Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.

Aplicación web de gestión financiera personal desarrollada con MEAN.JS

En este trabajo de fin de grado se llevará a cabo la elaboración de una aplicación web de gestión de gastos personales desde sus inicios, hasta su completo funcionamiento. Estas aplicaciones poseen un crecimiento emergente en el mercado, lo cual implica que la competencia entre ellas es muy elevada. Por ello el diseño de la aplicación que se va a desarrollar en este trabajo ha sido delicadamente cuidado. Se trata de un proceso minucioso el cual aportará a cada una de las partes de las que va a constar la aplicación características únicas que se plasmaran en funcionalidades para el usuario, como son: añadir sus propios gastos e ingresos mensuales, confeccionar gráficos de sus principales gastos, obtención de consejos de una fuente externa, etc… Estas funcionalidades de carácter único junto con otras más generalistas, como son el diseño gráfico en una amplia gama de colores, harán su manejo más fácil e intuitivo. Hay que destacar que para optimizar su uso, la aplicación tendrá la característica de ser responsive, es decir, será capaz de modificar su interfaz según el tamaño de la pantalla del dispositivo desde el que se acceda. Para su desarrollo, se va a utilizar una de las tecnologías más novedosas del mercado y siendo una de las más revolucionarias del momento, MEAN.JS. Con esta innovadora tecnología se creará la aplicación de gestión económica de gastos personales. Gracias al carácter innovador de aplicar esta tecnología novedosa, los retos que plantea este proyecto son muy variados, desde cómo estructurar las carpetas del proyecto y toda la parte de backend hasta como realizar el diseño de la parte de frontend. Además una vez finalizado su desarrollo y puesta en marcha se analizaran posibles mejoras para poder perfeccionarla en su totalidad. ABSTRACT In this final degree project will take out the development of a web application from its inception, until its full performance management. These applications have an emerging market growth, implying that competition between them is very high. Therefore the design of the application that will be developed in this work has been delicately care. It's a painstaking process which will provide each of the parties which will contain the application unique features that were translated into functionality for the user, such as: add their own expenses and monthly income, make graphs of your major expenses, obtaining advice from an external source, etc... These features of unique character together with other more general, such as graphic design in a wide range of colors, will make more easy and intuitive handling. It should be noted that to optimize its use, the application will have the characteristic of being responsive, will be able to modify your interface according to the size of the screen of the device from which are accessed. For its development, it is to use one of the newest technologies on the market and being one of the most revolutionary moment, MEAN. JS. The economic management of personal expenses application will be created with this innovative technology. Thanks to the innovative nature of applying this new technology, the challenges posed by this project are varied, from how to structure the folders of the project and all the backend part up to how to perform the part of frontend design. In addition once finished its development and commissioning possible improvements will analyze to be able to perfect it in its entirety.

Mujeres empresarias en el uso de la web 2.0: discursos de un preludio

Este trabajo presenta los principales resultados de una investigación cuya finalidad es conocer la adopción de las redes sociales on-line en las pymes dirigidas por mujeres. Se parte de la base de que el uso de redes, como elemento estratégico de comunicación, se encuentra todavía en una fase incipiente de desarrollo, lejos aún de ser una práctica consolidada. Nuestro interés en este trabajo es conocer la predisposición y motivaciones de las empresarias hacia el uso estas redes, así como las utilidades y dificultades a las que han de enfrentarse. Nos interesa visibilizar el cambio actitudinal y competencial que las empresarias están imprimiendo en sus empresas dentro del marco competitivo en el que se encuentran. En definitiva, nos interesa estudiar la percepción que tienen las empresarias sobre el uso de las redes sociales online en la medida en que están insertas, como una herramienta más de gestión empresarial. Nos situamos ante un nuevo ámbito de conocimiento sobre el que apenas existen referencias bibliográficas ni se ha realizado apenas investigación; de ahí que la investigación tenga una finalidad fundamentalmente exploratoria y de carácter cualitativo. Para la obtención de la información se realizaron catorce entrevistas semi-estructuradas entre empresarias andaluzas de distintos sectores de actividad. Entre los principales resultados encontramos que algo menos de la mitad de ellas las utilizan, o están implantadas en sus empresas, como herramientas de comunicación. El resto, y relacionado con el tamaño de sus negocios, las utilizan como una prolongación del uso personal en el que se iniciaron.

Evidências de validade da versão brasileira do Exercise Motivation Inventory-2 em contexto de academia e personal training

Este estudo teve como objetivos verificar a validade fatorial e a validade interna da versão brasileira do Exercise Motivation Inventory-2 (EMI-2) e comparar os principais motivos para prática de exercício tendo em conta os contextos de academia e personal training. Um total de 588 praticantes de exercício da cidade de Pelotas/RS/Brasil (405 de academia e 183 de personal training) preencheram o EMI-2, o qual é constituído por 51 itens, agrupados em 14 motivos (fatores) para prática de exercício físico. A validade fatorial do EMI-2 foi testada através da realização de análises fatoriais confirmatórias e a validade interna através do alfa de Cronbach. Para a verificar o efeito do contexto nos motivos foi utilizada a MANOVA e calculado o tamanho do efeito. Os resultados obtidos dão suporte à estrutura original do EMI-2 com 14 fatores, nesta amostra. Verificou-se um efeito multivariado significativo do contexto sobre os motivos de prática [Wilks’ λ = 0.912, F (14, 573.000) = 3.9, p < 0.001, η² = 0.088]. Os motivos de “Prazer”, “Força e resistência”, “Desafio”, “Socialização”, “Competição” e “Reconhecimento Social” foram significativamente superiores no contexto de academia e os motivos de “Agilidade” e “Prevenção de Doenças” foram significativamente superiores no contexto de personal training.

Guidelines for permitting overloads. Part I: effect of overloaded vehicles on the Indiana highway network. Final report.

Indiana Department of Transportation, Indianapolis

The Relationship between Adolescent Social Network Structure and Perceptions of School Climate

Thesis (Ph.D.)--University of Washington, 2016-06

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

Spatially orthogonal chemical functionalization of a hierarchical pore network for catalytic cascade reactions

The chemical functionality within porous architectures dictates their performance as heterogeneous catalysts; however, synthetic routes to control the spatial distribution of individual functions within porous solids are limited. Here we report the fabrication of spatially orthogonal bifunctional porous catalysts, through the stepwise template removal and chemical functionalization of an interconnected silica framework. Selective removal of polystyrene nanosphere templates from a lyotropic liquid crystal-templated silica sol–gel matrix, followed by extraction of the liquid crystal template, affords a hierarchical macroporous–mesoporous architecture. Decoupling of the individual template extractions allows independent functionalization of macropore and mesopore networks on the basis of chemical and/or size specificity. Spatial compartmentalization of, and directed molecular transport between, chemical functionalities affords control over the reaction sequence in catalytic cascades; herein illustrated by the Pd/Pt-catalysed oxidation of cinnamyl alcohol to cinnamic acid. We anticipate that our methodology will prompt further design of multifunctional materials comprising spatially compartmentalized functions.

The n-tuple network: coping with sub-optimality

The subject of this thesis is the n-tuple net.work (RAMnet). The major advantage of RAMnets is their speed and the simplicity with which they can be implemented in parallel hardware. On the other hand, this method is not a universal approximator and the training procedure does not involve the minimisation of a cost function. Hence RAMnets are potentially sub-optimal. It is important to understand the source of this sub-optimality and to develop the analytical tools that allow us to quantify the generalisation cost of using this model for any given data. We view RAMnets as classifiers and function approximators and try to determine how critical their lack of' universality and optimality is. In order to understand better the inherent. restrictions of the model, we review RAMnets showing their relationship to a number of well established general models such as: Associative Memories, Kamerva's Sparse Distributed Memory, Radial Basis Functions, General Regression Networks and Bayesian Classifiers. We then benchmark binary RAMnet. model against 23 other algorithms using real-world data from the StatLog Project. This large scale experimental study indicates that RAMnets are often capable of delivering results which are competitive with those obtained by more sophisticated, computationally expensive rnodels. The Frequency Weighted version is also benchmarked and shown to perform worse than the binary RAMnet for large values of the tuple size n. We demonstrate that the main issues in the Frequency Weighted RAMnets is adequate probability estimation and propose Good-Turing estimates in place of the more commonly used :Maximum Likelihood estimates. Having established the viability of the method numerically, we focus on providillg an analytical framework that allows us to quantify the generalisation cost of RAMnets for a given datasetL. For the classification network we provide a semi-quantitative argument which is based on the notion of Tuple distance. It gives a good indication of whether the network will fail for the given data. A rigorous Bayesian framework with Gaussian process prior assumptions is given for the regression n-tuple net. We show how to calculate the generalisation cost of this net and verify the results numerically for one dimensional noisy interpolation problems. We conclude that the n-tuple method of classification based on memorisation of random features can be a powerful alternative to slower cost driven models. The speed of the method is at the expense of its optimality. RAMnets will fail for certain datasets but the cases when they do so are relatively easy to determine with the analytical tools we provide.

BMI not WHR modulates BOLD fMRI responses in a sub-cortical reward network when participants judge the attractiveness of human female bodies

In perceptual terms, the human body is a complex 3d shape which has to be interpreted by the observer to judge its attractiveness. Both body mass and shape have been suggested as strong predictors of female attractiveness. Normally body mass and shape co-vary, and it is difficult to differentiate their separate effects. A recent study suggested that altering body mass does not modulate activity in the reward mechanisms of the brain, but shape does. However, using computer generated female body-shaped greyscale images, based on a Principal Component Analysis of female bodies, we were able to construct images which covary with real female body mass (indexed with BMI) and not with body shape (indexed with WHR), and vice versa. Twelve observers (6 male and 6 female) rated these images for attractiveness during an fMRI study. The attractiveness ratings were correlated with changes in BMI and not WHR. Our primary fMRI results demonstrated that in addition to activation in higher visual areas (such as the extrastriate body area), changing BMI also modulated activity in the caudate nucleus, and other parts of the brain reward system. This shows that BMI, not WHR, modulates reward mechanisms in the brain and we infer that this may have important implications for judgements of ideal body size in eating disordered individuals.

Social network theory and the sales manager role:engineering the right relationship flows

Sales leadership research has typically taken a leader-focused approach, investigating key questions from a top-down perspective. Yet considerable research outside sales has advocated a view of leadership that takes into account the fact that employees look beyond a single designated individual for leadership. In particular, the social networks of leaders have been a popular topic of investigation in the management literature, although coverage in the sales literature remains rare. The present paper conceptualizes the sales leadership role as one in which the leader must manage a network of simultaneous relationships; several types of sales manager relationships, such as the sales-manager-to-top-manager and the sales-manager-to-sales manager relationships, have received limited attention in the sales literature to date. Taking an approach based on social network theory, we develop a conceptualization of the sales manager as a "network engineer," who must manage multiple relationships, and the flows between them. Drawing from this model, we propose a detailed agenda for future sales research. © 2012 PSE National Educational Foundation. All rights reserved.

Energy efficient radio access architectures for green radio:large versus small cell size deployment

In this paper new architectural approaches that improve the energy efficiency of a cellular radio access network (RAN) are investigated. The aim of the paper is to characterize both the energy consumption ratio (ECR) and the energy consumption gain (ECG) of a cellular RAN when the cell size is reduced for a given user density and service area. The paper affirms that reducing the cell size reduces the cell ECR as desired while increasing the capacity density but the overall RAN energy consumption remains unchanged. In order to trade the increase in capacity density with RAN energy consumption, without degrading the cell capacity provision, a sleep mode is introduced. In sleep mode, cells without active users are powered-off, thereby saving energy. By combining a sleep mode with a small-cell deployment architecture, the paper shows that the ECG can be increased by the factor n = (R/R) while the cell ECR continues to decrease with decreasing cell size.

Small business owners’ success criteria, a values approach to personal differences

This study of 150 Dutch small business owners, identified through business/ network directories, investigated relationships between owners’ understanding of success and their personal values. Business owners ranked 10 success criteria. Per- sonal satisfaction, profitability, and satisfied stakeholders ranked highest. Multidi- mensional scaling techniques revealed two dimensions underlying the rank order of success criteria: person-oriented (personal satisfaction versus business growth) and business-oriented (profitability versus contributing back to society). Furthermore, business growth, profitability, and innovativeness were guided by self-enhancing value orientations (power and achievement). Softer success criteria, such as having satisfied stakeholders and a good work–life balance, were guided by self-transcendent value orientations (benevolence and universalism).

The Cascade Orthogonal Neural Network

In the paper new non-conventional growing neural network is proposed. It coincides with the Cascade- Correlation Learning Architecture structurally, but uses ortho-neurons as basic structure units, which can be adjusted using linear tuning procedures. As compared with conventional approximating neural networks proposed approach allows significantly to reduce time required for weight coefficients adjustment and the training dataset size.

Оптимизация на учителския състав в училище

Silvia Baeva - In the Ministry of Education and Science’s system it has been talked about optimization of the school network; this optimization can be carried out in different directions and be supported by laws. An important aspect in the optimization of the school network is to reduce costs and increase overall efficiency in each school. We will formulate this aspect as a problem of the multicriteria decisions making and by appropriate numbers of methods and criteria it can be transformed to the problem of unicriterion optimization. This problem is separated into two stages: 1-th stage – determining the minimum number of classes in a school under certain statutory provisions for the size of each of them; 2-th stage – the appointment of a minimum number of teachers and achievement of maximal effectiveness of teaching and acquiring of knowledge and skills by students according to certain statutory provisions for teachers’ annual norms of subjects and number of hours in a particular subject area and the salaries of teachers. The achievement of maximum overall efficiency is a priority in all schools.