Event-related collections, including both tweets and webpages, have valuable information, and are worth exploring in interdisciplinary research and education. Unfortunately, such data is noisy, so this variety of information has not been adequately exploited. Further, for better understanding, more knowledge hidden behind events needs to be unearthed. Regarding these collections, different societies may have different requirements in particular scenarios. Some may need relatively clean datasets for data exploration and data mining. Social researchers require preprocessing of information, so they can conduct analyses. General societies are interested in the overall descriptions of events. However, few systems, tools, or methods exist to support the flexible use of event-related collections. In this research, we propose a new, integrated system to process and analyze event-related collections at different levels (i.e., data, information, and knowledge). It also provides various services and covers the most important stages in a system pipeline, including collection development, curation, analysis, integration, and visualization. Firstly, we propose a query likelihood model with pre-query design and post-query expansion to rank a webpage corpus by query generation probability, and retrieve relevant webpages from event-related tweet collections. We further preserve webpage data into WARC files and enrich original tweets with webpages in JSON format. As an application of data management, we conduct an empirical study of the embedded URLs in tweets based on collection development and data curation techniques. Secondly, we develop TwiRole, an integrated model for 3-way user classification on Twitter, which detects brand-related, female-related, and male-related tweeters through multiple features with both machine learning (i.e., random forest classifier) and deep learning (i.e., an 18-layer ResNet) techniques. As guidance to user-centered social research at the information level, we combine TwiRole with a pre-trained recurrent neural network-based emotion detection model, and carry out tweeting pattern analyses on disaster-related collections. Finally, we propose a tweet-guided multi-document summarization (TMDS) model, which generates summaries of the event-related collections by using tweets associated with those events. The TMDS model also considers three aspects of named entities (i.e., importance, relatedness, and diversity) as well as topics, to score sentences in webpages, and then rank selected relevant sentences in proper order for summarization. The entire system is realized using many technologies, such as collection development, natural language processing, machine learning, and deep learning. For each part, comprehensive evaluations are carried out, that confirm the effectiveness and accuracy of our proposed approaches. Regarding broader impact, the outcomes proposed in our study can be easily adopted or extended for further event analyses and service development. / Doctor of Philosophy / Event-related collections, including both tweets and webpages, have valuable information. They are worth exploring in interdisciplinary research and education. Unfortunately, such data is noisy. Many tweets and webpages are not relevant to the events. This leads to difficulties during data analysis of the datasets, as well as explanation of the results. Further, for better understanding, more knowledge hidden behind events needs to be unearthed. Regarding these collections, different groups of people may have different requirements. Some may need relatively clean datasets for data exploration. Some require preprocessing of information, so they can conduct analyses, e.g., based on tweeter type or content topic. General societies are interested in the overall descriptions of events. However, few systems, tools, or methods exist to support the flexible use of event-related collections. Accordingly, we describe our new framework and integrated system to process and analyze event-related collections. It provides varied services and covers the most important stages in a system pipeline. It has sub-systems to clean, manage, analyze, integrate, and visualize event-related collections. It takes an event-related tweet collection as input and generates an event-related webpage corpus by leveraging Wikipedia and the URLs embedded in tweets. It also combines and enriches original tweets with webpages. As an application of data management, we conduct an empirical study of tweets and their embedded URLs. We developed TwiRole for 3-way user classification on Twitter. It detects brand-related, female-related, and male-related tweeters through their profiles, tweets, and images. To aid user-centered social research, we combine TwiRole with an existing emotion detection tool, and carry out tweeting pattern analyses on disaster-related collections. Finally, we propose a tweet-guided multi-document summarization (TMDS) model and service, which generates summaries of the event-related collections by using tweets associated with those events. It extracts important sentences across different topics from webpages, and organizes them in proper order. The entire system is realized using many technologies, such as collection development, natural language processing, machine learning, and deep learning. For each part, comprehensive evaluations help confirm the effectiveness and accuracy of our proposed approaches. Regarding broader impact, our methods and system can be easily adopted or extended for further event analyses and service development.

No / Accurate web log mining results and efficient online navigational pattern prediction are undeniably crucial for tuning up websites and consequently helping in visitors' retention. Like any other data mining task, web log mining starts with data cleaning and preparation and it ends up discovering some hidden knowledge which cannot be extracted using conventional methods. In order for this process to yield good results it has to rely on some good quality input data. Therefore, more focus in this process should be on data cleaning and pre-processing. On the other hand, one of the challenges facing online prediction is scalability. As a result any improvement in the efficiency of online prediction solutions is more than necessary. As a response to the aforementioned concerns we are proposing an enhancement to the web log mining process and to the online navigational pattern prediction. Our contribution contains three different components. First, we are proposing a refined time-out based heuristic for session identification. Second, we are suggesting the usage of a specific density based algorithm for navigational pattern discovery. Finally, a new approach for efficient online prediction is also suggested. The conducted experiments demonstrate the applicability and effectiveness of the proposed approach. (C) 2013 Elsevier B.V. All rights reserved.

La presente tesis doctoral aborda los usos de se, su tratamiento en los diccionarios románicos actuales y su representación en un diccionario de aprendizaje de español como lengua extranjera. Su objetivo principal es proponer un modelo de representación para verbos que muestren estos usos. Para ello, se atenderán los siguientes aspectos:  El estado de la cuestión tanto en los estudios de gramática (capítulo 2) como en los lexicográficos (capítulo 3).  La representación de los usos pronominales en los diccionarios románicos actuales, en concreto los de aprendizaje de segunda lengua (capítulo 4).  El análisis sistemático de los usos de se en el corpus, enfocado desde la perspectiva de la Theory of Norms and Exploitations y el Corpus Pattern Analysis de Hanks (2004) (capítulos 5 y 6).  La elaboración de un modelo de entrada lexicográfica verbal que contenga usos con se para un diccionario de ELE (capítulo 7). Los resultados de la tesis son principalmente la elaboración de una base de datos sobre verbos con usos pronominales (capítulo 6, SCPA) y de un prototipo de 20 entradas lexicográficas de los mismos verbos analizados con CPA (capítulo 7). / The present Ph.D. thesis studied the uses of the Spanish particle se, its treatment by current romance dictionaries and its representation in a dictionary for learners of Spanish as a foreign language. The main objective is to propose a model for the representation of the verbs that present the use of se. For this, the following aspects will be analysed:  The review of related work in grammar studies (chapter 2) as well as lexicography (chapter 3).  The representation of pronominal uses in the current romance dictionaries, particularly in those for learners of Spanish as a second language (chapter 4).  The systematic analysis of se in corpora from the perspective of Hanks’ (2004) theory of Norms and Exploitations and Corpus Patterns Analysis (chapter 5 and 6).  The elaboration of a model of a verbal lexical entry for a dictionary of Spanish as a second language containing uses of se (chapter 7). The results of the thesis are mainly the elaboration of a database on Spanish pronominal verbs (chapter 6, Spanish CPA) and of a prototype of 20 lexical entries with the same verbs analysed with CPA (chapter 7).

Violent crimes involving bloodshed may result in the formation of a number of blood drops that move through air and impact onto a surface producing a bloodstain pattern. Bloodstain Pattern Analysis (BPA), the analysis of the position, distribution, size and morphology of the stains within the pattern present at a crime scene, may provide information about the events that gave rise to the bloodshed. The location of blood origin, i.e. victim’s position at the moment of wounding and (or) wound location, determination is of major interest to BPA. This study investigated the dynamics of formation and flight of blood drops commonly found at a crime scene (so-called passive, cast-off, impact and gunshot drops) with the aim to facilitate blood origin determination. Features of blood drop formation at passive dripping with correlation to dripping surface characteristics were studied experimentally. A numerical scheme for accurate blood drop flight characteristics modelling, including oscillations, deformation and disintegration, was developed and validated against a number of analytical and experimental cases with special attention to the passive blood drop oscillations and ultimate deformation at terminal velocity, cast-off and impact blood drop deformation and breakup features. This provided an efficient and accurate method for typical blood drop flight reconstruction from the blood origin to impact as well as from the bloodstain location to the possible blood origin. Factors affecting blood drop trajectory and blood origin estimation were studied using the developed scheme.

The purpose of this study was to research the therapeutic outcomes achieved by a five year-old boy with Asperger Syndrome (AS), by means of non-directive processes of child centred play therapy (CCP) and sand tray play therapy (STP). In this investigative-descriptive qualitative research design, a saturated, holistic, intrinsic single case study was used as research method. The therapeutic process, events and outcomes of a unique single case within the context of AS, non-directive play therapy and the interactional-pattern analysis (IPA), are described. This study was motivated by the fact that the researcher disposed of data for a unique single case study that could contribute meaningfully to the need for a research database that describes effective therapeutic interventions and outcomes with children with AS. From the perspective of Rogerian person-centred theory (RPT), the literature study focused on an integrated discussion of AS, CCP and STP by means of 17 interpersonal variables of the interactional-pattern analysis (IPA). The following data sources was investigated: interviews with parents and teachers; CCP-sessions of J recorded on video; photos of some of J’s STP-sessions and the therapists’ process notes. Triangulation was used to evaluate the various categories of therapeutic outcomes from different viewpoints and to give meaning to them. The conclusions indicated that this boy with AS had used the non-directive processes of CCP and STP to achieve various therapeutic outcomes in the areas of: imaginary play; dramatic play; social interaction with the therapist, parents, family, teachers, his peer group and with strangers; traumatic experiences during visits to the doctor and bath times; identification, expressing and regulating emotions; and minimising acting out behaviour. Therapeutic outcomes have been demonstrated in 8 IPA-variables, namely: empathy, defining of relationships, potential to evoke acceptance or rejection, sincere interest and congruent conduct, control, emotional distance, problem solving and aspects relating to the presenting problem. The conclusion was reached that the conduct of the boy with AS as well as his mother and the therapist, played a mutual role in achieving his therapeutic outcomes within the 17 IPA-variables. The unstructured process of the non-directive play (CCP and STP) was utilised by a young child with AS to achieve therapeutic outcomes that relate to his everyday existence. A final conclusion is that involving the boy’s mother in his therapy and utilising an adapted Filial play program, enabled the mother to make emotional contact with her son and to diminish conflict between them. Guidelines for therapists are suggested with regard to non-directive responding in therapeutic contexts as found in this study. Furthermore, the contribution of this research to Psychology as science and discipline, is presented. Limitations of this study are indicated and recommendations for further research are made. / Thesis (Ph.D. (Psigologie))--North-West University, Vaal Triangle Campus, 2013

<p>This&nbsp / thesis&nbsp / examines&nbsp / the&nbsp / changes&nbsp / that&nbsp / have&nbsp / occurred&nbsp / within&nbsp / West-Coast Renosterveld within&nbsp / the&nbsp / last 350 years, and assesses&nbsp / the viability of&nbsp / the&nbsp / remaining fragments.</p>

Multiphoton laser scanning microscopy (MPLSM) is an advanced fluorescence imaging technology which can produce a less noisy microscope image and minimize the damage in living tissue. The MPLSM image in this research is the dehydroergosterol (DHE, a fluorescent sterol which closely mimics those of cholesterol in lipoproteins and membranes) on living cell's plasma membrane area. The objective is to use a statistical image analysis method to describe how cholesterol is distributed on a living cell's membrane. Statistical image analysis methods applied in this research include image segmentation/classification and spatial analysis. In image segmentation analysis, we design a supervised learning method by using smoothing technique with rank statistics. This approach is especially useful in a situation where we have only very limited information of classes we want to segment. We also apply unsupervised leaning methods on the image data. In image data spatial analysis, we explore the spatial correlation of segmented data by a Monte Carlo test. Our research shows that the distributions of DHE exhibit a spatially aggregated pattern. We fit two aggregated point pattern models, an area-interaction process model and a Poisson cluster process model, to the data. For the area interaction process model, we design algorithms for maximum pseudo-likelihood estimator and Monte Carlo maximum likelihood estimator under lattice data setting. For the Poisson Cluster process parameter estimation, the method for implicit statistical model parameter estimate is used. A group of simulation studies shows that the Monte Carlo maximum estimation method produces consistent parameter estimates. The goodness-of-fit tests show that we cannot reject both models. We propose to use the area interaction process model in further research.

<p>This&nbsp / thesis&nbsp / examines&nbsp / the&nbsp / changes&nbsp / that&nbsp / have&nbsp / occurred&nbsp / within&nbsp / West-Coast Renosterveld within&nbsp / the&nbsp / last 350 years, and assesses&nbsp / the viability of&nbsp / the&nbsp / remaining fragments.</p>

The purpose of this study was to research the therapeutic outcomes achieved by a five year-old boy with Asperger Syndrome (AS), by means of non-directive processes of child centred play therapy (CCP) and sand tray play therapy (STP). In this investigative-descriptive qualitative research design, a saturated, holistic, intrinsic single case study was used as research method. The therapeutic process, events and outcomes of a unique single case within the context of AS, non-directive play therapy and the interactional-pattern analysis (IPA), are described. This study was motivated by the fact that the researcher disposed of data for a unique single case study that could contribute meaningfully to the need for a research database that describes effective therapeutic interventions and outcomes with children with AS. From the perspective of Rogerian person-centred theory (RPT), the literature study focused on an integrated discussion of AS, CCP and STP by means of 17 interpersonal variables of the interactional-pattern analysis (IPA). The following data sources was investigated: interviews with parents and teachers; CCP-sessions of J recorded on video; photos of some of J’s STP-sessions and the therapists’ process notes. Triangulation was used to evaluate the various categories of therapeutic outcomes from different viewpoints and to give meaning to them. The conclusions indicated that this boy with AS had used the non-directive processes of CCP and STP to achieve various therapeutic outcomes in the areas of: imaginary play; dramatic play; social interaction with the therapist, parents, family, teachers, his peer group and with strangers; traumatic experiences during visits to the doctor and bath times; identification, expressing and regulating emotions; and minimising acting out behaviour. Therapeutic outcomes have been demonstrated in 8 IPA-variables, namely: empathy, defining of relationships, potential to evoke acceptance or rejection, sincere interest and congruent conduct, control, emotional distance, problem solving and aspects relating to the presenting problem. The conclusion was reached that the conduct of the boy with AS as well as his mother and the therapist, played a mutual role in achieving his therapeutic outcomes within the 17 IPA-variables. The unstructured process of the non-directive play (CCP and STP) was utilised by a young child with AS to achieve therapeutic outcomes that relate to his everyday existence. A final conclusion is that involving the boy’s mother in his therapy and utilising an adapted Filial play program, enabled the mother to make emotional contact with her son and to diminish conflict between them. Guidelines for therapists are suggested with regard to non-directive responding in therapeutic contexts as found in this study. Furthermore, the contribution of this research to Psychology as science and discipline, is presented. Limitations of this study are indicated and recommendations for further research are made. / Thesis (Ph.D. (Psigologie))--North-West University, Vaal Triangle Campus, 2013

The definition of optimal selection criteria for maximizing the response rate to Cardiac Resynchronization Therapy (CRT) is still an issue under active debate. Recent clinical approaches propose a classification of patients into classes of mechanisms that could lead to heart failure and study their response to the therapy. In this line of research, the computation of a metric between the motion and deformation patterns of a given subject and well identified classes of CRT responders is considered in this thesis, as the basis of a new strategy to compute patient selection indexes. The thesis proposes first an improved design for the construction of statistical atlases of myocardial motion and deformation, and applies it to the characterization of populations of patients involved in CRT. The added-value of our approach is highlighted in a clinical study, applying the methodology to a large population of patients with a given pattern of dyssynchrony (septal flash) and understanding the link between its correction and CRT response. Finally, we propose a method to extend the analysis to the comparison of individuals to reference populations, either healthy or pathological, using manifold learning techniques to model a disease as progressive deviations from normality along a manifold structure, and demonstrate the potential of our method for inter-subject comparison in CRT patients. / La definición de un criterio óptimo para mejorar la respuesta a la Terapia de Resincronización Cardíaca (TRC) sigue siendo un debate abierto. Estudio clínicos recientemente publicados proponen clasificar pacientes según diversos mecanismos patofisiológicos que pueden inducir insuficiencia cardíaca y estudian su respuesta a la terapia. Siguiendo esta línea de investigación, esta tesis considera el cálculo de una distancia entre los patrones de movimiento y deformación de un individuo y las clases de respondedores a la TRC, siendo la base de una nueva estrategia para calcular índices para seleccionar pacientes. Esta tesis presenta primero un método para construir un atlas estadístico de movimiento y deformación miocárdica, y su aplicación posterior a la caracterización de poblaciones de potenciales candidatos a la TRC. El valor añadido de nuestro método se enfatiza en un estudio clínico, en el cual se aplica la metodología a una gran población de pacientes con un patrón específico de disincronía cardíaca (llamado septal flash), y se relaciona su corrección y la respuesta a la TRC. Finalmente, se extiende el método para comparar individuos a una población de referencia, sana o patológica, usando técnicas de manifold learning para representar una patología como una desviación progresiva de la normalidad, con una estructura no lineal específica, y se demuestra el potencial de nuestro método para comparar entre sí candidatos a la TRC.