Submitted by Joel de Lima Pereira Castro Junior (joelpcastro@uol.com.br) on 2016-09-28T14:43:10Z No. of bitstreams: 1 Alessandra Bellas.pdf: 2237445 bytes, checksum: 0fcd4bfdc85441595e5f2cc7ee5ef123 (MD5) / Approved for entry into archive by Biblioteca de Administração e Ciências Contábeis (bac@ndc.uff.br) on 2016-09-30T16:04:48Z (GMT) No. of bitstreams: 1 Alessandra Bellas.pdf: 2237445 bytes, checksum: 0fcd4bfdc85441595e5f2cc7ee5ef123 (MD5) / Made available in DSpace on 2016-09-30T16:04:48Z (GMT). No. of bitstreams: 1 Alessandra Bellas.pdf: 2237445 bytes, checksum: 0fcd4bfdc85441595e5f2cc7ee5ef123 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Esta dissertação objetiva verificar as relações existentes entre as percepções de justiça organizacional, especificamente da justiça distributiva, justiça processual e justiça interacional, e as estratégias defensivas utilizadas por funcionários de Instituições bancárias públicas e privadas nos Municípios de Niterói e do Rio de Janeiro. Quanto aos procedimentos metodológicos, a pesquisa teve uma abordagem quanti-qualitativa, de cunho explicativo, descritivo e exploratório, caracterizado pela survey. Os métodos de amostragem foram não probabilísticos, sendo utilizados a amostragem por julgamento e amostragem “bola de neve”. A amostra foi composta por 127 trabalhadores de instituições bancárias públicas e privadas, localizadas nos Municípios de Niterói e Rio de Janeiro, que responderam ao formulário de pesquisa com a escala de percepção de justiça organizacional (EPJO), e destes, sete sujeitos, selecionados a partir da análise de cluster, participantes da entrevista semiestruturada que abordou sobre a justiça organizacional e as estratégias defensivas. Os dados do formulário foram tratados por um conjunto de procedimentos estatísticos, contendo estatística descritiva e análise multivariada de dados com as técnicas de análise fatorial, regressão linear múltipla e análise de cluster. As respostas das entrevistas foram interpretadas com base na Análise de Conteúdo, cuja técnica específica foi a análise categorial. Os principais resultados foram: a percepção de uma justiça organizacional mediana (3,07) nas instituições bancárias, com diferença estatisticamente significativa para a dimensão da justiça procedimental entre público e privado; a confirmação do modelo tridimensional para a justiça organizacional; a validação da justiça organizacional como um fator de segunda ordem; a validação das dimensões da justiça distributiva, justiça procedimental e justiça interacional como escalas múltiplas; o modelo de regressão da justiça organizacional, formado pelas variáveis “gênero”, “tipo de controle”, “tempo de trabalho na empresa” e “escolaridade”, com uma preditibilidade de 4,6% da variância total; a estrutura de parcionamento apontando que um maior número de funcionários das instituições bancárias possui uma percepção menos positiva da justiça organizacional, em detrimento do quantitativo que a percebe como mais justa; as estratégias defensivas, como por exemplo, adequação profissional para bater metas, ligação para os amigos; desligamento do trabalho e transferência de área; e as categorias das estratégias defensivas mais frequentes na comparação entre público e privado, sendo, no setor privado o uso da defesa explorada, fundamentada na negação e no serviço público, a defesa protetora com base na racionalização. Por fim, pode-se afirmar que a maior problemática das organizações bancárias está relacionada à dimensão distributiva, seguida da procedimental e da interacional, e que há indícios de uma relação passível de interpretação entre as dimensões da justiça organizacional e os tipos de estratégias defensivas e suas categorias utilizadas pelos funcionários de instituições bancárias públicas e privadas. / This dissertation aims at verifying the relationships between organizational justice perceptions, specifically of distributive justice, procedural justice and interactional justice, and the defensive strategies used by employees of public and private banking institutions in the cities of Niterói and Rio de Janeiro. The methodology used has a quantitative and qualitative approach, is explanatory, descriptive and exploratory, characterized by the survey. The sampling methods were not probabilistic, trial and "snowball" sampling were used. The sample consisted of 127 employees of public and private bank institutions, located in the cities of Niteroi and Rio de Janeiro, who answered the survey form with the organizational justice perception scale (EPJO), and from these, seven subjects were selected using cluster analysis to participate in a semi-structured interview about organizational justice and defense strategies. Form data was treated by a set of statistical procedures, containing descriptive statistics and multivariate data analysis using factor analysis, multiple and linear regression and cluster analysis. The answers from the interviews were interpreted using Content analysis, more specifically the Categorical analysis technique. The main results were: the perception of a median organizational justice (3.07) in banking institutions, with a statistically significant difference in the extent of procedural fairness between public and private; the confirmation of the three-dimensional model for organizational justice; the validation of organizational justice as a factor of second order; validation of the dimensions of distributive justice, procedural justice, and interactional justice as multiple scales; the regression model of organizational justice, formed by the variables "gender", "type of control", "working time in the company" and "education" with a predictability of 4.6% of the total variance; the partitioning structure in the cluster analysis pointing to a greater number of employees of banking institutions having a less positive perception of organizational justice, at the expense of the majority, who realize it as fairer; defensive strategies, such as professional suiting to achieve goals, calling a friend; disconnection from work and area transfer; and the most common defensive strategies categories when comparing public and private institutions, being, the use of explored defense based on denial and the protective defense based on rationalization, the most common strategies at private and public institutions respectively. Finally, it can be said that the biggest problem of banking organizations is related to the distributive dimension, followed by procedural and interactional, and there is evidence of a relationship, open to interpretation, between the dimensions of organizational justice and the types of defensive strategies and their categories used by the staff of public and private banking institutions.

Orientadores: Leo Pini Magalhães, Soraia Raupp Musse / Acompanha 1 CD-ROM / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-14T12:44:21Z (GMT). No. of bitstreams: 1 Bicho_AlessandrodeLima_D.pdf: 3153035 bytes, checksum: 02699fbfe11ede429a8d387c957cfb0d (MD5) Previous issue date: 2009 / Resumo: Este trabalho apresenta um método para simulação de multidões baseado no algoritmo de colonização do espaço. Este algoritmo foi originalmente proposto para modelar padrões de nervuras em folhas vegetais e de ramificações em árvores. A técnica baseia-se na competição por espaço entre nervuras ou ramificações durante o crescimento vegetal. Adaptado à simulação de multidões, o algoritmo de colonização do espaço visa simular a competição por espaço durante o movimento dos pedestres. Vários comportamentos observados em multidões reais, tais como evitar colisões, variar a velocidade de deslocamento do pedestre em função da densidade populacional e formar vias (lanes) de pedestres, nas quais o pedestre seguirá aquele imediatamente a sua frente, cuja direção e sentido são similares, são propriedades do algoritmo. O modelo de simulação de multidões proposto também caracteriza-se pela simplicidade de implementação, robustez e eficência computacional, permitindo, de acordo com o ambiente de simulação adotado, o controle interativo da multidão simulada. / Abstract: This work presents a method for crowd simulation based on the biologically-motivated space colonization algorithm. This algorithm was originally introduced to model leaf venation patterns and the branching architecture of trees. It operates by simulating the competition for space between growing veins or branches. Adapted to crowd modeling, the space colonization algorithm focuses on the competition for space among moving agents. Several behaviors observed in real crowds, including collision avoidance, relationship of crowd density and speed of agents, and the formation of lanes in which people follow each other, are properties of the algorithm. The proposed crowd modeling method is simple to implement, robust, computationally efficient, and suited to the interactive control of simulated crowds. / Doutorado / Engenharia de Computação / Doutor em Engenharia Elétrica

Mobile devices and online services allow capturing an unprecedented amount of information about human behavior. In this dissertation, I use these new types of data to understand how the built environment affects social life and businesses in cities. In Chapter 1, I provide the first causal evidence that the provision of urban parks promotes opportunities for racially and ethnically diverse encounters. Utilizing a novel dataset featuring individual GPS tracking data for more than 60 thousand Twitter users in the New York metro area, I introduce a measure of racial diversity that captures one's level of exposure to diverse others in places visited daily. My empirical strategy relies on using the variation in the timing of park construction works across the city (that temporarily limit the capacity of said parks) to identify the impact of the effectively accessible parkland area on the individual exposure to racial diversity. My results show that for White and Black/African American residents additional 10 acres of parks within a 5 km radius from home increase individual chances of encounters with the members of other groups by 1 p.p. The effect is sizable: for reference, transitioning from the current state to the random mixing scenario would require a 9 p.p increase in diversity for an average Black or African American individual and a 3.5 p.p increase for an average White person. I also provide evidence to suggest that park accessibility affects the diversity of White and Black residents differently: for parks located closer to home, the effect appears to be more pronounced for Whites than Blacks. Chapter 2, written jointly with Dmitry Sedov, investigates the role of sports facilities in generating consumption spillovers for the local businesses. The construction of sports facilities, which can cost hundreds of millions of dollars, is often subsidized by public sources. In many cases, subsidies are allocated on the premise that sports venues benefit the local economy by bringing new customers to nearby businesses. We pin down the size and the spatial distribution of such spillovers using daily foot traffic data from mobile phones covering major sports league facilities and the surrounding commercial establishments. By employing the fixed effects and the IV estimation strategies, we show that the spillover benefits are heterogeneous across sports and business sectors. We find that 100 baseball stadium visits generate roughly 29 visits to nearby food & accommodation businesses and about 6 visits to local retail establishments. While the estimates for football stadiums are comparable, basketball & hockey arenas do not appear to generate significant spillovers for the surrounding businesses. Using our spillover estimates, we also compute an upper bound on the additional local spending induced by each sample arena. The median value of the additional spending turns out to be substantially smaller than the corresponding median subsidy to sports facilities in our sample. In Chapter 3, I examine the contribution of parks to social ties between neighborhoods in New York City. Although the role of public spaces in facilitating social interactions in cities has been widely discussed by social scientists and urban design scholars, data sets from online social networks present unexplored opportunities to quantify this link on a larger scale. I use data on friendship links between Facebook users across New York City zip codes to show that two neighborhoods with a higher density of green spaces between them are more likely to have stronger social ties. In particular, when controlling for demographic differences and zip-code level fixed effects, I find that a 1 p.p. increase in the percentage of land allocated to parks between two given zip codes is associated with a 1.2% higher chance of online social connection between their residents. Comparing the effects of park density for different types of parks, I further document that the presence of community parks, flagship parks, and playgrounds are all significant predictors of higher social connectedness between zip codes. Notably, the largest estimated effect is for playgrounds, indicating a 33% higher probability of connection per 1 p.p. increase in density.

No description available.

Évaluer un comportement humain c’est évaluer tous les marqueurs traduisant ce comportement (gestes, paroles interactions, etc.). L’observation par un humain de certains marqueurs tels que les expressions faciales, la prosodie ou encore la linguistique, nécessite une formation spécialisée. Pour faciliter l’évaluation du comportement, des échelles indiquant les observations à mener et les conclusions à faire sont employées. Ainsi, automatiser l’évaluation du comportement revient à automatiser l’analyse d’un environnement par le biais de plusieurs capteurs, puis analyser les signaux obtenus afin d’en extraire les marqueurs permettant la déduction du comportement observé. Suite à la variabilité des observations de l’humain lors d’analyses trop spécifiques, de plus en plus d’études emploient ces systèmes automatiques d’observation et d’évaluation du comportement. L’objectif est d’assister l’analyse et l’évaluation humaine en exploitant des systèmes automatiques capables d’extraire des informations difficilement observables pour l’humain. En conséquence, la collaboration entre l’humain et les systèmes informatiques permet d’analyser plus d’éléments du comportement de manière fiable et objective. Cette thèse propose une approche de l’analyse du comportement s’appuyant sur la collaboration entre l’humain et un système automatique. Nous avons mis en place une plate-forme électronique et informatique composée d’un robot mobile et d’un système ambiant afin d’évaluer le comportement humain. Cette plate-forme se définie comme étant : — Modulaire à l’ajout ou le retrait de capteurs : L’ajout et la suppression de capteurs est faisable sans qu’un système ne soit impacté autrement que sur ses performances à reconnaître précisément les comportements; — Accessible à la lecture des données enregistrées : L’utilisation d’ontologies, en tant que base de données sémantiques et logiques, rend la plate-forme utilisable et accessible aux personnes non familiarisées aux systèmes informatiques complexes; — Robuste aux ambiguïtés : Chaque système de la plate-forme (ambiant ou robot) est indépendant et a sa propre représentation de l’environnement. Cependant, ils collaborent entre eux pour répondre aux incohérences ou aux manques d’informations durant l’accomplissement d’une tâche. A partir de la plate-forme présentée précédemment, nous analysons et mesurons la qualité de l’interaction entre un patient et un soignant lors d’une prise de sang réalisée en conditions habituelles. Pour cela, nous utilisons deux méthodes de renseignement des échelles : par un observateur présent lors du soin et par une étude de l’enregistrement vidéo réalisé durant le soin par la plate-forme. Nous émettons l’hypothèse que la présence d’un système automatique d’aide au diagnostic lors de l’analyse des vidéos enregistrées limite la complexité de l’évaluation du comportement et améliore l’objectivité de l’analyse. / To evaluate a human behavior is equivalent to evaluate all the markers translating this behavior (gestures, lyrics interactions, etc.). The observation by a human of certain markers such as facial expressions, prosody or linguistics, requires specialized training. To facilitate the assessment of behavior, scales indicating the observations to be made and the conclusions to be made are used. Thus, automating the evaluation of the behavior amounts to automate the analysis of an environment by means of several sensors, then analyzing the signals obtained in order to extract the markers allowing the deduction of the observed behavior. Due to the variability of human observations in overly specific analyzes, more and more studies are using thes automatic observation and behavioral evaluation systems. The objective is to assist human analysis and evaluation by exploiting automatic systems capable of extracting information that is difficult to observe for humans. As a result, the collaboration between the human and the computer systems makes it possible to analyze more elements of the behavior in a reliable and objective way. This thesis proposes an approach of behavior analysis based on the collaboration between humans and an automatic system. We set up an electronic and computer platform consisting of a mobile robot and an ambient system to evaluate human behavior. This platform is defined as: — Modular to the addition or removal of sensors: The addition and removal of sensors is feasible without a system is impacted otherwise than its performance to accurately recognize behaviors; — Accessible to Reading Recorded Data: The use of ontologies, as a semantic and logical database, makes the platform usable and accessible to people unfamiliar With complex computer systems; — Robust to ambiguities: every platform system (ambient or robot) is independent and has its own representation of the environment. However, they collaborate With each Other to respond to inconsistencies or lack of information during the performance of a task.

In recent years there has emerged a new trend focused on the body image in the Western countries. Our society is concerned with people's physical appearance and ideal body image. As consequence of this trend, two businesses emerge: fitness centers and plastic surgery clinics. Traditionally the consumers' expenditure in these services and goods has been considered a luxury especially during the economic slowdown. However, in the recent times, (at end of 2000s both service sectors are showing an increasing trend in terms of activity and business size). Thus, customers have seen the practice of fitness and plastic surgery procedures as a necessity rather than a luxury. The two kinds of products considered: fitness practice and plastic surgery procedures are of different nature; however they share several commonalities from the analysis point of view. In particular, referred to the fitness practice business, this involves a parallel increase of related economic sectors such as sports clothing, energy drinks and sports equipment. Related to the Spanish population who exercise regularly, this has evolved from 27% in 2005 to 35% in 2010, which shows a significant increase of the population sportive practices. A significant example of this trend is the fact that in 2009 the 74% of the Spanish public gyms had a fitness room for bodybuilding. On contrast, related to the market of plastic surgery measured by volume of activity, Spain occupies the level 13th position of the international ranking, which is headed by USA. The plastic surgery market embraces low invasive (non surgical) and high invasive (surgical) plastic surgery procedures; between both types, more than 300,000 thousands procedures are performed annually mainly by women in Spain. / Al-Kasadi, MSS. (2014). Modeling the propagation of the consumption of two emergent businesses: Fitness Practice and Plastic Surgery [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39795 / TESIS

Context-based Reasoning (CxBR) and Contextual Graphs (CxGs) involve the modeling of human behavior in autonomous and decision-support situations in which optimal human decision-making is of utmost importance. Both formalisms use the notion of contexts to allow the implementation of intelligent agents equipped with a context sensitive knowledge base. However, CxBR uses a set of discrete contexts, implying that models created using CxBR operate within one context at a given time interval. CxGs use a continuous context-based representation for a given problem-solving scenario for decision-support processes. Both formalisms use contexts dynamically by continuously changing between necessary contexts as needed in appropriate instances. This thesis identifies a synergy between these two formalisms by looking into their similarities and differences. It became clear during the research that each paradigm was designed with a very specific family of problems in mind. Thus, CXBR best implements models of autonomous agents in environment, while CxGs is best implemented in a decision support setting that requires the development of decision-making procedures. Cross applications were implemented on each and the results are discussed.

Autonomous robots interacting with humans in a social setting must consider the social-cultural environment when pursuing their objectives. Thus the social robot must perceive and understand the social cultural environment in order to be able to explain and predict the actions of its human interaction partners. This dissertation contributes to the emerging field of human-robot interaction for social robots in the following ways: 1. We used the social calculus technique based on culture sanctioned social metrics (CSSMs) to quantify, analyze and predict the behavior of the robot, human soldiers and the public perception in the Market Patrol peacekeeping scenario. 2. We validated the results of the Market Patrol scenario by comparing the predicted values with the judgment of a large group of human observers cognizant of the modeled culture. 3. We modeled the movement of a socially aware mobile robot in a dense crowds, using the concept of a micro-conflict to represent the challenge of giving or not giving way to pedestrians. 4. We developed an approach for the robot behavior in micro-conflicts based on the psychological observation that human opponents will use a consistent strategy. For this, the mobile robot classifies the opponent strategy reflected by the personality and social status of the person and chooses an appropriate counter-strategy that takes into account the urgency of the robots' mission. 5. We developed an alternative approach for the resolution of micro-conflicts based on the imitation of the behavior of the human agent. This approach aims to make the behavior of an autonomous robot closely resemble that of a remotely operated one.

<p>  </p> <p>Human error is one of the most prominent challenges facing cybersecurity today. Attackers manipulate people's natural inclination to make mistakes using social engineering tactics to exploit psychological vulnerabilities, gain trust, and access sensitive information. Trust plays a critical role in human interaction, both in the physical and digital realms, making it an attractive target for attackers. However, cultural backgrounds, which reflect individual and societal beliefs and values, are often overlooked in cybersecurity risk assessments, despite significantly influencing human behavior. This study was conducted to investigate the relationship between trust and cybersecurity risks across diverse cultural groups. The study's findings could provide valuable insights into addressing and preventing human-related vulnerabilities by enhancing overall cybersecurity measures and examining cross-cultural differences in human behavior and their impact on cybersecurity risks. As human factors in cybersecurity become increasingly crucial, this study was performed to understand the differences in risky cybersecurity behaviors among various cultural groups and investigate the impact of different perceptions of trust on engaging in risky behaviors. The outcome of this research provides insights into the critical role cultural backgrounds play in shaping human behavior in the context of cybersecurity. The results of this study may have significant implications for enhancing overall cybersecurity measures by identifying and addressing human-related vulnerabilities that may be unique to specific cultural groups.</p>

Introducing automated vehicles in to traffic withhuman drivers, human behavior prediction is essential to obtainoperation safety. In this study, a human behavior estimationmodel has been developed. The estimations are based on aHidden Markov Model (HMM) using observations to determinethe driving style of surrounding vehicles. The model is trainedusing two different methods: Baum Welch training and Viterbitraining to improve the performance. Both training methods areevaluated by looking at time complexity and convergence. Themodel is implemented with and without training and tested fordifferent driving styles. Results show that training is essentialfor accurate human behavior prediction. Viterbi training is fasterbut more noise sensitive compared to Baum Welch training. Also,Viterbi training produces good results if training data reflects oncurrently observed driver, which is not always the case. BaumWelch training is more robust in such situations. Lastly, BaumWelch training is recommended to obtain operation safety whenintroducing automated vehicles into traffic. / N ̈ar automatiserade fordon introduceras itrafiken och beh ̈over interagera med m ̈anskliga f ̈orare ̈ar det vik-tigt att kunna f ̈orutsp ̊a m ̈anskligt beteende. Detta f ̈or att kunnaerh ̊alla en s ̈akrare trafiksituation. I denna studie har en modellsom estimerar m ̈anskligt beteende utvecklats. Estimeringarna ̈ar baserade p ̊a en Hidden Markov Model d ̈ar observationeranv ̈ands f ̈or att best ̈amma k ̈orstil hos omgivande fordon itrafiken. Modellen tr ̈anas med tv ̊a olika metoder: Baum Welchtr ̈aning och Viterbi tr ̈aning f ̈or att f ̈orb ̈attra modellens prestanda.Tr ̈aningsmetoderna utv ̈arderas sedan genom att analysera derastidskomplexitet och konvergens. Modellen ̈ar implementerad medoch utan tr ̈aning och testad f ̈or olika k ̈orstilar. Erh ̊allna resultatvisar att tr ̈aning ̈ar viktigt f ̈or att kunna f ̈orutsp ̊a m ̈anskligtbeteende korrekt. Viterbi tr ̈aning ̈ar snabbare men mer k ̈ansligf ̈or brus i j ̈amf ̈orelse med Baum Welch tr ̈aning. Viterbi tr ̈aningger ̈aven en bra estimering i de fall d ̊a observerad tr ̈aningsdataavspeglar f ̈orarens k ̈orstil, vilket inte alltid ̈ar fallet. BaumWelch tr ̈aning ̈ar mer robust i s ̊adana situationer. Slutligenrekommenderas en estimeringsmodell implementerad med BaumWelch tr ̈aning f ̈or att erh ̊alla en s ̈aker k ̈orning d ̊a automatiseradefordon introduceras i trafiken / Kandidatexjobb i elektroteknik 2020, KTH, Stockholm