The field of wireless communications has been experiencing tremendous growth with the ever-increasing dependence on wireless services. In the operation of a communication network, the network coverage and node placement are of profound importance. The network performance metrics can be modeled as nonlinear functions of inter-node distances. Therefore, a geometric abstraction of the distance between wireless devices becomes a prerequisite for accurate system modeling and analysis. A geometrical probability approach is presented in this dissertation to characterize the probabilistic distance properties, for analyzing the location-critical performance metrics through various spatial distance distributions. Ideally, the research in geometrical probability shall give results for the distance distributions 1) over elementary geometries such as a straight line, squares and rectangles, and 2) over complex geometries such as rhombuses and hexagons. Both 1) and 2) are the representative topological shapes for communication networks. The current probability and statistics literature has explicit results for 1), whereas the results for 2) are not in existence. In particular, the absence of the distance distributions for rhombuses and hexagons has posed challenges towards the analytical modeling of location-critical performance metrics in complex geometries. This dissertation is dedicated to the application of existing results in 1) elementary geometries to the networking area, and the development of a new approach to deriving the distance distributions for complex geometries in 2), bridging the gap between the geometrical probability and networking research. The contribution of this dissertation is twofold. First, the one-dimensional Poisson point process in 1) is applied to the message dissemination in vehicular ad-hoc networks, where the network geometry is constrained by highways and city blocks. Second, a new approach is developed to derive the closed-form distributions of inter-node distances associated with rhombuses and hexagons in 2), which are obtained for the first time in the literature. Analytical models can be constructed for characterizing the location-critical network performance metrics, such as connectivity, nearest/farthest neighbor, transmission power, and path loss in wireless networks. Through both analytical and simulation results, this dissertation demonstrates that this geometrical probability approach provides accurate information essential to successful network protocol and system design, and goes beyond the approximations or Monte Carlo simulations by gracefully eliminating the empirical errors. / Graduate

Fixed and mobile communication service providers (CSPs) are facing fierce competition among each other. In a globally saturated market, the primary di↵erentiator between CSPs has become customer satisfaction, typically measured by the Net Promoter Score (NPS) for a subscriber. The NPS is the answer to the question: ”How likely is it that you will recommend this product/company to a friend or colleague?” The responses range from 0 representing not at all likely to 10 representing extremely likely. In this thesis, we aim to identify which, if any, network performance metrics contribute to subscriber satisfaction. In particular, we investigate the relationship between the NPS survey results and 11 network performance metrics of the respondents of a major mobile operator in South Africa. We identify the most influential performance metrics by fitting both linear and non-linear statistical models to the February 2018 survey dataset and test the models on the June 2018 dataset. We find that metrics such as Call Drop Rate, Call Setup Failure Rate, Call Duration and Server Setup Latency are consistently selected as significant features in models of NPS prediction. Nevertheless we find that all the tested statistical and machine learning models, whether linear or non-linear, are poor predictors of NPS scores in a month, when only the network performance metrics in the same month are provided. This suggests that either NPS is driven primarily by other factors (such as customer service interactions at branches and contact centres) or are determined by historical network performance over multiple months.

Intrusion systems have been the subject of considerable research during the past 33 years, since the original work of Anderson. Much has been published attempting to improve their performance using advanced data processing techniques including neural nets, statistical pattern recognition and genetic algorithms. Whilst some significant improvements have been achieved they are often the result of assumptions that are difficult to justify and comparing performance between different research groups is difficult. The thesis develops a new approach to defining performance focussed on comparing intrusion systems and technologies. A new taxonomy is proposed in which the type of output and the data scale over which an intrusion system operates is used for classification. The inconsistencies and inadequacies of existing definitions of detection are examined and five new intrusion levels are proposed from analogy with other detection-based technologies. These levels are known as detection, recognition, identification, confirmation and prosecution, each representing an increase in the information output from, and functionality of, the intrusion system. These levels are contrasted over four physical data scales, from application/host through to enterprise networks, introducing and developing the concept of a footprint as a pictorial representation of the scope of an intrusion system. An intrusion is now defined as “an activity that leads to the violation of the security policy of a computer system”. Five different intrusion technologies are illustrated using the footprint with current challenges also shown to stimulate further research. Integrity in the presence of mixed trust data streams at the highest intrusion level is identified as particularly challenging. Two metrics new to intrusion systems are defined to quantify performance and further aid comparison. Sensitivity is introduced to define basic detectability of an attack in terms of a single parameter, rather than the usual four currently in use. Selectivity is used to describe the ability of an intrusion system to discriminate between attack types. These metrics are quantified experimentally for network intrusion using the DARPA 1999 dataset and SNORT. Only nine of the 58 attack types present were detected with sensitivities in excess of 12dB indicating that detection performance of the attack types present in this dataset remains a challenge. The measured selectivity was also poor indicting that only three of the attack types could be confidently distinguished. The highest value of selectivity was 3.52, significantly lower than the theoretical limit of 5.83 for the evaluated system. Options for improving selectivity and sensitivity through additional measurements are examined.

Os rumos atuais da competição e da tecnologia justificam a crescente utilização de indicadores para a gestão dos recursos produtivos nas organizações industriais. Nesta linha de pensamento, o presente trabalho discorre sobre as principais abordagens relacionadas com gestão competitiva, construção de indicadores e métodos de custeio, disponíveis na literatura. Com base no modelo gerencial do Prof. Nigel Slack, para agregar vantagem competitiva na manufatura, é desenvolvido um sistema de indicadores integrados para a gestão do custeio e das atividades de manutenção. O modelo de gestão é validado por intermédio de um estudo de caso real e os resultados obtidos demonstram a eficácia do sistema de indicadores no monitoramento das atividades de manutenção nas empresas industriais. / The current trend in terms of world-wide competition and technological skills justify the increasing utilization of constant up-to-date information and decision-making data in manufacturing organizations. Accordingly, this work discusses the major contributions related to a world-class management, performance metrics and costing methods. Based on Nigel Slack’s management model proposed to increase competitiveness, an inter-related performance metrics system is developed, aiming to reduce maintenance cost and to improve the overall maintenance activities management. The management techniques proposed in this research is validated by its application in a real manufacturing company, selected for a case-study. This research shows that the data collected allows statistical analysis and helps a plant management team to get important conclusions about the effectiveness of the performance metrics proposed for maintenance management.

Recommendation systems have become extremely common in recent years due to the ubiquity of information across various applications. Online entertainment (e.g., Netflix), E-commerce (e.g., Amazon, Ebay) and publishing services such as Google News are all examples of services which use recommender systems. Recommendation systems are rapidly evolving in these years, but these methods have fallen short in coping with several emerging trends such as likes or votes on reviews. In this work we have proposed a new method based on collaborative filtering by considering other users' feedback on each review. To validate our approach we have used Yelp data set with more than 335,000 product and service category ratings and 70,817 real users. We present our results using comparative analysis with other well-known recommendation systems for particular categories of users and items. / Graduate / 0984 / 0800 / yheshmat@uvic.ca

Os indicadores de desempenho têm papel fundamental na gestão das organizações, pois mostram aos decisores a situação da organização e como ela se encontra em relação a seus objetivos. Entre os sistemas de indicadores de desempenho utilizado nas organizações, têm tido destaque a conjugação de métricas financeiras e não financeiras, baseada na crença de que a melhora nos resultados não financeiros irá ocasionar a melhora nos índices financeiros. Entretanto, não há uma metodologia consagrada para testar se esses relacionamentos (relações de causa-e-efeito) existem na realidade. O objetivo desse trabalho foi propor e validar parcialmente uma metodologia para testar e quantificar as relações causais entre indicadores de desempenho. A seqüência de passos foi definida a partir da literatura através da implementação de ferramentas do Desdobramento da Função Qualidade, Gerenciamento pelas Diretrizes, Pensamento Sistêmico e Ferramenta para Seleção de Planos de Ação. O método escolhido para sua validação parcial foi o estudo de caso. A unidade de análise foi uma organização que já utiliza métricas financeiras e não financeiras e possui base histórica de dados. A pesquisa utilizou como fontes de evidência a observação participante e entrevista estruturada. Para a análise dos dados foram utilizadas técnicas estatísticas e representação escrita. Os resultados permitem concluir que a metodologia consegue quantificar as relações causais entre métricas de desempenho. A aplicação também gerou grande aprendizado organizacional. A principal contribuição desse trabalho é o modelo conceitual parcialmente validado o qual pode ser utilizado para transformar o sistema de indicadores de desempenho em fonte de informações para a tomada de decisão através da quantificação das relações de causa-e-efeito. / Performance metrics have a fundamental role in organizations, because they show to decision makers the situation of the organization in relation to its objectives. Most of the metrics systems used have financial and non-financial indicators, based on the belief that if a non-financial performance is increased, it will cause the same behavior in financial results. On the other hand, there is not a consecrated methodology to test if these relationships (causal relations) exist in the real world. The objective of this paper is to propose and partially validate a methodology to test and quantify the causal relations among performance metrics. A sequence of steps was defined from literature research, using tools from Quality Function Deployment, Policy Deployment, System Dynamics and Tool for Action Planning Selection. The research method chosen was case study. The research unit was an organization that already uses financial and non-financial metrics and has historic data of it. As font of evidences, were used participant observation and structure interviews. Data analysis was made with statistical techniques and written representation. From the results, it can be concluded using the methodology it’s possible to quantify the causal relations between performance metrics. The application of this methodology also contributed the organizations learning. The mainly contribution of this paper is the partially validated conceptual methodology, that can be used to make the performance metric system a information source to decision making, trough the quantification of causal relations.

Os indicadores de desempenho têm papel fundamental na gestão das organizações, pois mostram aos decisores a situação da organização e como ela se encontra em relação a seus objetivos. Entre os sistemas de indicadores de desempenho utilizado nas organizações, têm tido destaque a conjugação de métricas financeiras e não financeiras, baseada na crença de que a melhora nos resultados não financeiros irá ocasionar a melhora nos índices financeiros. Entretanto, não há uma metodologia consagrada para testar se esses relacionamentos (relações de causa-e-efeito) existem na realidade. O objetivo desse trabalho foi propor e validar parcialmente uma metodologia para testar e quantificar as relações causais entre indicadores de desempenho. A seqüência de passos foi definida a partir da literatura através da implementação de ferramentas do Desdobramento da Função Qualidade, Gerenciamento pelas Diretrizes, Pensamento Sistêmico e Ferramenta para Seleção de Planos de Ação. O método escolhido para sua validação parcial foi o estudo de caso. A unidade de análise foi uma organização que já utiliza métricas financeiras e não financeiras e possui base histórica de dados. A pesquisa utilizou como fontes de evidência a observação participante e entrevista estruturada. Para a análise dos dados foram utilizadas técnicas estatísticas e representação escrita. Os resultados permitem concluir que a metodologia consegue quantificar as relações causais entre métricas de desempenho. A aplicação também gerou grande aprendizado organizacional. A principal contribuição desse trabalho é o modelo conceitual parcialmente validado o qual pode ser utilizado para transformar o sistema de indicadores de desempenho em fonte de informações para a tomada de decisão através da quantificação das relações de causa-e-efeito. / Performance metrics have a fundamental role in organizations, because they show to decision makers the situation of the organization in relation to its objectives. Most of the metrics systems used have financial and non-financial indicators, based on the belief that if a non-financial performance is increased, it will cause the same behavior in financial results. On the other hand, there is not a consecrated methodology to test if these relationships (causal relations) exist in the real world. The objective of this paper is to propose and partially validate a methodology to test and quantify the causal relations among performance metrics. A sequence of steps was defined from literature research, using tools from Quality Function Deployment, Policy Deployment, System Dynamics and Tool for Action Planning Selection. The research method chosen was case study. The research unit was an organization that already uses financial and non-financial metrics and has historic data of it. As font of evidences, were used participant observation and structure interviews. Data analysis was made with statistical techniques and written representation. From the results, it can be concluded using the methodology it’s possible to quantify the causal relations between performance metrics. The application of this methodology also contributed the organizations learning. The mainly contribution of this paper is the partially validated conceptual methodology, that can be used to make the performance metric system a information source to decision making, trough the quantification of causal relations.

Os rumos atuais da competição e da tecnologia justificam a crescente utilização de indicadores para a gestão dos recursos produtivos nas organizações industriais. Nesta linha de pensamento, o presente trabalho discorre sobre as principais abordagens relacionadas com gestão competitiva, construção de indicadores e métodos de custeio, disponíveis na literatura. Com base no modelo gerencial do Prof. Nigel Slack, para agregar vantagem competitiva na manufatura, é desenvolvido um sistema de indicadores integrados para a gestão do custeio e das atividades de manutenção. O modelo de gestão é validado por intermédio de um estudo de caso real e os resultados obtidos demonstram a eficácia do sistema de indicadores no monitoramento das atividades de manutenção nas empresas industriais. / The current trend in terms of world-wide competition and technological skills justify the increasing utilization of constant up-to-date information and decision-making data in manufacturing organizations. Accordingly, this work discusses the major contributions related to a world-class management, performance metrics and costing methods. Based on Nigel Slack’s management model proposed to increase competitiveness, an inter-related performance metrics system is developed, aiming to reduce maintenance cost and to improve the overall maintenance activities management. The management techniques proposed in this research is validated by its application in a real manufacturing company, selected for a case-study. This research shows that the data collected allows statistical analysis and helps a plant management team to get important conclusions about the effectiveness of the performance metrics proposed for maintenance management.

Os indicadores de desempenho têm papel fundamental na gestão das organizações, pois mostram aos decisores a situação da organização e como ela se encontra em relação a seus objetivos. Entre os sistemas de indicadores de desempenho utilizado nas organizações, têm tido destaque a conjugação de métricas financeiras e não financeiras, baseada na crença de que a melhora nos resultados não financeiros irá ocasionar a melhora nos índices financeiros. Entretanto, não há uma metodologia consagrada para testar se esses relacionamentos (relações de causa-e-efeito) existem na realidade. O objetivo desse trabalho foi propor e validar parcialmente uma metodologia para testar e quantificar as relações causais entre indicadores de desempenho. A seqüência de passos foi definida a partir da literatura através da implementação de ferramentas do Desdobramento da Função Qualidade, Gerenciamento pelas Diretrizes, Pensamento Sistêmico e Ferramenta para Seleção de Planos de Ação. O método escolhido para sua validação parcial foi o estudo de caso. A unidade de análise foi uma organização que já utiliza métricas financeiras e não financeiras e possui base histórica de dados. A pesquisa utilizou como fontes de evidência a observação participante e entrevista estruturada. Para a análise dos dados foram utilizadas técnicas estatísticas e representação escrita. Os resultados permitem concluir que a metodologia consegue quantificar as relações causais entre métricas de desempenho. A aplicação também gerou grande aprendizado organizacional. A principal contribuição desse trabalho é o modelo conceitual parcialmente validado o qual pode ser utilizado para transformar o sistema de indicadores de desempenho em fonte de informações para a tomada de decisão através da quantificação das relações de causa-e-efeito. / Performance metrics have a fundamental role in organizations, because they show to decision makers the situation of the organization in relation to its objectives. Most of the metrics systems used have financial and non-financial indicators, based on the belief that if a non-financial performance is increased, it will cause the same behavior in financial results. On the other hand, there is not a consecrated methodology to test if these relationships (causal relations) exist in the real world. The objective of this paper is to propose and partially validate a methodology to test and quantify the causal relations among performance metrics. A sequence of steps was defined from literature research, using tools from Quality Function Deployment, Policy Deployment, System Dynamics and Tool for Action Planning Selection. The research method chosen was case study. The research unit was an organization that already uses financial and non-financial metrics and has historic data of it. As font of evidences, were used participant observation and structure interviews. Data analysis was made with statistical techniques and written representation. From the results, it can be concluded using the methodology it’s possible to quantify the causal relations between performance metrics. The application of this methodology also contributed the organizations learning. The mainly contribution of this paper is the partially validated conceptual methodology, that can be used to make the performance metric system a information source to decision making, trough the quantification of causal relations.

Approved for public release; distribution in unlimited. / In the management of the U.S. Naval inventory, data quality is of critical importance. Errors in major inventory databases contribute to increased operational costs, reduced revenue, and loss of confidence in the reliability of the supply system. Maintaining error-free databases is not a realistic objective. Data-quality efforts must be prioritized to ensure that limited resources are allocated to achieve the maximum benefit. This thesis proposes a methodology to assist the Naval Inventory Control Point in the prioritization of its data-quality efforts. By linking data errors to Naval inventory performance metrics, statistical testing is used to identify errors that have the greatest adverse impact on inventory operations. By focusing remediation efforts on errors identified in this manner, the Navy can best use its limited resources devoted to improvement of data quality. Two inventory performance metrics are considered: Supply Material Availability (SMA), an established metric in Naval inventory management; and Backorder Persistence Metric (BPM), which is developed in the thesis. Backorder persistence measures the duration of time that the ratio of backorders to quarterly demand exceeds a threshold value. Both metrics can be used together to target remediation on reducing shortage costs and improving inventory system performance. / Lieutenant Commander, Supply Corps, United States Navy