Miracle-dz/UniFAR-FTUs huggingface dataset:
Generación de comportamientos de enjambre en robots móviles a través del uso del aprendizaje por refuerzo.

En este trabajo se hace uso de tecnicas de aprendizaje por refuerzo (Q-Learning) con el objetivo de entrenar un grupo de robots para generar comportamientos de enjambre. Se presentan dos posibles soluciones con diferentes enfoques. En la primera solucion propuesta se establecen los estados del robot en funcion de la distancia de sus dos vecinos mas cercanos. En la segunda solucion propuesta se definen un radio de atraccion y otro radio de repulsion, y los estados se establecen segun la cantidad de vecinos dentro de cada uno de los radios divididos en los cuatro cuadrantes locales del robot. Para cada solucion propuesta se definen las acciones del robot y se propone una politica de premios y castigos. Cada robot se conecta con sus vecinos una vez que ha alcanzado una distancia prudente. Se hace uso de teoria de grafos para medir la conectividad del enjambre y saber si la topologia del grafo que forma el enjambre al final de la simulacion es conexo o no. En este trabajo se asume que la comunicacion de cada agente con sus vecinos ya esta resuelta. Se realizan varias pruebas en Matlab para cada una de las soluciones propuestas variando el numero de robots del enjambre. Finalmente se prueba la segunda solucion propuesta en V-rep usando robots cuadricopteros virtuales. Este documento esta estructurado de la siguiente forma: En el capitulo 1 y 2 se define el problema y la justificacion. El capitulo 3 y 4 contienen una revision de trabajos relacionados con robotica de enjambre y se definen los objetivos del proyecto. En el capitulo 5 se presentan los conceptos teoricos necesarios utilizados en el desarrollo de este proyecto. En el capitulo 6 y 7 se muestra el diseno metodologico, la administracion del proyecto, cronograma de actividades y presupuesto para el proyecto. En el capitulo 8 se muestra el trabajo previo a la realizacion de este proyecto usando logica difusa. En el capitulo 9 y 10 se muestra el diseno del proyecto, el planteamiento de las soluciones propuestas, - las pruebas y resultados de las dos soluciones. Finalmente, las conclusiones se muestran en el capitulo 11.
Classification of Melanoma on Dermoscopy Images using SVM Classifier

: By analyzing the dermoscopy pictures, a unique technique is developed for classifying melanocytic tumors as benign or malignant. The algorithm contains the following steps: first, lesions extracted using k-means method; then second, features are extracted; and third, lesion classification by using a classifier based on a Support Vector Machine (SVM) model. Lesions occur that are overlarge to be entirely contained among the dermoscopy image. To influence this tough presentation, new features are proposed, and which are able to characterize border irregularities on both complete and incomplete lesions. In this model, to achieve improved performance a SVM classifier is intended. Experiments are administered on two numerous dermoscopy databases that embrace images of both the xanthous and caucasian races. The results show that classification accuracy is greatly enhanced by the employment of the new features and also the proposed classifier model.
Genetic determination and layout rules of visual cortical architecture

The functional architecture of the primary visual cortex is set up by neurons that preferentially respond to visual stimuli with contours of a specific orientation in visual space. In primates and placental carnivores, orientation preference is arranged into continuous and roughly repetitive (iso-) orientation domains. Exceptions are pinwheels that are surrounded by all orientation preferences. The configuration of pinwheels adheres to quantitative species-invariant statistics, the common design. This common design most likely evolved independently at least twice in the course of the past 65 million years, which might indicate a functionally advantageous trait. The possible acquisition of environment-dependent functional traits by genes, the Baldwin effect, makes it conceivable that visual cortical architecture is partially or redundantly encoded by genetic information. In this conception, genetic mechanisms support the emergence of visual cortical architecture or even establish it under unfavorable environments. In this dissertation, I examine the capability of genetic mechanisms for encoding visual cortical architecture and mathematically dissect the pinwheel configuration under measurement noise as well as in different geometries. First, I theoretically explore possible roles of genetic mechanisms in visual cortical development that were previously excluded from theoretical research, mostly because the information capacity of the genome appeared too small to contain a blueprint for wiring up the cortex. For the first time, I provide a biologically plausible scheme for quantitatively encoding functional visual cortical architecture by genetic information that circumvents the alleged information bottleneck. Key ingredients for this mechanism are active transport and trans-neuronal signaling as well as joined dynamics of morphogens and connectome. This theory provides predictions for experimental tests and thus may help to clarify the relative importance of genes and environments on complex human traits. Second, I disentangle the link between orientation domain ensembles and the species-invariant pinwheel statistics of the common design. This examination highlights informative measures of pinwheel configurations for model benchmarking. Third, I mathematically investigate the susceptibility of the pinwheel configuration to measurement noise. The results give rise to an extrapolation method of pinwheel densities to the zero noise limit and provide an approximated analytical expression for confidence regions of pinwheel centers. Thus, the work facilitates high-precision measurements and enhances benchmarking for devising more accurate models of visual cortical development. Finally, I shed light on genuine three-dimensional properties of functional visual cortical architectures. I devise maximum entropy models of three-dimensional functional visual cortical architectures in different geometries. This theory enables the examination of possible evolutionary transitions between different functional architectures for which intermediate organizations might still exist.
CHiP: A Configurable Hybrid Parallel Covering Array Constructor

We present a configurable, hybrid, and parallel covering array constructor, called CHiP. CHiP is parallel in that it utilizes vast amount of parallelism provided by graphics processing units (GPUs). CHiP is hybrid in that it bundles the bests of two construction approaches for computing covering arrays; a metaheuristic search-based approach for efficiently covering a large portion of the required combinations and a constraint satisfaction-based approach for effectively covering the remaining hard-to-cover-by-chance combinations. CHiP is configurable in that a trade-off between covering array sizes and construction times can be made. We have conducted a series of experiments, in which we compared the efficiency and effectiveness of CHiP to those of a number of existing constructors by using both full factorial designs and well-known benchmarks. In these experiments, we report new upper bounds on covering array sizes, demonstrating the effectiveness of CHiP, and the first results for a higher coverage strength, demonstrating the scalability of CHiP.
Fruit production forecasting by neuro-fuzzy techniques

Neuro-fuzzy techniques are finding a practical application in many fields such as in model identification and forecasting of linear and non-linear systems. This paper presents a neuro-fuzzy model for forecasting the fruit production of some agriculture products (olives, lemons, oranges, cherries and pistachios). The model utilizes a time series of yearly data. The fruit forecasting is based on Adaptive Neural Fuzzy Inference System (ANFIS). ANFIS uses a combination of the least-squares method and the backprobagation gradient descent method to estimate the optimal food forecast parameters for each year. The results are compared to those of an Autoregressive (AR) model and an Autoregressive Moving Average model (ARMA).
The Effects of Financing Risk on the Value of Firm and Profitability: Evidence from Nigerian Commercial Banks

This study is designed to address the critical issues of financing risk in the banking industry. The data from sixteen selected commercial banks? audited financial reports from 2009 to 2015 was used, making up to 112 observations. The panel data approach was used in the study for the analytical models. The market-based and accounting-based measure was used to proxy firm performance while financing risk was proxied by the Short-term debt, Long-term debt and Total debt ratio. The controlled variables used in this study included bank size and the GDP growth rate. Based on the random effect analysis in the models, the TDE ratio and GDP had a negative significant effect on firm value, suggesting that improvement in the TDE and GDP would increase firm value. The LTD ratio had a positive significant effect on firm value. The STD, LTD and TDE all impacted negatively on the banks? return on assets. This suggested that a decrease in STD, LTD and TDE would lead to an increase in banks? return on asset. The STD, LTD and GDP had a negative and significant effect on the banks? net interest margin. The firm size had no impact on either the firm value or profitability measure used in the study. It was observed that the GDP played an important role in the performance of the commercial banks in the study. Hence, this paper suggests that further study can explore the effects of firm characteristics on firm value by exploring non-financial firms and/or a cross-country study.
The changing nature of News Reporting, Story Development and Editing

With advancements in technology in this age of globalization and digital media, the nature of News Reporting, Story Development and Editing across the United States have been constantly evolving. Through a systematic secondary research, the current research would examine various factors which led to the evolutionary journey of News Reporting, when there was simply a man behind a desk delivering news to the age of journalism and reporting with the help of robots. This journey has been truly inspiring and has developed a relationship with the target audience in terms of expecting something new each time they see various podcasts and live reporting from journalists across the globe. The results depict similar advancements in the niche area of Story Development as we have entered the age of digital storytelling. This includes various skillsets such as research, resource-selection, script-writing, voice-overs, technical skill development, collaboration, creative expression and presentation, all of which would be discussed in detail. Similar advancements were observed in the journey of document editing as well as film-making and editing procedures from the traditional years to the digital age. Key words: News Reporting, Story Development, Story-telling, Editing.
Mobile Wireless Sensor Networks: An Overview

Mobile wireless sensor networks (MWSNs) have emerged and shifted the focus from the typical static wireless sensor networks to networks with mobile sensor nodes that are capable to sense the various types of events. Also, they can change their position fre- quently in a specific sensing area. The applications of the MWSNs can be widely divided into time-driven, event-driven, on-demand and tracking based applications. Mobile sen- sor node architecture, residual energy utilization, mobility, topology, scalability, localization, data collection routing, Quality of Service (QoS), etc., are the key factors to design an energy efficient MWSNs for some specific purpose. This chapter deals with an overview of the MWSNs and a few significant phenomena to design an energy efficient MWSNs to the large-scale environment.
Knowledge Productivity in the 2020s: Time for a New E/RA A Research Study on the Impact of Organizational Design and Employee Engagement on the Knowledge Productivity of Service Firms

The subject of this study is the interdisciplinary perspective approach to knowledge productivity within the service industry. Relationships between organizational design and employee engagement are studied between constructs of both organizational and psychological theory and their effects on knowledge productivity, whereby an attempt is made to bridge both disciplines. Amongst other things the level of responsible autonomy (RA) is related to employee engagement (E) and organizational knowledge productivity. It is argued that an organizational design and the “misfit” of the employee’s preferences with the perceived organizational design characteristics will have a strong negative influence on their work engagement- and knowledge productivity levels.
Color image super-resolution algorithm based on SVM classified learning

Due to the limitations of image capture device and imaging environments in traditional imaging process, high-resolution (HR) images are difficult to be obtained. The method of digital image processing can be used in image super-resolution with one or an image sequence in original conditions to reconstruct HR images which over the range of imaging system. Traditional learning-based super-resolution algorithm need to run through the sample library with a high computing complexity, and a high recognition rate in the scene with small shifts. This dissertation is mainly about color image SR and parallel implementation of the SR algorithm. An algorithm based on SVM classified learning is proposed in this paper.
Documentation of Scholarship of Teaching and Learning Trends at National Council on Family Relations Annual Conferences, 2006-2015

Research indicates that while the Scholarship of Teaching and Learning (SoTL) continues to advance its integration into universities throughout the United States (Huber & Hutchings, 2005; O’Meara & Rice, 2005 as cited in Gurung, Ansburg, Alexander, Lawrence, & Johnson, 2005), some fields have been more receptive than others. Studies have explored faculty members’ perceived support of SoTL at departmental and institutional levels (Gurung et al., 2008; Reinke, Muraco, & Maurer, 2016). However, inquiry on SoTL penetration into traditional disciplinary conferences remains scarce. The paucity of research exploring inclusion or exclusion of SoTL sessions at professional meetings warrants further attention. This investigation examined historical changes in the presence of SoTL topics at National Council on Family Relations (NCFR) annual conferences from 2006-2015. Through content analyses of conference programs, researchers explored ratios of SoTL to non-SoTL sessions and gender ratios of presenters (McKinney & Chick, 2010). Institutional Carnegie classification of presenters of SoTL sessions was also recorded. Discussion addresses implications of findings for growth of SoTL in family science and the interdisciplinary SoTL community.
Building a Modern Financial Model of Company Management

During some years, many original and interesting papers devoted to the issue of property management were published. However, there is an acute shortage of works devoted to the system of accessing models for cost-effectiveness analysis. The most researchers adapt a certain method to assess the market value, for example, discounting of cash flows to real management process, or choose of a key performance indicator of the enterprise from the position of cost management. According to the author, when building a financial management model, it is necessary not to look for a single indicator of efficiency, but develop a system of criteria to assess such efficiency. The more capacious and general these criteria are, the less dependent the management system will be on the subjectivity of the decision-maker. The model should limit the ability of management to manipulate basic accounting values. The model should possess a normative or standard development model of the company, which would be able to ensure an increase in its cost growth. Within the framework of this model, it proves the pivotal importance to adjust the budgets of the company in varying market environment. Budget planning enables to solve the tasks of current management because even in the case of budget execution, the company can reduce its cost. The budget itself does not give answers to questions about whether the company’s level of profitability, the growth of its revenues, etc., is sufficient or not. At the same time, the model of making decisions based on the criterion of cost can give a response to the shareholders on these issues when the budget is approved in any
1 How to Develop a Great Digital Strategy

As leading technology companies embrace biometrics, artificial intelligence (AI), drones, and other exciting digital technologies, senior business executives at many other companies feel pressured to do the same. But if they are to maximize the value from investment in new technologies, business leaders first must make sure that their companies have a great digital strategy.
Performance Gain in HIVE through Query Optimization using Index Joins

Index joins range unit pivotal for proficiency and quality once technique questions over colossal data. HIVE may be a cluster balanced immense data administration motor that is good for data examination applications and for OLAP for phenomenally "specific" inquiries whose yield sizes region unit little division from the contributing data, there the beast compel experiences poor execution because of repetitive circle I/O operations or end in starts of additional guide operations. Here all through this paper a shot is made and propose file joins procedure to rush up the inquiry strategy and incorporate it in Hive by mapping our vogue to the unique change stream to assess the execution, we've a slant to give and measure check inquiries on datasets created abuse TPC-H benchmark. Our outcomes show vital execution increase over moderately tremendous data sets and/or uncommonly specific questions having a two-way are a piece of and one be a piece of condition.
DNA insecticides as an emerging tool for plant protection and food security strategies

A large number of plant diseases and damages are caused by insects and insect vectors of plant pathogens, leading to the serious threats facing plant protection and food security. The access to safe and nutritiously high-quality food is essential for human growth and development. This translates to a well-developed society with systematically organized efforts for maintenance and increased food production or supply to meet the continuous growing demand. The effects of environmental, biological, chemical, political and socioeconomic factors have all contributed to the present nature of food dynamics, its availability, supply and security. Hence, the development of safe bio-based substances should be prioritized for precise and effective use in plant protection strategies. This review examines the sequential results of the insecticidal potentials of unmodified short single-stranded DNA fragments used as DNA insecticides, and emerging tool for safe plant protection strategy.
Future occupational safety and health research needs and priorities in the member states of the European Union

During the period 1998-1999 data collection was carried out in the EU Member States in order to collect and publish up-to-date information on future occupational safety and health research needs and priorities to improve collaboration and to guide occupational safety and health research over the next decade. National reports included the viewpoints of social partners and of all relevant research institutions. Psychosocial issues (stress at work), ergonomics (manual handling/work postures) and chemical risk factors (toxic/dangerous) emerged overall as the top priority areas for future research. In the area of safety, the most prominence was given to human factors risks, in the area of physical agents to the risk of noise. Issues relating to small and medium-sized enterprises were also ranked highly both under risk management and as a group requiring attention. Groups such as ageing workers and people with reduced working ability are of particular interest to Member States. Teleworking emerged as important areas for future research.
Driving Audit Committee Disclosure: Legislation Versus Best Practice

Abstract Stakeholders have no alternative than to rely on the credibility and effectiveness of governance and oversight structures within organizations, to protect their interest. This study investigates whether the expectation for expanded disclosure on audit committees has been adopted as part of organizational culture. The evolution of audit committee guidance in the King reports and prominent global reports were analyzed and compared to legislation governing all sectors within South Africa. A document analysis in the form of a structured content analysis was conducted to determine adherence to King guidance by South African organizations. Optimal scaling was applied to determine dimensions of disclosure, with respect to audit committee best practice. Finally, the level of adherence to legislation versus adherence to best practices is gauged within each dimension. Results support organizations to have generally increased disclosure on audit committees’ composition and role. The study adds to the body of knowledge on voluntary disclosure of audit committee best practice, to be considered by policy makers and management, on what may strengthen the credibility and effectiveness of audit committee oversight as perceived by the stakeholder. The result also presents a foundation for further research within this area.
Are Automatic Metrics Robust and Reliable in Specic Machine Translation Tasks?

We present a comparison of automatic metrics against human evaluations of translation quality in several scenarios which were unexplored up to now. Our experimentation was conducted on translation hypotheses that were problematic for the automatic metrics, as the results greatly diverged from one metric to another. We also compared three different translation technologies. Our evaluation shows that in most cases, the metrics capture the human criteria. However, we face failures of the automatic metrics when applied to some domains and systems. Interestingly, we find that automatic metrics applied to the neural machine translation hypotheses provide the most reliable results. Finally, we provide some advice when dealing with these problematic domains.
Detailed mathematical and simulation model of a synchronous generator

Synchronous generator theory has been known since the beginning of its use, but the modelling and analysis of synchronous generators is still very existent in the present-day. Modern digital computers enable development of detailed simulation models, thus individual power system elements, including synchronous generators, are represented by the highest degree order models in power system simulation software packages. In this paper, first, a detailed mathematical model of a synchronous generator is described. Then, a simulation model of a synchronous generator developed based on the presented mathematical model. Finally, a transient stability after a short-circuit is simulated using real generator parameters.
Why do we overspecify in dialogue? An experiment on L2 lexical acquisition

We describe an experimental study designed to evaluate the effect of overspecification on L2 language acquisition. Our hypothesis is that overspecification helps establish alignment, which facilitates the acquisition of lexemes. Our results show that subjects receiving overspecified references during the exercise phase are slower at resolving the exercises, but have better lexeme acquisition rates. This supports the claim that overspecification is a useful mechanism for communication.