Linked Data based Health Information Representation, Visualization and Retrieval System on the Semantic Web

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Proactive ontology-based content provision in the context of e-learning

Magdeburg, Univ., Fak. für Informatik, Diss., 2008

The role of auditory cortices in the retrieval of single-trial auditory-visual object memories.

Single-trial encounters with multisensory stimuli affect both memory performance and early-latency brain responses to visual stimuli. Whether and how auditory cortices support memory processes based on single-trial multisensory learning is unknown and may differ qualitatively and quantitatively from comparable processes within visual cortices due to purported differences in memory capacities across the senses. We recorded event-related potentials (ERPs) as healthy adults (n = 18) performed a continuous recognition task in the auditory modality, discriminating initial (new) from repeated (old) sounds of environmental objects. Initial presentations were either unisensory or multisensory; the latter entailed synchronous presentation of a semantically congruent or a meaningless image. Repeated presentations were exclusively auditory, thus differing only according to the context in which the sound was initially encountered. Discrimination abilities (indexed by d') were increased for repeated sounds that were initially encountered with a semantically congruent image versus sounds initially encountered with either a meaningless or no image. Analyses of ERPs within an electrical neuroimaging framework revealed that early stages of auditory processing of repeated sounds were affected by prior single-trial multisensory contexts. These effects followed from significantly reduced activity within a distributed network, including the right superior temporal cortex, suggesting an inverse relationship between brain activity and behavioural outcome on this task. The present findings demonstrate how auditory cortices contribute to long-term effects of multisensory experiences on auditory object discrimination. We propose a new framework for the efficacy of multisensory processes to impact both current multisensory stimulus processing and unisensory discrimination abilities later in time.

The Role and Measurement of Social Capital in New Technology-Based Start-up Context

Tämän Pro gradu-tutkielman tavoitteena olirakentaa esiymmärrys sosiaalisen pääoman roolista ja mittaamisesta uuden teknologian start-up yrityksissä. Pääasiallisena tarkoituksena tässä tutkimuksessa olilöytää sosiaalisen pääoman ja start-up yrityksen tuloksellisuuden välille yhdistävä tekijä. Tutkimuksen empiirinen aineisto kerättiin pääasiallisesti kuuden OKO Venture Capitalin sijoitusportfolioon sisältyvien case-yritysten kvalitatiivisten teemahaastatteluiden sekä kvantitatiivisten kyselylomakkeiden avulla. Kvalitatiivisten haastatteluiden tulosten perusteella sosiaalisen pääoman ja tuloksellisuuden välille löytyi yhdistävä tekijä, jota käytettiin myöhemmin hyväksi kvantitatiivisessa kyselylomakkeessa. Tämän tutkielman tulokset osoittivat, että startegisen päätöksenteon kautta sosiaalinen pääoma vaikuttaa osittain start-up yritysten tuloksellisuuteen. Manageriaalisesti tärkempi löydös tässä tutkimuksessa oli kuitenkin se, että sosiaalista pääomaa voidaan käyttää hyväksi ennustettaessa uuden teknologian start-up yritysten tulevaisuuden kassavirtoja.

Business Model Considerations for Privacy Protection in a Mobile Location Based Context

In this paper we discuss the main privacy issues around mobile business models and we envision new solutions having privacy protection as a main value proposition. We construct a framework to help analyze the situation and assume that a third party is necessary to warrant transactions between mobile users and m-commerce providers. We then use the business model canvas to describe a generic business model pattern for privacy third party services. This pattern is then illustrated in two different variations of a privacy business model, which we call privacy broker and privacy management software. We conclude by giving examples for each business model and by suggesting further directions of investigation

Moral disengagement: Towards a context-general category-based measure of the concept

Bandura (1986) developed the concept of moral disengagement to explain how individuals can engage in detrimental behavior while experiencing low levels of negative feelings such as guilt-feelings. Most of the research conducted on moral disengagement investigated this concept as a global concept (e.g., Bandura, Barbaranelli, Caprara, & Pastorelli, 1996; Moore, Detert, Klebe Treviño, Baker, & Mayer, 2012) while Bandura (1986, 1990) initially developed eight distinct mechanisms of moral disengagement grouped into four categories representing the various means through which moral disengagement can operate. In our work, we propose to develop measures of this concept based on its categories, namely rightness of actions, rejection of personal responsibility, distortion of negative consequences, and negative perception of the victims, and which is not specific a particular area of research. Through our measures, we aim at better understanding the cognitive process leading individuals to behave unethically by investigating which category plays a role in explaining unethical behavior depending on the situations in which individuals are. To this purpose, we conducted five studies to develop the measures and to test its predictive validity. Particularly, we assessed the ability of the newly developed measures to predict two types of unethical behaviors, i.e. discriminatory behavior and cheating behavior. Confirmatory Factor analyses demonstrated a good fit of the model and findings generally supported our predictions.

Assessing functional relations in single-case designs: Quantitative proposals in the context of the evidence-based movement

In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications.

Practical Framework for Monitoring the Performance of Agile IT Projects in an Output-Based Outsourcing Context

Over the past decade, organizations worldwide have begun to widely adopt agile software development practices, which offer greater flexibility to frequently changing business requirements, better cost effectiveness due to minimization of waste, faster time-to-market, and closer collaboration between business and IT. At the same time, IT services are continuing to be increasingly outsourced to third parties providing the organizations with the ability to focus on their core capabilities as well as to take advantage of better demand scalability, access to specialized skills, and cost benefits. An output-based pricing model, where the customers pay directly for the functionality that was delivered rather than the effort spent, is quickly becoming a new trend in IT outsourcing allowing to transfer the risk away from the customer while at the same time offering much better incentives for the supplier to optimize processes and improve efficiency, and consequently producing a true win-win outcome. Despite the widespread adoption of both agile practices and output-based outsourcing, there is little formal research available on how the two can be effectively combined in practice. Moreover, little practical guidance exists on how companies can measure the performance of their agile projects, which are being delivered in an output-based outsourced environment. This research attempted to shed light on this issue by developing a practical project monitoring framework which may be readily applied by organizations to monitor the performance of agile projects in an output-based outsourcing context, thus taking advantage of the combined benefits of such an arrangement Modified from action research approach, this research was divided into two cycles, each consisting of the Identification, Analysis, Verification, and Conclusion phases. During Cycle 1, a list of six Key Performance Indicators (KPIs) was proposed and accepted by the professionals in the studied multinational organization, which formed the core of the proposed framework and answered the first research sub-question of what needs to be measured. In Cycle 2, a more in-depth analysis was provided for each of the suggested Key Performance Indicators including the techniques for capturing, calculating, and evaluating the information provided by each KPI. In the course of Cycle 2, the second research sub-question was answered, clarifying how the data for each KPI needed to be measured, interpreted, and acted upon. Consequently, after two incremental research cycles, the primary research question was answered describing the practical framework that may be used for monitoring the performance of agile IT projects delivered in an output-based outsourcing context. This framework was evaluated by the professionals within the context of the studied organization and received positive feedback across all four evaluation criteria set forth in this research, including the low overhead of data collection, high value of provided information, ease of understandability of the metric dashboard, and high generalizability of the proposed framework.

Relating Dependent Terms in Information Retrieval

Les moteurs de recherche font partie de notre vie quotidienne. Actuellement, plus d’un tiers de la population mondiale utilise l’Internet. Les moteurs de recherche leur permettent de trouver rapidement les informations ou les produits qu'ils veulent. La recherche d'information (IR) est le fondement de moteurs de recherche modernes. Les approches traditionnelles de recherche d'information supposent que les termes d'indexation sont indépendants. Pourtant, les termes qui apparaissent dans le même contexte sont souvent dépendants. L’absence de la prise en compte de ces dépendances est une des causes de l’introduction de bruit dans le résultat (résultat non pertinents). Certaines études ont proposé d’intégrer certains types de dépendance, tels que la proximité, la cooccurrence, la contiguïté et de la dépendance grammaticale. Dans la plupart des cas, les modèles de dépendance sont construits séparément et ensuite combinés avec le modèle traditionnel de mots avec une importance constante. Par conséquent, ils ne peuvent pas capturer correctement la dépendance variable et la force de dépendance. Par exemple, la dépendance entre les mots adjacents "Black Friday" est plus importante que celle entre les mots "road constructions". Dans cette thèse, nous étudions différentes approches pour capturer les relations des termes et de leurs forces de dépendance. Nous avons proposé des méthodes suivantes: ─ Nous réexaminons l'approche de combinaison en utilisant différentes unités d'indexation pour la RI monolingue en chinois et la RI translinguistique entre anglais et chinois. En plus d’utiliser des mots, nous étudions la possibilité d'utiliser bi-gramme et uni-gramme comme unité de traduction pour le chinois. Plusieurs modèles de traduction sont construits pour traduire des mots anglais en uni-grammes, bi-grammes et mots chinois avec un corpus parallèle. Une requête en anglais est ensuite traduite de plusieurs façons, et un score classement est produit avec chaque traduction. Le score final de classement combine tous ces types de traduction. Nous considérons la dépendance entre les termes en utilisant la théorie d’évidence de Dempster-Shafer. Une occurrence d'un fragment de texte (de plusieurs mots) dans un document est considérée comme représentant l'ensemble de tous les termes constituants. La probabilité est assignée à un tel ensemble de termes plutôt qu’a chaque terme individuel. Au moment d’évaluation de requête, cette probabilité est redistribuée aux termes de la requête si ces derniers sont différents. Cette approche nous permet d'intégrer les relations de dépendance entre les termes. Nous proposons un modèle discriminant pour intégrer les différentes types de dépendance selon leur force et leur utilité pour la RI. Notamment, nous considérons la dépendance de contiguïté et de cooccurrence à de différentes distances, c’est-à-dire les bi-grammes et les paires de termes dans une fenêtre de 2, 4, 8 et 16 mots. Le poids d’un bi-gramme ou d’une paire de termes dépendants est déterminé selon un ensemble des caractères, en utilisant la régression SVM. Toutes les méthodes proposées sont évaluées sur plusieurs collections en anglais et/ou chinois, et les résultats expérimentaux montrent que ces méthodes produisent des améliorations substantielles sur l'état de l'art.

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

Intelligent Agent-based Multilingual Information Retrieval System

The goal of this work is to develop an Open Agent Architecture for Multilingual information retrieval from Relational Database. The query for information retrieval can be given in plain Hindi or Malayalam; two prominent regional languages of India. The system supports distributed processing of user requests through collaborating agents. Natural language processing techniques are used for meaning extraction from the plain query and information is given back to the user in his/ her native language. The system architecture is designed in a structured way so that it can be adapted to other regional languages of India

Content Based Image Retrieval System for Malayalam Handwritten Characters

Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance

Content-Based Image Retrieval of Axial Brain Slices Using a Novel LBP with a Ternary Encoding

Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images

Content Based Image Retrieval of Brain MR Images across Different Classes

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users’ feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved