State estimation is widely used as a tool to evaluate the real time power system prevailing conditions. State estimation algorithms could suffer divergence under stressed system conditions. This dissertation first investigates impacts of variations of load levels and topology errors on the convergence property of the commonly used weighted least square (WLS) state estimator. The influence of topology errors on the condition number of the gain matrix in the state estimator is also analyzed. The minimum singular value of gain matrix is proposed to measure the distance between the operating point and state estimation divergence. To study the impact of the load increment on the convergence property of WLS state estimator, two types of load increment are utilized: one is the load increment of all load buses, and the other is a single load increment. In addition, phasor measurement unit (PMU) measurements are applied in state estimation to verify if they could solve the divergence problem and improve state estimation accuracy. The dissertation investigates the impacts of variations of line power flow increment and topology errors on convergence property of the WLS state estimator. A simple 3-bus system and the IEEE 118-bus system are used as the test cases to verify the common rule. Furthermore, the simulation results show that adding PMU measurements could generally improve the robustness of state estimation. Two new approaches for improving the robustness of the state estimation with PMU measurements are proposed. One is the equality-constrained state estimation with PMU measurements, and the other is Hachtel's matrix state estimation with PMU measurements approach. The dissertation also proposed a new heuristic approach for optimal placement of phasor measurement units (PMUs) in power system for improving state estimation accuracy. In the problem of adding PMU measurements into the estimator, two methods are investigated. Method I is to mix PMU measurements with conventional measurements in the estimator, and method II is to add PMU measurements through a post-processing step. These two methods can achieve very similar state estimation results, but method II is a more time-efficient approach which does not modify the existing state estimation software.

Several studies have examined the effect of remittances on economic growth,poverty, education, and governance, among other factors, in developing countrieswith inconclusive results. Using annual panel data of 99 developing countries invarious empirical models, this study aim to answer the question how remittances affect a broader aspect of development using the Human Development Index asdependent variable. The findings indicate that there is a positive relationship between remittances and the level of human development in developing countries.

The thesis analyses and validates Beamforming methods using Convex Optimization.  CVX which is a Matlab supported tool for convex optimization has been used to develop this concept. An algorithm is designed by which an appropriate system has been identified by varying parameters such as number of antennas, passband width, and stopbands widths of a beamformer. We have observed the beamformer by minimizing the error for Least-square and Infinity norms. A graph obtained by the optimum values between least-square and infinity norms shows us a trade-off between these two norms. We have observed convex optimization for double passband of a beamformer which has proven the flexibility of convex optimization. On extension for this, we designed a filter in which stopband is arbitrary. A constraint is used by which the stopband would be varying depending upon the upper boundary (limiting) line which varies w.r.t y-axis (dB). The beamformer has been observed for feasibility by varying parameters such as number of antennas, arbitrary upper boundaries, stopbands and passband. This proves that there is flexibility for designing a beamformer as desired.

The primary aim of this research was to investigate the fundamental acoustic properties of several cementitious materials, the influence of mix design parameters/constituents, and finally the effect of the physical and mechanical properties of cementitious material concrete/mortar on the acoustic properties of the material. The main objectives were: To understand the mechanism of sound production in musical instruments and the effects of the material(s) employed on the sound generated; To build upon previous research regarding selection of the tested physical/mechanical properties and acoustic properties of cementitious materials; To draw conclusions regarding the effect of different constituents, mix designs and material properties upon the acoustic properties of the material; To build a model of the relationship between the acoustic properties of a cementitious material and its mix design via its physical/mechanical properties. In order to meet the aim, this research was conducted by employing the semi-experimental (half analytical) method: two experimental programmes were performed (I and II); a mathematical optimization technique (least square method) was then implemented in order to construct an optimized mathematical model to match with the experimental data. In Experimental Programme I, six constituents/factors were investigated regarding the effect on the physical/mechanical and acoustic properties: cementitious material additives (fly ash, silica fume, and GGBS), superplasticizer, and basic mix design parameters (w/c ratio, and sand grading). 11 properties (eight physical/mechanical properties: compressive strength, density, hardness, flexural strength, flexural modulus, elastic modulus, dynamic modulus and slump test; and three acoustic properties: resonant frequency, speed of sound and quality factor (internal damping)) were tested for each constituents/factors related mortar type. For each type of mortar, there were three cubes, three prisms and three cylinders produced. In Experimental Programme I, 20 mix designs were investigated, 180 specimens produced, and 660 test results recorded. After analysing the results of Experimental Programme I, fly ash (FA), w/b ratio and b/s ratio were selected as the cementitious material/factors which had the greatest influence on the acoustic properties of the material; these were subsequently investigated in detail in Experimental Programme II. In Experimental Programme II, various combinations of FA replacement level, w/b ratios and b/s ratios (three factors) resulted in 1122 test results. The relationship between these three factors on the selected 11 properties was then determined. Through using regression analysis and optimization technique (least square method), the relationship between the physical/mechanical properties and acoustic properties was then determined. Through both experimental programmes, 54 mix designs were investigated in total, with 486 specimens produced and tested, and 1782 test results recorded. Finally, based upon well-known existing relationships (including, model of compressive strength and elastic modulus, and the model of elastic modulus and dynamic modulus), and new regressioned models of FA-mortar (the relationship of compressive strength and constituents, which is unique for different mixes), the optimized object function of acoustic properties (speed of sound and damping ratio) and mix design (proportions of constituents) were constructed via the physical/mechanical properties.

This study aims at developing a model to estimate flood damage cost caused in Gonaives, Haiti by Hurricane Jeanne in 2004. In order to reach this goal, the influence of income, inundation duration and inundation depth, slope, population density and distance to major roads on the loss costs was investigated. Surveyed data were analyzed using Excel and ArcGIS 10 software. The ordinary least square and the geographically weighted regression analyses were used to predict flood damage costs. Then, the estimates were delineated using voronoi geostatistical map tool. As a result, the factors account for the costs as high as 83%. The flood damage cost in a household varies between 24,315 through 37,693 Haitian Gourdes (approximately 607.875 through 942.325 U.S. Dollars). Severe damages were spotted in the urban area and in the rural section of Bassin whereas very low and low losses are essentially found in Labranle. The urban area was more severely affected by comparison with the rural area. Damages in the urban area are estimated at 41,206,869.57USD against 698,222,174.10 17,455,554.35USD in the rural area. In the urban part, damages were more severe in Raboteau-Jubilée and in Downtown but Bigot-Parc Vincent had the highest overall damage cost estimated at 9,729,368.95 USD. The lowest cost 7,602,040.42USD was recorded in Raboteau. Approximately, 39.38% of the rural area underwent very low to moderate damages. Bassin was the most severely struck by the 2004 floods, but Bayonnais turned out to have the highest loss cost: 4,988,487.66 USD. Bassin along with Labranle had the least damage cost, 2,956,131.11 and 2,268,321.41 USD respectively. Based on the findings, we recommended the implementation and diversification of income-generating activities, the maintenance and improvement of drains, sewers and gullies cleaning and the establishment of conservation practices upstream of the watersheds. In addition, the model should be applied and validated using actual official records as reference data. Finally, the use of a calculation-based approach is suggested to determine flood damage costs in order to reduce subjectivity during surveys.

We are currently living in the Internet of Things (IoT) era, which involves devices that are connected to Internet and are communicating with each other. Each year, the number of devices increases rapidly, which result in rapid growth of data that is generated. This large amount of data is sometimes titled as Big Data, which is generated from different sources, such as log data of user behavior. These log files can be collected and analyzed in different ways, such as creating product recommendations. Product recommendations have been around since the late 90s, when the amount of data collected were not at the same level as it is today. The aim of this thesis has been to investigating methods to process and create product recommendations to see how well they are adapted for Big Data. This has been accomplished by three theory studies on how to process user events, how to make the product recommendation algorithm called collaborative filtering scalable and finally how to convert implicit feedback to explicit feedback (ratings). This resulted in a recommendation engine consisting of Apache Spark as the data processing system, which had three functions: read multiple log files and concatenate log files for each month, parsing the log files of the user events to create explicit ratings from the transactions and create four types of recommendations. The NoSQL database MongoDB was chosen as the database to store the different types of product recommendations that was created. To be able to get the recommendations from the recommendation engine and the database, a REST API was implemented which can be used by any third-party. What can be concluded from the results of this thesis work is that the system that was implemented is partial scalable. This means that Apache Spark was scalable for both concatenating files, parse and create ratings and also create the recommendations using the ALS method. However, MongoDB was shown to be not scalable when managing more than 100 concurrent requests. Future work involves making the recommendation engine distributed in a multi-node cluster to utilize the parallelization of Apache Spark. Other recommendations include considering other NoSQL databases that might be more scalable than MongoDB.

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The focus of the project is to validate the fluid model with different flooring materials and the measurements of an instrument to test flooring materials and its force attenuating capabilities using mathematical models to describe the signature and coefficients of the floor.As a part of improving the knowledge about the linear dynamics of vibrations involved during the sudden impact caused on hip bones of elderly people during fall. The project initiated in January 2017 and end date was set to May 2017.The main contribution of the present work focuses on the development of a mathematical fluid model for floors. The aim of the thesis was to analyze, compare different floor materials and to study the linear dynamics of falling impacts on floors. The impact of the hammer during a fall is captured by an accelerometer and response is collected using a picoscope. The collected data was analyzed using matlab least square method which is coded as per the fluid model.The finding from this thesis showed that the fluid model works with a more elastic model but it doesn't work for rigid materials like wood. The importance of parameters like velocity, mass, energy loss and other coefficients of a floor which influences the model during the impact of falling on floors were identified and a standardized testing method was set.

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Orientador: Gilmar Barreto / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T17:28:20Z (GMT). No. of bitstreams: 1 Pucciarelli_AmilcarJose_M.pdf: 3241769 bytes, checksum: cfad3cee97a35c84df363b3a8578479d (MD5) Previous issue date: 2005 / Resumo: Este estudo primeiramente investiga fundamentos teóricos para análise, desenvolvimento e implementação de algoritmos para modelagem de dados de sistemas dinâmicos e de séries temporais com a finalidade de predição. As séries temporais utilizadas são baseadas em dados reais retirados da literatura. A grande vantagem de se modelar uma série temporal e de se prever um dado futuro é poder tomar ações antecipadas sobre ela o quem vem a ser muito útil, por exemplo em controle. O modelo nebuloso Takagi-Sugeno será utilizado na modelagem das séries temporais onde os conjuntos nebulosos do antecedente e os parâmetros do conseqüente são estimados via métodos de agrupamentos e identificação paramétrica, respectivamente / Abstract: This work firstly explores theoretical foundations for analisis, development and implementation of algorithms for data modelling dynamic systems and time series with a prediction goaI. The used time series are based on real data from the literature. The main advantage of time series modelling and forecasting is make antecipated decisions about it, and this becomes very useful, for example, in controI. The Takagi-Sugeno fuzzy model is used for time series modelling where the antecedent fuzzy partitions and the consequent parameters are estimated by clustering methods and parametric identification, respectively / Mestrado / Automação / Mestre em Engenharia Elétrica