Em um ambiente altamente competitivo, onde a disputa por clientes rentáveis torna-se cada vez mais acirrada, a crescente importância das ações de marketing como atividades estratégicas ganham destaque. Este papel traz consigo cobranças, deveres e responsabilidades a serem cumpridas em um ambiente corporativo. Torna-se natural que a alta gestão das companhias exija avaliações de desempenho pautadas pela mensuração dos resultados através de métricas bem definidas e estabelecidas. Mais que indicadores de resultados, as corporações necessitam justificar seus investimentos com maior responsabilidade de forma a garantir transparência junto aos Stakeholders, assim como proporcionar uma melhor remuneração aos Shareholders. Os princípios de Governança Corporativa, Accountability e Compliance tornam-se essenciais nas corporações que exercem as melhores práticas de mercado e utilizam métricas de desempenho como meio de prestação de contas. Àquelas que possuem orientação para mercado necessitam de métricas adequadas e específicas que meçam a satisfação do cliente visando assegurar-lhes uma entrega de valor superior frente aos competidores, pois clientes são ativos de marketing significativos e geram valor para o acionista. Esta dissertação tem por objetivo estudar métricas de desempenho, que são utilizadas regularmente pelos gestores de marketing para análise de resultados, alocação de recursos e Accountability. Para que o objetivo ora proposto fosse alcançado, o estudo foi organizado em duas etapas, onde a primeira aborda o levantamento do referencial teórico, que visou organizar o conhecimento das métricas de desempenho proposto em literatura, sobre a evolução do pensamento de marketing e sua influência no desenvolvimento e utilização de métricas para aferir resultados, alocação de recursos, valor para o Acionista, Accountability em marketing e seus objetivos, orientação para mercado e Métricas de desempenho e aplicações. A segunda etapa abrange a pesquisa empírica, que proporcionou a identificação das métricas mais difundidas e utilizadas pelas empresas farmacêuticas de medicamentos isentos de prescrição no Brasil e seus gestores de marketing, para aferir resultados, subsidiar alocação de recursos e Accountability em Marketing, bem como àquelas que são consideradas mais importantes por estes profissionais. Este estudo foi desenvolvido por meio de uma abordagem quantitativa, através de levantamento, utilizando um questionário estruturado (survey), via internet, o qual foi aplicado em gestores de marketing de empresas farmacêuticas de medicamentos isentos de prescrição. A análise dos dados obtidos por meio da pesquisa empírica foi descrita de forma detalhada, assim como os achados da utilização das métricas em acordo com perfil da empresa, seja por tamanho ou origem. Dentre os principais resultados encontrados e por meio da análise das evidencias apresentadas, as métricas mais utilizadas são as métricas de margens e lucros e financeiras, quando analisamos empresas multinacionais, e, as empresas nacionais, embora também façam uso das métricas de margens e lucros, utilizam com mais intensidade em seu lugar as métricas de mapeamento, segmentação e posicionamento de mercado, associadas às financeiras. / In a highly competitive environment where competition for profitable customers becomes increasingly fierce, the growing importance of marketing actions as strategic activities is highlighted. This importance carries duties, responsibilities, and requests to be met in a corporate environment. It becomes natural that top management of companies requires performance evaluations based on well-defined and established measurements of results. More than indicators of results, corporations need to justify their investments with greater responsibility to ensure transparency with stakeholders, as well as provide better remuneration to Shareholders. Principles of Corporate Governance, Accountability and Compliance become essential in corporations that exert the best market practices and use performance metrics as a means of accountability. Those that have market orientation require appropriate and specific metrics that measure customer satisfaction in order to ensure the delivery of superior value compared to competitors, because customers are marketing assets and generate significant shareholder value. This thesis aims to study performance metrics, which are regularly used by marketing managers to analyze results, resource allocation and Accountability. To reach the proposed objective, this study was organized in two parts: the first deals with the survey of theoretical framework, which aimed at organizing knowledge of the performance metrics proposed in the literature, the evolution of marketing ideas and their influence in the development and use of metrics to measure results, resource allocation, value for Shareholders, Accountability and marketing objectives, market orientation and performance metrics and applications. The second part covers the empirical research, which yielded the identification of the most widespread marketing metrics used by non-prescription drug pharmaceutical companies in Brazil and their managers to measure outcomes, support resource allocation and Accountability in Marketing, as well as those that are considered most important by these professionals. This study was conducted via a quantitative approach, through a structured questionnaire (survey), via the Internet, where the survey instrument was proposed to marketing managers of non-prescription drug pharmaceutical companies. The analysis of data obtained through empirical research has been described in detail, as well as the findings of the use of metrics in accordance with company profile, either by size or origin. Among the main findings and analyzing the evidence presented, the most frequently used metrics are financial and margins & profits when we are analyzing multinational companies. When we analyze the domestic companies, although it also makes use of margins & profits metrics, they used more intensively in its place mapping, segmentation and market positioning metrics, associated with financial metrics.

Maintaining the pH of a fluid or a solution at a specific value is a concern in many industrial processes, wastewater management, and food and pharmaceutical production. Given the importance of controlling pH in many processes, the objective of this thesis is to study and compare the effectiveness of some controller algorithms to control the pH of a process. In this study, the performance of three controller algorithms, namely PID, fractional PID and LA controllers, is evaluated for the control of a simple neutralization process using conventional controller performance metrics. Performance metrics used are the response time, the Integral of the Time weighted Absolute Error (ITAE), the Integral of the Squared Error (ISE), and the Integral of the Squares of the changes (ΔU) in the manipulated variable (ISDU). The three controllers were therefore tuned to minimize one or a combination of the controller performance metrics. Results show that PID, fractional PID and LA controllers implemented and tested in this research are all worthy controllers for maintaining pH of the neutralization process. Simulation results show that the three controllers can be used with confidence to cope with the high nonlinearity of a pH neutralization process provided that the process is properly designed. The relative small gain in performance obtained with the fractional PID controller, compared to a linear PID controller, suggests that it is not worth resorting to a fractional PID controller given its complexity and higher computation effort. Results show that PID and LA controllers are easy to implement with short response time and low ITAE and ISDU performance metrics.

Gestational diabetes Mellitus (GDM), a condition involving abnormal levels of glucose in the blood plasma has seen a rapid surge amongst the gestating mothers belonging to different regions and ethnicities around the world. Cur- rent method of screening and diagnosing GDM is restricted to Oral Glucose Tolerance Test (OGTT). With the advent of machine learning algorithms, the healthcare has seen a surge of machine learning methods for disease diag- nosis which are increasingly being employed in a clinical setup. Yet in the area of GDM, there has not been wide spread utilization of these algorithms to generate multi-parametric diagnostic models to aid the clinicians for the aforementioned condition diagnosis.In literature, there is an evident scarcity of application of machine learn- ing algorithms for the GDM diagnosis. It has been limited to the proposed use of some very simple algorithms like logistic regression. Hence, we have attempted to address this research gap by employing a wide-array of machine learning algorithms, known to be effective for binary classification, for GDM classification early on amongst gestating mother. This can aid the clinicians for early diagnosis of GDM and will offer chances to mitigate the adverse out- comes related to GDM among the gestating mother and their progeny.We set up an empirical study to look into the performance of different ma- chine learning algorithms used specifically for the task of GDM classification. These algorithms were trained on a set of chosen predictor variables by the ex- perts. Then compared the results with the existing machine learning methods in the literature for GDM classification based on a set of performance metrics. Our model couldn’t outperform the already proposed machine learning mod- els for GDM classification. We could attribute it to our chosen set of predictor variable and the under reporting of various performance metrics like precision in the existing literature leading to a lack of informed comparison. / Graviditetsdiabetes Mellitus (GDM), ett tillstånd som involverar onormala ni- våer av glukos i blodplasma har haft en snabb kraftig ökning bland de drab- bade mammorna som tillhör olika regioner och etniciteter runt om i världen. Den nuvarande metoden för screening och diagnos av GDM är begränsad till Oralt glukosetoleranstest (OGTT). Med tillkomsten av maskininlärningsalgo- ritmer har hälso- och sjukvården sett en ökning av maskininlärningsmetoder för sjukdomsdiagnos som alltmer används i en klinisk installation. Ändå inom GDM-området har det inte använts stor spridning av dessa algoritmer för att generera multiparametriska diagnostiska modeller för att hjälpa klinikerna för ovannämnda tillståndsdiagnos.I litteraturen finns det en uppenbar brist på tillämpning av maskininlär- ningsalgoritmer för GDM-diagnosen. Det har begränsats till den föreslagna användningen av några mycket enkla algoritmer som logistisk regression. Där- för har vi försökt att ta itu med detta forskningsgap genom att använda ett brett spektrum av maskininlärningsalgoritmer, kända för att vara effektiva för binär klassificering, för GDM-klassificering tidigt bland gesterande mamma. Det- ta kan hjälpa klinikerna för tidig diagnos av GDM och kommer att erbjuda chanser att mildra de negativa utfallen relaterade till GDM bland de dödande mamma och deras avkommor.Vi inrättade en empirisk studie för att undersöka prestandan för olika ma- skininlärningsalgoritmer som används specifikt för uppgiften att klassificera GDM. Dessa algoritmer tränades på en uppsättning valda prediktorvariabler av experterna. Jämfört sedan resultaten med de befintliga maskininlärnings- metoderna i litteraturen för GDM-klassificering baserat på en uppsättning pre- standametriker. Vår modell kunde inte överträffa de redan föreslagna maskininlärningsmodellerna för GDM-klassificering. Vi kunde tillskriva den valda uppsättningen prediktorvariabler och underrapportering av olika prestanda- metriker som precision i befintlig litteratur vilket leder till brist på informerad jämförelse.

The performance of financial institutions is significantly influenced by the actions of loan officers. The process by which lending decisions are made is therefore of critical interest to management, shareholders, and regulators alike. Indeed, the drain on bank capital that has often accompanied credit quality problems in the past has encouraged the search for new approaches towards the management of lending and related activities. / This thesis seeks to examine whether existing governance and incentive techniques found in banks are sufficiently comprehensive in guiding loan decision-making. In the context of lending to the corporate sector, the study investigates the endogenous and exogenous influences surrounding the lending role, and assesses the implications for how loan officers are monitored, evaluated, and motivated to act in a financial institution’s best interests. / By first developing an expanded model that conceptualizes the loan offer function, and then grounding this framework within a business cycle context, the study demonstrates the potential for governance and reward systems, that are constant through time, to have variable outcomes/effects. Support for this hypothesis is provided based on publicly available financial market information and other material gathered from private sources. A proposal is then advanced for the development of a management information system that identifies changes in credit standards being applied, thereby enabling banks to benchmark and influence loan officer performance in the context of cyclically changing attitudes to risk and the effects on negotiating power.

The performance of financial institutions is significantly influenced by the actions of loan officers. The process by which lending decisions are made is therefore of critical interest to management, shareholders, and regulators alike. Indeed, the drain on bank capital that has often accompanied credit quality problems in the past has encouraged the search for new approaches towards the management of lending and related activities. / This thesis seeks to examine whether existing governance and incentive techniques found in banks are sufficiently comprehensive in guiding loan decision-making. In the context of lending to the corporate sector, the study investigates the endogenous and exogenous influences surrounding the lending role, and assesses the implications for how loan officers are monitored, evaluated, and motivated to act in a financial institution’s best interests. / By first developing an expanded model that conceptualizes the loan offer function, and then grounding this framework within a business cycle context, the study demonstrates the potential for governance and reward systems, that are constant through time, to have variable outcomes/effects. Support for this hypothesis is provided based on publicly available financial market information and other material gathered from private sources. A proposal is then advanced for the development of a management information system that identifies changes in credit standards being applied, thereby enabling banks to benchmark and influence loan officer performance in the context of cyclically changing attitudes to risk and the effects on negotiating power.

In recent years the service-oriented design paradigm has enabled applications to be built by incorporating third party services. With the increasing popularity of this new paradigm, many companies and organizations have started to adopt this technology, which has resulted in an increase of the number and variety of third party providers. With the vast improvement of global networking infrastructure, a large number of providers offer their services for worldwide clients. As a result, clients are often presented with a number of providers that offer services with the same or similar functionalities, but differ in terms of non-functional attributes (or Quality of Service – QoS), such as performance. In this environment, the role of provider recommendation has become more important - in assisting clients in choosing the provider that meets their QoS requirement. / In this thesis we focus on provider recommendation based on one of the most important QoS attributes – performance. Specifically, we investigate client-perceived performance, which is the application-level performance measured at the client-side every time the client invokes the service. This performance metric has the advantage of accurately representing client experience, compared to the widely used server-side metrics in the current frameworks (e.g. Service Level Agreement or SLA in Web Services context). As a result, provider recommendation based on this metric will be favourable from the client’s point of view. / In this thesis we address two key research challenges related to provider recommendation based on client-perceived performance - performance assessment and performance prediction. We begin by identifying heterogeneity factors that affect client-perceived performance among clients in a global Internet environment. We then perform extensive real-world experiments to evaluate the significance of each factor to the client-perceived performance. / From our finding on heterogeneity factors, we then develop a performance estimation technique to address performance assessment for cases where direct measurements are unavailable. This technique is based on the generalization concept, i.e. estimating performance based on the measurement gathered by similar clients. A two-stage grouping scheme based on the heterogeneity factors we identified earlier is proposed to address the problem of determining client similarity. We then develop an estimation algorithm and validate it using synthetic data, as well as real world datasets. / With regard to performance prediction, we focus on the medium-term prediction aspect to address the needs of the emerging technology requirements: distinguishing providers based on medium-term (e.g. one to seven days) performance. Such applications are found when the providers require subscription from their clients to access the service. Another situation where the medium-term prediction is important is in temporal-aware selection: the providers need to be differentiated, based on the expected performance of a particular time interval (e.g. during business hours). We investigate the applicability of classical time series prediction methods: ARIMA and exponential smoothing, as well as their seasonal counterparts – seasonal ARIMA and Holt-Winters. Our results show that these existing models lack the ability to capture the important characteristics of client-perceived performance, thus producing poor medium-term prediction. We then develop a medium-term prediction method that is specifically designed to account for the key characteristics of a client-perceived performance series, and to show that our prediction methods produce higher accuracy for medium-term prediction compared to the existing methods. / In order to demonstrate the applicability of our solution in practice, we developed a provider recommendation framework based on client-perceived performance (named PROPPER), which utilizes our findings on performance assessment and prediction. We formulated the recommendation algorithm and evaluated it through a mirror selection case study. It is shown that our framework produces better outcomes in most cases, compared to country-based or geographic distance-based selection schemes, which are the current approach of mirror selection nowadays.

This research seeks to identify how an organization's facility management (FM) practices relate with the state of sustainability in the organization. A review of the literature leads to presentation of a model defining these relationships. The concepts of direct and indirect FM sustainability roles in organizational sustainability are presented. Accepted facility metrics found in the APPA Facilities Performance Indicator Survey are used as indicators of FM in University System of Georgia institutions and are tested for correlation with sustainability best practices scores generated in an assessment performed for this research. FM performance indicators representing the direct role of FM are not found to be correlated with organizational sustainability best practicesin USG higher education organizations.

This thesis analyzes fundamental estimation filters &ndash / Alpha-Beta Filter, Alpha-Beta-Gamma Filter, Constant Velocity (CV) Kalman Filter, Constant Acceleration (CA) Kalman Filter, Extended Kalman Filter, 2-model Interacting Multiple Model (IMM) Filter and 3-model IMM with respect to their resource requirements and performance. In resource requirement part, fundamental estimation filters are compared according to their CPU usage, memory needs and complexity. The best fundamental estimation filter which needs very low resources is the Alpha-Beta-Filter. In performance evaluation part of this thesis, performance metrics used are: Root-Mean-Square Error (RMSE), Average Euclidean Error (AEE), Geometric Average Error (GAE) and normalized form of these. The normalized form of performance metrics makes measure of error independent of range and the length of trajectory. Fundamental estimation filters and performance metrics are implemented in MATLAB. MONTE CARLO simulation method and 6 different air trajectories are used for testing. Test results show that performance of fundamental estimation filters varies according to trajectory and target dynamics used in constructing the filter. Consequently, filter performance is application-dependent. Therefore, before choosing an estimation filter, most probable target dynamics, hardware resources and acceptable error level should be investigated. An estimation filter which matches these requirements will be &lsquo / the best estimation filter&rsquo / .

Em um ambiente altamente competitivo, onde a disputa por clientes rentáveis torna-se cada vez mais acirrada, a crescente importância das ações de marketing como atividades estratégicas ganham destaque. Este papel traz consigo cobranças, deveres e responsabilidades a serem cumpridas em um ambiente corporativo. Torna-se natural que a alta gestão das companhias exija avaliações de desempenho pautadas pela mensuração dos resultados através de métricas bem definidas e estabelecidas. Mais que indicadores de resultados, as corporações necessitam justificar seus investimentos com maior responsabilidade de forma a garantir transparência junto aos Stakeholders, assim como proporcionar uma melhor remuneração aos Shareholders. Os princípios de Governança Corporativa, Accountability e Compliance tornam-se essenciais nas corporações que exercem as melhores práticas de mercado e utilizam métricas de desempenho como meio de prestação de contas. Àquelas que possuem orientação para mercado necessitam de métricas adequadas e específicas que meçam a satisfação do cliente visando assegurar-lhes uma entrega de valor superior frente aos competidores, pois clientes são ativos de marketing significativos e geram valor para o acionista. Esta dissertação tem por objetivo estudar métricas de desempenho, que são utilizadas regularmente pelos gestores de marketing para análise de resultados, alocação de recursos e Accountability. Para que o objetivo ora proposto fosse alcançado, o estudo foi organizado em duas etapas, onde a primeira aborda o levantamento do referencial teórico, que visou organizar o conhecimento das métricas de desempenho proposto em literatura, sobre a evolução do pensamento de marketing e sua influência no desenvolvimento e utilização de métricas para aferir resultados, alocação de recursos, valor para o Acionista, Accountability em marketing e seus objetivos, orientação para mercado e Métricas de desempenho e aplicações. A segunda etapa abrange a pesquisa empírica, que proporcionou a identificação das métricas mais difundidas e utilizadas pelas empresas farmacêuticas de medicamentos isentos de prescrição no Brasil e seus gestores de marketing, para aferir resultados, subsidiar alocação de recursos e Accountability em Marketing, bem como àquelas que são consideradas mais importantes por estes profissionais. Este estudo foi desenvolvido por meio de uma abordagem quantitativa, através de levantamento, utilizando um questionário estruturado (survey), via internet, o qual foi aplicado em gestores de marketing de empresas farmacêuticas de medicamentos isentos de prescrição. A análise dos dados obtidos por meio da pesquisa empírica foi descrita de forma detalhada, assim como os achados da utilização das métricas em acordo com perfil da empresa, seja por tamanho ou origem. Dentre os principais resultados encontrados e por meio da análise das evidencias apresentadas, as métricas mais utilizadas são as métricas de margens e lucros e financeiras, quando analisamos empresas multinacionais, e, as empresas nacionais, embora também façam uso das métricas de margens e lucros, utilizam com mais intensidade em seu lugar as métricas de mapeamento, segmentação e posicionamento de mercado, associadas às financeiras. / In a highly competitive environment where competition for profitable customers becomes increasingly fierce, the growing importance of marketing actions as strategic activities is highlighted. This importance carries duties, responsibilities, and requests to be met in a corporate environment. It becomes natural that top management of companies requires performance evaluations based on well-defined and established measurements of results. More than indicators of results, corporations need to justify their investments with greater responsibility to ensure transparency with stakeholders, as well as provide better remuneration to Shareholders. Principles of Corporate Governance, Accountability and Compliance become essential in corporations that exert the best market practices and use performance metrics as a means of accountability. Those that have market orientation require appropriate and specific metrics that measure customer satisfaction in order to ensure the delivery of superior value compared to competitors, because customers are marketing assets and generate significant shareholder value. This thesis aims to study performance metrics, which are regularly used by marketing managers to analyze results, resource allocation and Accountability. To reach the proposed objective, this study was organized in two parts: the first deals with the survey of theoretical framework, which aimed at organizing knowledge of the performance metrics proposed in the literature, the evolution of marketing ideas and their influence in the development and use of metrics to measure results, resource allocation, value for Shareholders, Accountability and marketing objectives, market orientation and performance metrics and applications. The second part covers the empirical research, which yielded the identification of the most widespread marketing metrics used by non-prescription drug pharmaceutical companies in Brazil and their managers to measure outcomes, support resource allocation and Accountability in Marketing, as well as those that are considered most important by these professionals. This study was conducted via a quantitative approach, through a structured questionnaire (survey), via the Internet, where the survey instrument was proposed to marketing managers of non-prescription drug pharmaceutical companies. The analysis of data obtained through empirical research has been described in detail, as well as the findings of the use of metrics in accordance with company profile, either by size or origin. Among the main findings and analyzing the evidence presented, the most frequently used metrics are financial and margins & profits when we are analyzing multinational companies. When we analyze the domestic companies, although it also makes use of margins & profits metrics, they used more intensively in its place mapping, segmentation and market positioning metrics, associated with financial metrics.

A mobile ad-hoc network is an assortment of wireless mobile hosts, which establishes a momentary network without any assist of centralized administrator. The characteristics of an ad-hoc network can be explored on the base of routing protocols. The dynamic topology is the vital characteristic in which nodes frequently change their position. In the ad-hoc networks, there are mobile nodes such as Personal Digital Assistance (PDA), smart phone and laptops; they have limited operational resources like battery power and bandwidth. The control traffic is to be minimized, which is the main responsibility of routing protocols by selecting the shortest path and controlling the traffic. In this study work, we focus on performance issues of routing protocols, Optimized Link State Routing (OLSR), Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Temporally Ordered Routing Algorithm (TORA) in mobility and standalone ad-hoc networks. For this purpose, we first study and explain these protocols and then we use the Optimized Network Engineering Tool (OPNET) modeler tool and analyze the performance metrics delay, throughput and network load.