Yes / As big data (BD) and data analytics gain significance in Europe, the industry expects that executives will eventually move towards evidence based decision making, and consequently would build sustainable competitive advantages for their organisations. Therefore, the lessons learned from experiences of European executives can be key for human development and also economic development. However, it also seems that in some cases decision makers in Europe seem to not use business intelligence systems at all. Since, executives are intelligent human beings with credible and proven expertise, it seems to raise a question mark on effectiveness of business intelligence systems, and the potential it has in human and economic development. Furthermore, repeated evaluation of literature pointed out that ultimately executives in Europe make decisions by intuition, and this leads to the question whether big data would ever replace intuition. In this paper, the mind-sets of executives about application and limitations of big data have been explored, by taking into account the cognitive factors in decision making. By using this, it is evaluated whether BD technologies can use to accelerate intuition development of the executives, and consequently lead to faster and sustainable economic development in the developing world.

Engineering problems involving the development of cheap, easy-to-use, and effective packet communications terminals for connectivity to low-earth-orbit satellites (PACSATs) are addressed. Two prototype terminals were developed: a base station for maximum duration connectivity to the satellite, and a smaller station for portability and low cost. Commercially available systems for related amateur radio uses were integrated for these prototypes. The prototypes illustrated areas for further development before widespread use of PACSATs can be realized. To better understand some of the issues for PACSATs, two analyses were developed. The first analysis approach characterizes PACSAT orbits so that tradeoffs are readily identified and quantified. Results from an analysis of one PACSAT orbit indicate conflicting needs for the two terminal types. The second analysis approach addresses issues involving the use of an increasingly popular method for transmitting 9600 baud FSK which combines the spectral efficiency of premodulation pulse shaping with the simplicity of using FM discriminators for demodulation. The spectrum of the transmitted signal is studied and the performance of the demodulator is compared to that of an appropriate coherent receiver. Doppler shifts on the channel is particularly important for PACSAT communications. An analysis approach that addresses the mistuning problem is presented. Results of this analysis identify changes that would better suit the needs of PACSAT terminals. / Master of Science

No description available.

With the advent of information technology, MIS research has tried to understand and describe the impact of this technology on organizations. To date the vast majority of this research has focused on a macro-level of analysis. But the introduction of the microcomputer has significantly altered the focus of computing through the development of a body of managerial computer users. This study looked at the following questions: What factors constitute an information technology user environment? What are the usage and knowledge differences which constitute a concept of user sophistication? Do those differences significantly impact on a user’s level of structured decisions and assessment of information attributes? To answer these questions a study was conducted of 229 middle managers in two academic institutions. The author developed a conceptual model of an information technology user to serve as the basis for the analysis. The study employed a multivariate regression analysis to test hypotheses developed from the user model. The results indicated that a positive relationship exists between managerial computer usage and a high perceived level of structured decisions. Furthermore, there was a strong association between a managerial user’s level of computer understanding and his assessment of information reliability and sufficiency. The study also identified significant differences in a user’s information technology environments and cognitive types. / Ph. D.

Decision Support Systems (DSS) should increase the effectiveness of a decision and the efficiency of the decision making process. The success of DSSs has varied among individual users. One explanation for this variation is that individual’s spatial ability has a moderating effect on performance. Another factor found to impact decision performance is the structure of the task. The purpose of this study is to determine whether spatial ability factors have a moderating effect on decision making performance in a DSS environment under differing task structure. Three of the major factors of spatial ability (spatial scanning, spatial relations, and field independence) and two levels of task structure (moderately complex and complex) are considered in the study. Spatial scanning and field independence were assessed by the Kit Factor-Reference Cognitive Tests, Map Planning Test and Hidden Figures Test, respectively [Ekstrom et al., 1976]. Spatial relations was assessed by the Mental Rotations Test [Vanderberg & Kuse, 1978]. Model formulation and data analysis are two stages of decision making considered in the study. Decision making performance is assessed by time to complete the task, DSS features used, decision confidence, and decision accuracy. Computer experience is treated as a control variable. Fifty Master level students in the School of Business attended three experimental sessions which involved completing several spatial ability tests, participating in a ninety minute lecture on the software package, and completing four practice problems and two experimental cases. The software package employed in the experiment is IFPS, a DSS generator. The results of the study indicate that spatial relations has a moderating effect on decision confidence during the data analysis stage of decision making. Furthermore, there is a significant moderating interaction effect between spatial relations and task complexity when performance is assessed by decision confidence. Spatial relations is found to be more significantly related to performance in the complex case than in the moderately complex case. / Ph. D.

Yes / The increasing prevalence and associated cost of treating chronic obstructive pulmonary disease (COPD) is unsustainable. Health care organizations are focusing on ways to support self-management and prevent hospital admissions, including telehealth-monitoring services capturing physiological and health status data. This paper reports on data captured during a pilot randomized controlled trial of telehealth-supported care within a community-based service for patients discharged from hospital following an exacerbation of their COPD. The aim was to undertake the first analysis of system data to determine whether telehealth monitoring can identify an exacerbation of COPD, providing clinicians with an opportunity to intervene with timely treatment and prevent hospital readmission. Methods: A total of 23 participants received a telehealth-supported intervention. This paper reports on the analysis of data from a telehealth monitoring system that captured data from two sources: (1) data uploaded both manually and using Bluetooth peripheral devices by the 23 participants and (2) clinical records entered as nursing notes by the clinicians. Rules embedded in the telehealth monitoring system triggered system alerts to be reviewed by remote clinicians who determined whether clinical intervention was required. We also analyzed data on the frequency and length (bed days) of hospital admissions, frequency of hospital Accident and Emergency visits that did not lead to hospital admission, and frequency and type of community health care service contacts—other than the COPD discharge service—for all participants for the duration of the intervention and 6 months postintervention. Results: Patients generated 512 alerts, 451 of which occurred during the first 42 days that all participants used the equipment. Patients generated fewer alerts over time with typically seven alerts per day within the first 10 days and four alerts per day thereafter. They also had three times more days without alerts than with alerts. Alerts were most commonly triggered by reports of being more tired, having difficulty with self-care, and blood pressure being out of range. During the 8-week intervention, and for 6-month follow-up, eight of the 23 patients were hospitalized. Hospital readmission rates (2/23, 9%) in the first 28 days of service were lower than the 20% UK norm. Conclusions: It seems that the clinical team can identify exacerbations based on both an increase in alerts and the types of system-generated alerts as evidenced by their efforts to provided treatment interventions. There was some indication that telehealth monitoring potentially delayed hospitalizations until after patients had been discharged from the service. We suggest that telehealth-supported care can fulfill an important role in enabling patients with COPD to better manage their condition and remain out of hospital, but adequate resourcing and timely response to alerts is a critical factor in supporting patients to remain at home. / This project was funded by the National Institute for Health Collaboration for Leadership in Applied Health Research and Care Yorkshire and Humber (CLAHRC YH).

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-04-24T13:52:10Z No. of bitstreams: 1 Julio Cesar da Silva Soares.pdf: 1645821 bytes, checksum: e32d7384c0a6f1999bc7eb190dcd7a05 (MD5) / Made available in DSpace on 2017-04-24T13:52:10Z (GMT). No. of bitstreams: 1 Julio Cesar da Silva Soares.pdf: 1645821 bytes, checksum: e32d7384c0a6f1999bc7eb190dcd7a05 (MD5) Previous issue date: 2017-03-22 / FAPEMA / Urban roads are very complex. The increase in the flow of vehicles in the cities has contributed to traffic accidents. Researches for accident reduction show that the traffic lights are effective in reducing accidents. Traffic lights can minimize the occurrence of accidents at intersections and crosswalks. The implementation of traffic light signals shows significant advantages, otherwise reveals some problems such as the failure to detect road signs by drivers on urban roads. This fact is related to excessive visual information, the stress of the drivers and/or eyestrain makes the drivers lose their attention. These reasons motivated researches about intelligent vehicles. This work aims to develop a methodology to detect and recognize traffic lights, to be applied in smart vehicles. This methodology can contribute to the Advanced Driver Support Systems (ADAS), which assists drivers, especially those with partial vision impairment. Image processing techniques are used to develop the detection methodology. Back project and global thresholding are combined to find light points. Local thresholding techniques are applied to calculate the symmetry between the radius and the center of the light points to segment the traffic light body. The first step got an average rate of 99% of detection. The features of the traffic lights are extracted using Haralick texture measures, with the inclusion of color and shape information. The data generated by the feature extraction step were preprocessed using the SMOTE technique to balance the database. The recognition and identification of the traffic lights state are made by an artificial neural network using Multilayer-Perceptron (MLP). The backpropagation learning algorithm are used in the network training. The validation results show an average recognition rate of 98%. / As vias urbanas estão cada vez mais complexas e o acréscimo no fluxo de veículos nas cidades de médio e grande porte vem contribuindo para a elevação do número de acidentes. Pesquisas apontam que os sinais de trânsito são eficientes na redução do número de acidentes. A implantação de sinais de trânsito apresentam vantagens relevantes, mas por outro lado revelam alguns problemas, como a dificuldade na detecção de sinais de trânsito pelos condutores em vias urbanas. Este fato está relacionado à quantidade de informações visuais nas vias, ao estresse dos motoristas e/ou à fadiga visual destes, que fazem os motoristas desviarem sua atenção da sinalização. Estas razões motivaram muitas pesquisas nos últimos anos, sobre o tema veículos inteligentes. Assim, o presente trabalho propõe uma metodologia para detectar e reconhecer semáforos de trânsito para ser aplicada em veículos inteligentes, podendo contribuir para os Advanced Driver Support Systems - ADAS (Sistema Avançado de Auxílio ao Motorista), e que auxilie os motoristas, em especial aqueles com deficiência parcial da visão. Além disso, o sistema desenvolvido é capaz de identificar o estado do semáforo e indicar ao condutor se ele deve parar ou prosseguir, contribuindo assim para a redução de acidentes de transito. Para o desenvolvimento do algoritmo de detecção, utilizaram-se técnicas de processamento de imagens, através de histograma retroprojetado e limiarização global para detectar pontos de luzes. A limiarização local é aplicada para o cálculo de simetria entre o raio e o centro dos pontos de luzes, com a finalidade de segmentar o corpo do semáforo, onde se obteve uma taxa média de detecção de 99%. As características dos semáforos foram extraídas utilizando os atributos de Haralick, com a inclusão de informações de cor e forma. Os dados gerados pela extração de características foram pré-processados utilizando a técnica de SMOTE para balancear a base de dados. O reconhecimento e a identificação do estado do semáforo foram realizados por uma rede neural artificial do tipo Multilayer Perceptron (MLP). No treinamento da rede se utilizou o algoritmo de aprendizagem backpropagation e a separação de dados para treinamento e validação. Os resultados da validação mostraram uma taxa média de reconhecimento de 98%.

Safety of the airborne platforms rests heavily on the way they are maintained. This maintenance includes repairs and testing, to reduce platform down time. Maintenance is performed using generic and specific test equipment within the existing maintenance management system (MMS). This thesis reports the work undertaken to improve maintainability and availability of avionics systems using an intelligent decision support system (IDSS). In order to understand the shortcomings of the existing system, the prevalent practices and methodologies are researched. This research thesis reports the development and implementation of an IDSS and the significant improvements made by this IDSS by integrating autonomous and independent information sources by employing a multi-agent system (MAS). Data mining techniques and intelligence agents (IA) are employed to create an expert system. The developed IDSS successfully demonstrates its ability to integrate and collate the available information and convert into valuable knowledge. Using this knowledge, the IDSS is able to generate interpreted alerts, warnings and recommendations thereby reasonably improving platform maintainability and availability. All facets of integrated logistics support (ILS) are considered to create a holistic picture. As the system ages, the IDSS also matures to assist managers and maintainers in making informed decisions about the platform, the unit under test (UUT) and even the environment that supports the platform.

Thesis (M.S.)--University of Missouri-Columbia, 2009. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Thesis advisor: Yang Gong. "May 2009" Includes bibliographical references.

No description available.