984 resultados para Service Interruption Modelling
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Dissertation to obtain the degree of Master in Chemical and Biochemical Engineering
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Enterprise Resource Planning (ERP) system literature reports very little research on post-adoption stages, that is, actual usage and value. Even fewer studies focus on the specificities of an industry analysis. Based on the Technology-Organizational-Environment (TOE) framework and the Resource-Based View (RBV) theory, we develop a research model to measure and examine determinants of ERP use and value and their impact in the Iberian region (Portugal and Spain) across Manufacturing and Services industries in Small and Medium Enterprises (SMEs). The empirical test was conducted through structural equation modelling, using data from 261 firms in the peninsula in the Manufacturing and Service industries. Results show that amongst ERP use determinants, Training is the most important determinant for Service firms and Compatibility for Manufacturing firms. Firm size, Analytics, and Collaboration contribute to ERP Value in both industries, with Analytics being more important for the Service industry. The paper provides insight into which determinants contribute to ERP use and ERP value in Iberian Manufacturing and Services SMEs, offering managerial and academic implications.
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The purpose of this thesis is to study the impact of a port strike on companies that perform as logistic service providers in a supply chain (SC), here denominated 3PL (third-party logistic providers). These companies are highly dependent on ports to perform their activity, since they provide international services. Consequently, a disruption in a port can seriously impair their business. A stevedores’ strike is one of the possible disruptions that can affect ports. This study aims to analyze the negative effects caused by this disruption, and what strategies 3PLs may implement in order to keep their performance levels stable and have a quick recovery time. Within this objective, the first step will be to establish a theoretical context about the maritime port’s sector and 3PLs in a SC context, to then expand the concept of a resilient SC, and finally to develop a theoretical framework in order to better contextualize the case study. Subsequently, the impact of a port strike will be quantified by using a case study comprising three companies, covering the areas of land and sea distribution and port operations. Information from primary sources was assembled in two phases: first via e-mail and, in a second phase, through a personal interview. The information from secondary sources was obtained through television news, internet and conferences, enabling its cross-analysis. Finally, by analyzing the collected data, it will be possible to draw conclusions about the measures carried out by each company to minimize the negative effects of the strike, thus contributing to a more resilient SC. As a conclusion, a stevedores’ strike will create a snow-ball of negative effects in the SC, degrading all relevant KPIs (key performance indicators) of the 3PLs under study. No mitigation and contingency strategies available proved really effective to reduce the negative effects of a port strike disruption.
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This project aims to prepare Worten Empresas (WE) fulfilling the increasing market demand through process changings, focusing on the Portuguese market, particularly on internal B2B clients1. Several methods were used to measure the current service level provided - process mapping, resources assessment, benchmark and a survey. The results were then used to compare against service level actually desired by WE’s customer, and then to identify the performance gaps in response times and quality of the follow-up during the sales process. To bridge the identified gaps, both a set of recommendations and an implementation plan were suggested to improve and monitor customer experience. This study concluded that it is possible to fulfill the increasing level of demand and at the same time improve customer satisfaction by implementing changes at the operations level.
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In order to estimate the incidence of and risk factors for developing tuberculosis, the clinical charts of a retrospective cohort of 281 HIV-positive adults, who were notified to the AIDS Program of the Health Department of Brasilia in 1998, were reviewed in 2003. All the patients were treatment-naive regarding antiretroviral therapy at the time of inclusion in the cohort. Twenty-nine patients were identified as having tuberculosis at the start of the study. Thirteen incident tuberculosis cases were identified during the 60 months of follow-up, with an incidence density rate of 1.24/100 person-years. Tuberculosis incidence was highest among patients with baseline CD4+ T-lymphocyte counts < 200 cells/µl who were not using antiretroviral therapy (incidence = 5.47; 95% CI = 2.73 to 10.94). Multivariate analysis showed that baseline CD4+ T-lymphocyte counts < 200 cells/µl (adjusted hazard ratio [AHR] = 5.09; 95% CI = 1.27 to 20.37; p = 0.02) and non-use of antiretroviral therapy (AHR = 12.17; 95% CI = 2.6 to 56.90; p = 0.001) were independently associated with increased risk of tuberculosis.
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This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.
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Teleoperation is a concept born with the rapid evolution of technology, with an intuitive meaning "operate at a distance." The first teleoperation system was created in the mid 1950s, which were handled chemicals. Remote controlled systems are present nowadays in various types of applications. This dissertation presents the development of a mobile application to perform the teleoperation of a mobile service robot. The application integrates a distributed surveillance (the result of a research project QREN) and led to the development of a communication interface between the robot (the result of another QREN project) and the vigilance system. It was necessary to specify a communication protocol between the two systems, which was implemented over a communication framework 0MQ (Zero Message Queue). For the testing, three prototype applications were developed before to perform the test on the robot.
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Transport is an essential sector in modern societies. It connects economic sectors and industries. Next to its contribution to economic development and social interconnection, it also causes adverse impacts on the environment and results in health hazards. Transport is a major source of ground air pollution, especially in urban areas, and therefore contributing to the health problems, such as cardiovascular and respiratory diseases, cancer, and physical injuries. This thesis presents the results of a health risk assessment that quantifies the mortality and the diseases associated with particulate matter pollution resulting from urban road transport in Hai Phong City, Vietnam. The focus is on the integration of modelling and GIS approaches in the exposure analysis to increase the accuracy of the assessment and to produce timely and consistent assessment results. The modelling was done to estimate traffic conditions and concentrations of particulate matters based on geo-references data. A simplified health risk assessment was also done for Ha Noi based on monitoring data that allows a comparison of the results between the two cases. The results of the case studies show that health risk assessment based on modelling data can provide a much more detail results and allows assessing health impacts of different mobility development options at micro level. The use of modeling and GIS as a common platform for the integration of different assessments (environmental, health, socio-economic, etc.) provides various strengths, especially in capitalising on the available data stored in different units and forms and allows handling large amount of data. The use of models and GIS in a health risk assessment, from a decision making point of view, can reduce the processing/waiting time while providing a view at different scales: from micro scale (sections of a city) to a macro scale. It also helps visualising the links between air quality and health outcomes which is useful discussing different development options. However, a number of improvements can be made to further advance the integration. An improved integration programme of the data will facilitate the application of integrated models in policy-making. Data on mobility survey, environmental monitoring and measuring must be standardised and legalised. Various traffic models, together with emission and dispersion models, should be tested and more attention should be given to their uncertainty and sensitivity
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In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.
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Retail services are a main contributor to municipal budget and are an activity that affects perceived quality-of-life, especially for those with mobility difficulties (e.g. the elderly, low income citizens). However, there is evidence of a decline in some of the services market towns provide to their citizens. In market towns, this decline has been reported all over the western world, from North America to Australia. The aim of this research was to understand retail decline and enlighten on some ways of addressing this decline, using a case study, Thornbury, a small town in the Southwest of England. Data collected came from two participatory approaches: photo-surveys and multicriteria mapping. The interpretation of data came from using participants as analysts, but also, using systems thinking (systems diagramming and social trap theory) for theory building. This research moves away from mainstream economic and town planning perspectives by making use of different methods and concepts used in anthropology and visual sociology (photo-surveys), decision-making and ecological economics (multicriteria mapping and social trap theory). In sum, this research has experimented with different methods, out of their context, to analyse retail decline in a small town. This research developed a conceptual model for retail decline and identified the existence of conflicting goals and interests and their implications for retail decline, as well as causes for these. Most of the potential causes have had little attention in the literature. This research also identified that some of the measures commonly used for dealing with retail decline may be contributing to the causes of retail decline itself. Additionally, this research reviewed some of the measures that can be used to deal with retail decline, implications for policy-making and reflected on the use of the data collection and analysis methods in the context of small to medium towns.
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With the continuum growth of Internet connected devices, the scalability of the protocols used for communication between them is facing a new set of challenges. In robotics these communications protocols are an essential element, and must be able to accomplish with the desired communication. In a context of a multi-‐‑agent platform, the main types of Internet communication protocols used in robotics, mission planning and task allocation problems will be revised. It will be defined how to represent a message and how to cope with their transport between devices in a distributed environment, reviewing all the layers of the messaging process. A review of the ROS platform is also presented with the intent of integrating the already existing communication protocols with the ServRobot, a mobile autonomous robot, and the DVA, a distributed autonomous surveillance system. This is done with the objective of assigning missions to ServRobot in a security context.
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This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles.
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As the complexity of markets and the dynamicity of systems evolve, the need for interoperable systems capable of strengthening enterprise communication effectiveness increases. This is particularly significant when it comes to collaborative enterprise networks, like manufacturing supply chains, where several companies work, communicate, and depend on each other, in order to achieve a specific goal. Once interoperability is achieved, that is once all network parties are able to communicate with and understand each other, organisations are able to exchange information along a stable environment that follows agreed laws. However, as markets adapt to new requirements and demands, an evolutionary behaviour is triggered giving space to interoperability problems, thus disrupting the sustainability of interoperability and raising the need to develop monitoring activities capable of detecting and preventing unexpected behaviour. This work seeks to contribute to the development of monitoring techniques for interoperable SOA-based enterprise networks. It focuses on the automatic detection of harmonisation breaking events during real-time communications, and strives to develop and propose a methodological approach to handle these disruptions with minimal or no human intervention, hence providing existing service-based networks with the ability to detect and promptly react to interoperability issues.
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Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/64337/2009 ; projects PTDC/ECM/70652/2006, PTDC/ECM/117660/2010 and RECI/ECM-HID/0371/2012
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INTRODUCTION: Leprosy is an infectious disease caused by Mycobacterium leprae. The aim of this study was to describe the epidemiological, clinical, and operational aspects of leprosy carriers. METHODS: A cross-sectional study leprosy patients assisted in São Luis, MA, was performed. RESULTS: Of the 85 cases analyzed, 51.7% were male participants, and 60% were brown. Concerning the age, 54.8% of women were between 35 and 49 years, and 57.6% of men were between 20 and 34 years. Lepromatous leprosy was found in 42.3% of cases, and the multibacillary form was found in 72.9%. The skin smear was positive in 42.3%. The occurrence of reaction was found in 43.5% of cases, and 83.5% had no Bacillus Calmette-Guérin scar. Leprosy in the family was reported by 44.7% of the patients. Most of the individuals (96.4%) lived in houses made of brick with more than three rooms (72.6%) and two persons per room (65.1%). Concerning the level of education, 41.4% of women and 34.1% of men had more than one to three years of education. The most evaluated age group in the beginning of the treatment was that of 35 to 49 years with a Grade 0 incapability (64.5%), and that in the end was the age group of 20 to 34 (29.9%) with Grade 0, 30.7% Grade 1, and 11.5% Grade 2. CONCLUSIONS: The frequency of multibacillary forms found in this study and the cases in family members point out delayed diagnoses. Thus, early diagnosis and appropriate treatment are important in decreasing the outcome of disabilities.