Adaptive Probabilistic Topic Models for Social Networks

Thesis (Master's)--University of Washington, 2012

Adaptive learning in agents behaviour: A framework for electricity markets simulation

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. This paper presents a methodology to provide decision support to electricity market negotiating players. This model allows integrating different strategic approaches for electricity market negotiations, and choosing the most appropriate one at each time, for each different negotiation context. This methodology is integrated in ALBidS (Adaptive Learning strategic Bidding System) – a multiagent system that provides decision support to MASCEM's negotiating agents so that they can properly achieve their goals. ALBidS uses artificial intelligence methodologies and data analysis algorithms to provide effective adaptive learning capabilities to such negotiating entities. The main contribution is provided by a methodology that combines several distinct strategies to build actions proposals, so that the best can be chosen at each time, depending on the context and simulation circumstances. The choosing process includes reinforcement learning algorithms, a mechanism for negotiating contexts analysis, a mechanism for the management of the efficiency/effectiveness balance of the system, and a mechanism for competitor players' profiles definition.

Enhancing Agent Mediated Electronic Markets with Ontology Matching Services and Social Network Support

Os Mercados Eletrónicos atingiram uma complexidade e nível de sofisticação tão elevados, que tornaram inadequados os modelos de software convencionais. Estes mercados são caracterizados por serem abertos, dinâmicos e competitivos, e constituídos por várias entidades independentes e heterogéneas. Tais entidades desempenham os seus papéis de forma autónoma, seguindo os seus objetivos, reagindo às ocorrências do ambiente em que se inserem e interagindo umas com as outras. Esta realidade levou a que existisse por parte da comunidade científica um especial interesse no estudo da negociação automática executada por agentes de software [Zhang et al., 2011]. No entanto, a diversidade dos atores envolvidos pode levar à existência de diferentes conceptualizações das suas necessidades e capacidades dando origem a incompatibilidades semânticas, que podem prejudicar a negociação e impedir a ocorrência de transações que satisfaçam as partes envolvidas. Os novos mercados devem, assim, possuir mecanismos que lhes permitam exibir novas capacidades, nomeadamente a capacidade de auxiliar na comunicação entre os diferentes agentes. Pelo que, é defendido neste trabalho que os mercados devem oferecer serviços de ontologias que permitam facilitar a interoperabilidade entre os agentes. No entanto, os humanos tendem a ser relutantes em aceitar a conceptualização de outros, a não ser que sejam convencidos de que poderão conseguir um bom negócio. Neste contexto, a aplicação e exploração de relações capturadas em redes sociais pode resultar no estabelecimento de relações de confiança entre vendedores e consumidores, e ao mesmo tempo, conduzir a um aumento da eficiência da negociação e consequentemente na satisfação das partes envolvidas. O sistema AEMOS é uma plataforma de comércio eletrónico baseada em agentes que inclui serviços de ontologias, mais especificamente, serviços de alinhamento de ontologias, incluindo a recomendação de possíveis alinhamentos entre as ontologias dos parceiros de negociação. Este sistema inclui também uma componente baseada numa rede social, que é construída aplicando técnicas de análise de redes socias sobre informação recolhida pelo mercado, e que permite melhorar a recomendação de alinhamentos e auxiliar os agentes na sua escolha. Neste trabalho são apresentados o desenvolvimento e implementação do sistema AEMOS, mais concretamente: • É proposto um novo modelo para comércio eletrónico baseado em agentes que disponibiliza serviços de ontologias; • Adicionalmente propõem-se o uso de redes sociais emergentes para captar e explorar informação sobre relações entre os diferentes parceiros de negócio; • É definida e implementada uma componente de serviços de ontologias que é capaz de: • o Sugerir alinhamentos entre ontologias para pares de agentes; • o Traduzir mensagens escritas de acordo com uma ontologia em mensagens escritas de acordo com outra, utilizando alinhamentos previamente aprovados; • o Melhorar os seus próprios serviços recorrendo às funcionalidades disponibilizadas pela componente de redes sociais; • É definida e implementada uma componente de redes sociais que: • o É capaz de construir e gerir um grafo de relações de proximidade entre agentes, e de relações de adequação de alinhamentos a agentes, tendo em conta os perfis, comportamento e interação dos agentes, bem como a cobertura e utilização dos alinhamentos; • o Explora e adapta técnicas e algoritmos de análise de redes sociais às várias fases dos processos do mercado eletrónico. A implementação e experimentação do modelo proposto demonstra como a colaboração entre os diferentes agentes pode ser vantajosa na melhoria do desempenho do sistema e como a inclusão e combinação de serviços de ontologias e redes sociais se reflete na eficiência da negociação de transações e na dinâmica do mercado como um todo.

On-line system for faults detection in induction motors based on PCA

Dissertation to obtain the degree of Master in Electrical and Computer Engineering

Opening Pousada da Serra da Estrela in Covilhã: A two-way impact analysis - Interacting with public agents

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Fatigue life assessment of endodontic instruments subjected to multi planar curvature

This present study aimed to investigate the fatigue life of unused (new) endodontic instruments made of NiTi with control memory by Coltene™ and subjected to the multi curvature of a mandibular first molar root canal. Additionally, the instrument‟s structural behaviour was analysed through non-linear finite element analysis (FEA). The fatigue life of twelve Hyflex™ CM files was assessed while were forced to adopt a stance with multiple radius of curvature, similar to the ones usually found in a mandibular first molar root canal; nine of them were subjected to Pecking motion, a relative movement of axial type. To achieve this, it was designed an experimental setup with the aim of timing the instruments until fracture while worked inside a stainless steel mandibular first molar model with relative axial motion to simulate the pecking motion. Additionally, the model‟s root canal multi-curvature was confirmed by radiography. The non-linear finite element analysis was conducted using the computer aided design software package SolidWorks™ Simulation, in order to define the imposed displacement required by the FEA, it was necessary to model an endodontic instrument with simplified geometry using SolidWorks™ and subsequently analyse the geometry of the root canal CAD model. The experimental results shown that the instruments subjected to pecking motion displayed higher fatigue life values and higher lengths of fractured tips than those with only rotational relative movement. The finite element non-linear analyses shown, for identical conditions, maximum values for the first principal stress lower than the yield strength of the material and those were located in similar positions to the instrument‟s fracture location determined by the experimental testing results.

Variability of ascending aorta diameter measurements as assessed with electrocardiography-gated multidetector computerized tomography and computer assisted diagnosis software.

Recently, morphometric measurements of the ascending aorta have been done with ECG-gated multidector computerized tomography (MDCT) to help the development of future novel transcatheter therapies (TCT); nevertheless, the variability of such measurements remains unknown. Thirty patients referred for ECG-gated CT thoracic angiography were evaluated. Continuous reformations of the ascending aorta, perpendicular to the centerline, were obtained automatically with a commercially available computer aided diagnosis (CAD). Then measurements of the maximal diameter were done with the CAD and manually by two observers (separately). Measurements were repeated one month later. The Bland-Altman method, Spearman coefficients, and a Wilcoxon signed-rank test were used to evaluate the variability, the correlation, and the differences between observers. The interobserver variability for maximal diameter between the two observers was up to 1.2 mm with limits of agreement [-1.5, +0.9] mm; whereas the intraobserver limits were [-1.2, +1.0] mm for the first observer and [-0.8, +0.8] mm for the second observer. The intraobserver CAD variability was 0.8 mm. The correlation was good between observers and the CAD (0.980-0.986); however, significant differences do exist (P<0.001). The maximum variability observed was 1.2 mm and should be considered in reports of measurements of the ascending aorta. The CAD is as reproducible as an experienced reader.

Attitudes of second year diploma nurses in three community colleges toward the use of computers in the nursing role /

The effectiveness of various kinds of computer programs is of concern to nurse-educators. Using a 3x3 experimental design, ninety second year diploma student nurses were randomly selected from a total population at three community colleges in Ontario. Data were collected via a 20-item valid and reliable Likert-type questionnaire developed by the nursing profession to measure perceptions of nurses about computers in the nursing role. The groups were pretested and posttested at the beginning and end of one semester. Subjects attending College A group received a computer literacy course which comprised word processing with technology awareness. College B students were exposed to computer-aided instruction primarily in nursing simulations intermittently throughout the semester. College C subjects maintained their regular curriculum with no computer involvement. The student's t-test (two-tailed) was employed to assess the attitude scores data and a one-way analysis of variance was performed on the attitude scores. Posttest analysis revealed that there was a significant difference (p<.05) between attitude scores on the use of computers in the nursing role between College A and C. No significant differences (p>.05) were seen between College B and A in posttesting. Suggestions for continued computer education of diploma student nurses are provided.

Identification of Network-Based Risk Factors Associated with Gonorrhea

The evolving antimicrobial resistance coupled with a recent increase in incidence highlights the importance of reducing gonococcal transmission. Establishing novel risk factors associated with gonorrhea facilitates the development of appropriate prevention and disease control strategies. Sexual Network Analysis (NA), a novel research technique used to further understand sexually transmitted infections, was used to identify network-based risk factors in a defined region in Ontario, Canada experiencing an increase in the incidence of gonorrhea. Linear network structures were identified as important reservoirs of gonococcal transmission. Additionally, a significant association between a central network position and gonorrhea was observed. The central participants were more likely to be younger, report a greater number of risk factors, engage in anonymous sex, have multiple sex partners in the past six months and have sex with the same sex. The network-based risk factors identified through sexual NA, serving as a method of analyzing local surveillance data, support the development of strategies aimed at reducing gonococcal spread.

Scoliosis curve type classification from 3D trunk image

Adolescent idiopathic scoliosis (AIS) is a deformity of the spine manifested by asymmetry and deformities of the external surface of the trunk. Classification of scoliosis deformities according to curve type is used to plan management of scoliosis patients. Currently, scoliosis curve type is determined based on X-ray exam. However, cumulative exposure to X-rays radiation significantly increases the risk for certain cancer. In this paper, we propose a robust system that can classify the scoliosis curve type from non invasive acquisition of 3D trunk surface of the patients. The 3D image of the trunk is divided into patches and local geometric descriptors characterizing the surface of the back are computed from each patch and forming the features. We perform the reduction of the dimensionality by using Principal Component Analysis and 53 components were retained. In this work a multi-class classifier is built with Least-squares support vector machine (LS-SVM) which is a kernel classifier. For this study, a new kernel was designed in order to achieve a robust classifier in comparison with polynomial and Gaussian kernel. The proposed system was validated using data of 103 patients with different scoliosis curve types diagnosed and classified by an orthopedic surgeon from the X-ray images. The average rate of successful classification was 93.3% with a better rate of prediction for the major thoracic and lumbar/thoracolumbar types.

Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

Plasma Polymerised Organic Thin Films-A Study on the Structural, Electrical and Nonlinear Optical Properties for Possible Applications

This proposed thesis is entitled “Plasma Polymerised Organic Thin Films: A study on the Structural, Electrical, and Nonlinear Optical Properties for Possible Applications. Polymers and polymer based materials find enormous applications in the realm of electronics and optoelectronics. They are employed as both active and passive components in making various devices. Enormous research activities are going on in this area for the last three decades or so, and many useful contributions are made quite accidentally. Conducting polymers is such a discovery, and eversince the discovery of conducting polyacetylene, a new branch of science itself has emerged in the form of synthetic metals. Conducting polymers are useful materials for many applications like polymer displays, high density data storage, polymer FETs, polymer LEDs, photo voltaic devices and electrochemical cells. With the emergence of molecular electronics and its potential in finding useful applications, organic thin films are receiving an unusual attention by scientists and engineers alike. This is evident from the vast literature pertaining to this field appearing in various journals. Recently, computer aided design of organic molecules have added further impetus to the ongoing research activities in this area. Polymers, especially, conducting polymers can be prepared both in the bulk and in the thinfilm form. However, many applications necessitate that they are grown in the thin film form either as free standing or on appropriate substrates. As far as their bulk counterparts are concerned, they can be prepared by various polymerisation techniques such as chemical routes and electrochemical means. A survey of the literature reveals that polymers like polyaniline, polypyrrole, polythiophene, have been investigated with a view to studying their structural electrical and optical properties. Among the various alternate techniques employed for the preparation of polymer thin films, the method of plasma polymerisation needs special attention in this context. The technique of plasma polymerisation is an inexpensive method and often requires very less infra structure. This method includes the employment of ac, rf, dc, microwave and pulsed sources. They produce pinhole free homogeneous films on appropriate substrates under controlled conditions. In conventional plasma polymerisation set up, the monomer is fed into an evacuated chamber and an ac/rf/dc/ w/pulsed discharge is created which enables the monomer species to dissociate, leading to the formation of polymer thin films. However, it has been found that the structure and hence the properties exhibited by plasma polymerized thin films are quite different from that of their counterparts produced by other thin film preparation techniques such as electrochemical deposition or spin coating. The properties of these thin films can be tuned only if the interrelationship between the structure and other properties are understood from a fundamental point of view. So very often, a through evaluation of the various properties is a pre-requisite for tailoring the properties of the thin films for applications. It has been found that conjugation is a necessary condition for enhancing the conductivity of polymer thin films. RF technique of plasma polymerisation is an excellent tool to induce conjugation and this modifies the electrical properties too. Both oxidative and reductive doping can be employed to modify the electrical properties of the polymer thin films for various applications. This is where organic thin films based on polymers scored over inorganic thin films, where in large area devices can be fabricated with organic semiconductors which is difficult to achieve by inorganic materials. For such applications, a variety of polymers have been synthesized such as polyaniline, polythiophene, polypyrrole etc. There are newer polymers added to this family every now and then. There are many virgin areas where plasma polymers are yet to make a foray namely low-k dielectrics or as potential nonlinear optical materials such as optical limiters. There are also many materials which are not been prepared by the method of plasma polymerisation. Some of the materials which are not been dealt with are phenyl hydrazine and tea tree oil. The advantage of employing organic extracts like tea tree oil monomers as precursors for making plasma polymers is that there can be value addition to the already existing uses and possibility exists in converting them to electronic grade materials, especially semiconductors and optically active materials for photonic applications. One of the major motivations of this study is to synthesize plasma polymer thin films based on aniline, phenyl hydrazine, pyrrole, tea tree oil and eucalyptus oil by employing both rf and ac plasma polymerisation techniques. This will be carried out with the objective of growing thin films on various substrates such as glass, quartz and indium tin oxide (ITO) coated glass. There are various properties namely structural, electrical, dielectric permittivity, nonlinear optical properties which are to be evaluated to establish the relationship with the structure and the other properties. Special emphasis will be laid in evaluating the optical parameters like refractive index (n), extinction coefficient (k), the real and imaginary components of dielectric constant and the optical transition energies of the polymer thin films from the spectroscopic ellipsometric studies. Apart from evaluating these physical constants, it is also possible to predict whether a material exhibit nonlinear optical properties by ellipsometric investigations. So further studies using open aperture z-scan technique in order to evaluate the nonlinear optical properties of a few selected samples which are potential nonlinear optical materials is another objective of the present study. It will be another endeavour to offer an appropriate explanation for the nonlinear optical properties displayed by these films. Doping of plasma polymers is found to modify both the electrical conductivity and optical properties. Iodine is found to modify the properties of the polymer thin films. However insitu iodine doping is tricky and the film often looses its stability because of the escape of iodine. An appropriate insitu technique of doping will be developed to dope iodine in to the plasma polymerized thin films. Doping of polymer thin films with iodine results in improved and modified optical and electrical properties. However it requires tools like FTIR and UV-Vis-NIR spectroscopy to elucidate the structural and optical modifications imparted to the polymer films. This will be attempted here to establish the role of iodine in the modification of the properties exhibited by the films

Fractal based techniques for classification of mammograms and identification of microcalcifications

After skin cancer, breast cancer accounts for the second greatest number of cancer diagnoses in women. Currently the etiologies of breast cancer are unknown, and there is no generally accepted therapy for preventing it. Therefore, the best way to improve the prognosis for breast cancer is early detection and treatment. Computer aided detection systems (CAD) for detecting masses or micro-calcifications in mammograms have already been used and proven to be a potentially powerful tool , so the radiologists are attracted by the effectiveness of clinical application of CAD systems. Fractal geometry is well suited for describing the complex physiological structures that defy the traditional Euclidean geometry, which is based on smooth shapes. The major contribution of this research include the development of • A new fractal feature to accurately classify mammograms into normal and normal (i)With masses (benign or malignant) (ii) with microcalcifications (benign or malignant) • A novel fast fractal modeling method to identify the presence of microcalcifications by fractal modeling of mammograms and then subtracting the modeled image from the original mammogram. The performances of these methods were evaluated using different standard statistical analysis methods. The results obtained indicate that the developed methods are highly beneficial for assisting radiologists in making diagnostic decisions. The mammograms for the study were obtained from the two online databases namely, MIAS (Mammographic Image Analysis Society) and DDSM (Digital Database for Screening Mammography.

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering

Speckle noise formed as a result of the coherent nature of ultrasound imaging affects the lesion detectability. We have proposed a new weighted linear filtering approach using Local Binary Patterns (LBP) for reducing the speckle noise in ultrasound images. The new filter achieves good results in reducing the noise without affecting the image content. The performance of the proposed filter has been compared with some of the commonly used denoising filters. The proposed filter outperforms the existing filters in terms of quantitative analysis and in edge preservation. The experimental analysis is done using various ultrasound images