An approach to facilitate problem solving: Individualizing the problem proposition

This paper addresses one of the many facets of the problem-solving activity: the challenge inherent in the problem proposition. We have identified the problem proposition as a core element in obtaining efficient problem solving. The Educational Dimension Portfolio, EDP, is our proposal for individualizing the problem proposition. This paper presents EDP's characteristics and implications through testing the results of 491 IESE Business School executives from the European Union (EU) and Latin America (LA). We enumerate five working hypotheses and show their results. We also propose an Educational Delivery Approach (EDA) to help managers become manager-educators. We present the Socratic educational process, the apprenticeship process and the providing alternatives process as a guide to become a manager-educator.problem solving; problem proposition; operations management; manager-educator;

Four dimensions to induce learning: The challenge profile.

Knowledge generation is critical for company survival and managers need to face a new role: becoming educators. This requires an understanding of how knowledge is generated and what triggers individual learning. We propose that each individual has a personal predisposition to use a particular learning profile. Our findings show the Educational Dimensions Portfolio (EDP) as a gallery of profiles that match each individual's problem-solving challenge. A manager-educator can use the EDP model for triggering individual learning. We have verified, using statistical methods, that there are four EDP dimensions. They are related to both David Kolb's and Peter Honey's learning styles. We have verified that each individual has a personal predisposition to use a particular profile. We call it the challenge profile. That specific combination provides the individual's gateway not only to his own learning but also to inducing learning in others.manager as educator; innovation; challenge; learning styles; knowledge management;

Using business data to assess the impact of Covid-19 in Portuguese Private Sector Activity

Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceCOVID-19’s containment measures resulted in a severe shock to all national businesses. The supply and demand were strongly impacted due to suspending the companies' typical behavior and the physical absence of customers. More than ever, there is an increased need for data to monitor these effects quickly and affordably. Therefore, this project proposes to assess the endogenous determinants of Portuguese private sector firms in their financial performance during the first year of Covid-19, while showcasing secondary data's potential within private institutions. The main goal is to extract historical data from one of the largest Banks in Portugal with features that reflect important business characteristics and deliver essential insights into the evolution of national enterprises. Several linear regression models were implemented to study which business attributes, from 2019, made companies more fragile or robust to COVID-19’s outbreak. Hence, delivering knowledge to build catered solutions to the vast spectrum of Portuguese firms and protect them from the next shock. The results suggested that for the variation in total revenue, the variables responsible for the largest coefficients in absolute value were the accommodation and food services and the micro dimension category - both of which showcased a negative impact. Furthermore, the only positive coefficients were the features associated with exporting activity and the energy and manufactory sector. The number of employees was more impacted by the dimension of the company, whose negative impact was proportional to the size. The accommodation and food services, other services and wholesale and retail trading showcased having a significant adverse effect on this target variable, and exportation activity presented the only positive impact

Implementation of bots for multi-action adversarial game solving

Treball final de Grau en Disseny i Desenvolupament de Videojocs. Codi: VJ1241. Curs acadèmic: 2021/2022This document presents the report of a Final Degree Work consisting of a project that includes several components related to multi-action adversarial game solving. It involves the development of a multi-action adversarial card game that is capable of delivering relevant results on the performance of different algorithms. It also encompasses the development and testing of bots that play the game using several different algorithms, one of which entails a novel approach to solving these kind of games. Finally, as the main research action of the project, an experiment on the performance of the algorithms within the game was performed. Within each of the chapters of this report attention will be put into going trough all these components of the project. The framework architecture for A Simple MultiAction Card Game (ASMACAG) will be firstly presented. It is the simple but complete card game proposed as a tool to test, develop and debug bots that implement artificial intelligence algorithms in the context of adversarial multi-action games. Then the focus will be on the development process and the specifics of each of the algorithms included in the project, as well as the decisions taken on what parameters to use for them. Finally the experiment carried out within the game will be discussed, to further comprehend what conclusions can be drawn about the implemented bots and the game itself

Implementação de redes 5G baseadas em código aberto

Recently, a growth of mobile networks, from a huge connection of only a few devices, to the need for constant maintenance with support even with different technological needs. This requires increasing the capacity of networks to respond to user needs, increasing connection speeds and decreasing latencies. In many cases, the demand for the capabilities offered by the new generation of mobile networks, 5G, remains unanswered with conventional structures, especially in urban areas. As a viable option for these needs, the use of small cells emerged. The use of this equipment is facilitated due to the flexibility offered by the architecture of 5G mobile networks that facilitate the division of the same into functional units with a virtual implementation, thus helping to spread the coverage area. The growing interest in 5G mobile networks and the immense possibilities they offer have given rise to projects focused on the development of 5G mobile networks that are made available for consultation and use by the interested community. These networks are mostly implemented in a virtual way, with the exception of the component responsible for the emission of the radio signal, where some options will be presented for this purpose during the course of the dissertation. As a target of study and evaluation of the state of development and usefulness throughout this dissertation, OpenAirInterface was chosen from among these open-source projects. The complete implementation of the same is presented and described, as well as the tests carried out in order to determine which are the functional bandwidths and which are the options for optimizing its operation. To conclude the work carried out, the results and balance of these tests are presented in the form of speed and latency tests in various bandwidths, verification of occupancy of the same, flexibility in modifying the emission frequency, as well as the result of a test of connecting elements of mobile networks developed by different open-source projects as a way of evaluating the flexibility of these networks.Recentemente temos assistido a um crescimento enorme de redes móveis, desde a conexão de apenas alguns dispositivos, até à necessidade de manter ligação constante com múltiplos equipamentos com necessidades tecnológicas diferentes. Isto requer o aumento da capacidade das redes para dar resposta às necessidades dos utilizadores, aumentar velocidades de conexão e diminuir latências. Em muitos casos, a procura pelas capacidades oferecidas pela nova geração de redes móveis, o 5G, continua sem resposta com as estruturas convencionais, especialmente em áreas urbanas. Como opção viável para essas necessidades, surgiu o uso de small cells. O uso desse equipamento é facilitado devido à flexibilidade oferecida pela arquitetura de redes móveis 5G que facilitam a divisão da mesma em unidades funcionais com uma implementação virtual ajudando assim à propagação da área de cobertura. O interesse crescente de redes móveis 5G e as imensas possibilidades que as mesmas oferecem, fizeram surgir projetos focados no desenvolvimento de redes móveis 5G que são colocados disponíveis para consulta e uso da comunidade interessada. Estes redes são maioritariamente implementadas de forma virtual à exceção do componente responsável pela emissão do sinal rádio, onde serão apresentadas algumas opções para o efeito no decorrer da dissertação. Como alvo de estudo e avaliação do estado de desenvolvimento e utilidade ao longo desta dissertação, foi escolhida a OpenAirInterface de entre esses projetos open-source. É apresentada e descrita a implementação completa da mesma, assim como os testes efetuados no sentido de apurar quais as larguras de banda funcionais e quais as opções de otimização de funcionamento da mesma. Para concluir o trabalho realizado, é apresentado o resultado e balanço desses testes na forma de testes de velocidade e latência em várias larguras de banda, verificação de ocupação da mesma, flexibilidade em modificar a frequência de emissão, assim como o resultado de um teste de conexão de elementos de redes móveis desenvolvidos por projetos open-source diferentes como forma de avaliar a flexibilidade destas redes.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Un recorrido necesario sobre los estudios de juventudes en Argentina

El presente artículo es de carácter teórico y busca reconstruir el abordaje que han tenido las juventudes en Nuestra América. El objetivo es obtener insumos para desarrollar una propuesta teórico-metodológica para el abordaje de las prácticas y los discursos que los y las jóvenes de sectores populares. El mismo parte desde los orígenes del concepto juventud, su desarrollo en las Ciencias Sociales y ofrece una clasificación de los estudios sectoriales sobre jóvenes en Argentina. Se presta especial atención a aquellos que abordan la relación de los y las jóvenes con la política, en sus distintos formatos y colores. Con el fin de marcar algunos trazos para el abordaje de las prácticas de los y las jóvenes.This article is a theoretical approach that wants explore inside the youth studies in Latin America. The goal is to get inputs to develop a proposal for theoretical and methodological approach to the practices and discourses of young people from working class.We analyze the origins of the concept ‘youth’, its development in Social Sciences and we make a classification of youth’s sectorial studies in Argentina. We take special attention to those that study the relationship between politics and youth. Finally, we show some elements to make youth studies.Fil: Seca, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Ciencias Humanas, Sociales y Ambientales; Argentina. Universidad Nacional de Cuyo; Argentin

Volume Estimation of Standing Shorea sp. on UPM-JISE Rehabilitated Forest in Bintulu, Sarawak

This study was aimed to analyze the relationship between diameter at breast height, height, and volume of standing Shorea sp. and the relationship between age and volume of this species.  The study was conducted at different ages of rehabilitated forest in Bintulu Sarawak, where the measurement was taken from tree stand year 1992 until 2003.  The sampling plot of 20m x 20m was built for each age of stand. Ten standing Shorea sp. were randomly measured for sectionals (taper) from diameter at breast height until the free branches of the tree. The rest of the trees within the plot were only measured by diameter at breast height. All collected data were calculated to find basal area of each tree in meter square (m2).  The volume per plot was calculated using the Smalian’s formula to find the taper volume of the Shorea sp.  Statistical analysis was conducted to find the regression equation which could explain the relation between volume, diameter, and height of the tree.  Result showed that there was a relationship between volume, diameter, and height of the tree, and also there was relationship between volume and age of the tree.  Meanwhile, there was no relationship between taper of standing trees and age of trees. This means that volume taper of standing tree and age have no correlation

Design and control of parallel three phase voltage source Inverters in low voltage AC microgrid

Design and hierarchical control of three phase parallel Voltage Source Inverters are developed in this paper. The control scheme is based on synchronous reference frame and consists of primary and secondary control levels. The primary control consists of the droop control and the virtual output impedance loops. This control level is designed to share the active and reactive power correctly between the connected VSIs in order to avoid the undesired circulating current and overload of the connected VSIs. The secondary control is designed to clear the magnitude and the frequency deviations caused by the primary control. The control structure is validated through dynamics simulations.The obtained results demonstrate the effectiveness of the control structure

Explorations of the semantic learning machine neuroevolution algorithm: dynamic training data use and ensemble construction methods

Dissertation presented as the partial requirement for obtaining a Master’s degree in Data Science and Advanced AnalyticsAs the world’s technology evolves, the power to implement new and more efficient algorithms increases but so does the complexity of the problems at hand. Neuroevolution algorithms fit in this context in the sense that they are able to evolve Artificial Neural Networks (ANNs). The recently proposed Neuroevolution algorithm called Semantic Learning Machine (SLM) has the advantage of searching over unimodal error landscapes in any Supervised Learning task where the error is measured as a distance to the known targets. The absence of local optima in the search space results in a more efficient learning when compared to other neuroevolution algorithms. This work studies how different approaches of dynamically using the training data affect the generalization of the SLM algorithm. Results show that these methods can be useful in offering different alternatives to achieve a superior generalization. These approaches are evaluated experimentally in fifteen real-world binary classification data sets. Across these fifteen data sets, results show that the SLM is able to outperform the Multilayer Perceptron (MLP) in 13 out of the 15 considered problems with statistical significance after parameter tuning was applied to both algorithms. Furthermore, this work also considers how different ensemble construction methods such as a simple averaging approach, Bagging and Boosting affect the resulting generalization of the SLM and MLP algorithms. Results suggest that the stochastic nature of the SLM offers enough diversity to the base learner in a way that a simple averaging method can be competitive when compared to more complex techniques like Bagging and Boosting.À medida que a tecnologia evolui, a possibilidade de implementar algoritmos novos e mais eficientes aumenta, no entanto, a complexidade dos problemas com que nos deparamos também se torna maior. Algoritmos de Neuroevolution encaixam-se neste contexto, na medida em que são capazes de evoluir Artificial Neural Networks (ANNs). O algoritmo de Neuroevolution recentemente proposto chamado Semantic Learning Machine (SLM) tem a vantagem de procurar sobre landscapes de erros unimodais em qualquer problema de Supervised Learning, onde o erro é medido como a distância aos alvos conhecidos. A não existência de local optima no espaço de procura resulta numa aprendizagem mais eficiente quando comparada com outros algoritmos de Neuroevolution. Este trabalho estuda como métodos diferentes de uso dinâmico de dados de treino afeta a generalização do algoritmo SLM. Os resultados mostram que estes métodos são úteis a oferecer uma alternativa que atinge uma generalização competitiva. Estes métodos são testados em quinze problemas reais de classificação binária. Nestes quinze problemas, o algoritmo SLM mostra superioridade ao Multilayer Perceptron (MLP) em treze deles com significância estatística depois de ser aplicado parameter tuning em ambos os algoritmos. Para além disso, este trabalho também considera como diferentes métodos de construção de ensembles, tal como um simples método de averaging, Bagging e Boosting afetam os valores de generalização dos algoritmos SLM e MLP. Os resultados sugerem que a natureza estocástica da SLM oferece diversidade suficiente aos base learners de maneira a que o método mais simples de construção de ensembles se torne competitivo quando comparado com técnicas mais complexas como Bagging e Boosting