-innovation has proven to be a source of competitive advantage today. The industrial clusters, their dynamism, and the synergies created within them attract a lot of attention from the scientific community. However, to date, the joint study of these two concepts and, more specifically, the factors that drive eco-innovation specifically in a cluster, have not been studied in depth. This article models eco-innovation in industrial clusters, thus addressing this gap and proposing a model based on information gathered from the literature and a detailed analysis of behavior in relation to eco-innovation in different sectors. Results suggest that including eco-innovation variables and measures may have positive implications such as improvements at the strategic level and the reduction of costs and use of resources. An eco-innovation model for clusters is proposed. It considers eight key factors that seek to raise its competitive level by promoting eco-innovation within clusters. The model includes five internal factors that analyze business capabilities and three external factors that study the effect of launching eco-innovative activities. This model could help the companies’ managers and those responsible for clusters in creating more successful strategies to increase competitiveness by enhancing eco-innovation. It could also serve as a guide for government entities in the performance of eco-innovative activities in economic sector

Impact of class imbalance on convolutional neural network training in multi-class problems

Image classification is the process of assigning an image one or multiple tags that describe its content. To perform the classification, a model must be designed for learning the labels to be assigned to a given image. The assignment is made through a learning process that uses a set of previously labeled training images, which must be large enough to guarantee efficient training. Many approaches have been researched to find optimal solutions to classification problems, however, databases with large amounts of images and the increased processing power of GPUs have made convolutional neural networks (CNNs) the best choice, as they outperform traditional algorithms. This paper presents a systematic analysis aimed at understanding how the issue of class inequality affects the efficiency of a convolutionary neural network trained for a task of image classification, and presents a technique for correcting the overtraining and that the network generalization