Vertical handover based adaptions for multimedia applications in pervasive systems

This paper proposes an architecture for pervasive computing which utilizes context information to provide adaptations based on vertical handovers (handovers between heterogeneous networks) while supporting application Quality of Service (QoS). The future of mobile computing will see an increase in ubiquitous network connectivity which allows users to roam freely between heterogeneous networks. One of the requirements for pervasive computing is to adapt computing applications or their environment if current applications can no longer be provided with the requested QoS. One of possible adaptations is a vertical handover to a different network. Vertical handover operations include changing network interfaces on a single device or changes between different devices. Such handovers should be performed with minimal user distraction and minimal violation of communication QoS for user applications. The solution utilises context information regarding user devices, user location, application requirements, and network environment. The paper shows how vertical handover adaptations are incorporated into the whole infrastructure of a pervasive system

Vertical handovers as adaption methods in pervasive systems

Pervasive systems need to be context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover (handover between heterogeneous networks) is one of possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining continuity of their applications. This paper proposes a vertical handover approach suitable for multimedia applications in pervasive systems. It describes the adaptability decision making process which uses vertical handovers to support users mobility and provision of QoS suitable for users’ applications. The process evaluates context information regarding user devices, User location, network environment, and user perceived QoS of applications.

Language against the odds, or rather not:the weak central coherence hypothesis and language

EV is a child with a talent for learning language combined with Asperger syndrome. EV’s talent is evident in the unusual circumstances of her acquisition of both her first (Bulgarian) and second (German) languages and the unique patterns of both receptive and expressive language (in both the L1 and L2), in which she shows subtle dissociations in competence and performance consistent with an uneven cognitive profile of skills and abilities. We argue that this case provides support for theories of language learning and usage that require more general underlying cognitive mechanisms and skills. One such account, the Weak Central Coherence (WCC) hypothesis of autism, provides a plausible framework for the interpretation of the simultaneous co-occurrence of EV’s particular pattern of cognitive strengths and weaknesses. Furthermore, we show that specific features of the uneven cognitive profile of Asperger syndrome can help explain the observed language talent displayed by EV. Thus, rather than demonstrating a case where language learning takes place despite the presence of deficits, EV’s case illustrates how a pattern of strengths within this profile can specifically promote language learning.

The clinical utility of the middle latency and 40Hz auditory evoked potentials in audiological electrodiagnosis

The two elcctrophysiological tests currently favoured in the clinical measurement of hearing threshold arc the brainstorm evoked potential (BAEP) and the slow vertex response (SVR). However, both tests possess disadvantages. The BAEP is the test of choice in younger patients as it is stable at all levels of arousal, but little information has been obtained to date at a range of frequencies. The SVR is frequency specific but is unreliable in certain adult subjects and is unstable during sleep or in young children. These deficiencies have prompted research into a third group of potentials, the middle latency response (MLR) and the 40HZ responses. This research has compared the SVR and 40HZ response in waking adults and reports that the 40HZ test can provide a viable alternative to the SVR provided that a high degree of subject relaxation is ensured. A second study examined the morphology of the MLR and 40HZ during sleep. This work suggested that these potentials arc markedly different during sleep and that methodological factors have been responsible for masking these changes in previous studies. The clinical possibilities of tone pip BAEPs were then examined as these components were proved to be the only stable responses present in sleep. It was found that threshold estimates to 5OOHz, lOOOHz and 4000Hz stimuli could be made to within 15dBSL in most cases. A final study looked more closely at methods of obtaining frequency specific information in sleeping subjects. Threshold estimates were made using established BAEP parameters and this was compared to a 40HZ procedure which recorded a series of BAEPs over a 100msec. time sweep. Results indicated that the 40mHz procedure was superior to existing techniques in estimating threshold to low frequency stimuli. This research has confirmed a role for the MLR and 40Hz response as alternative measures of hearing capability in waking subjects and proposes that the 40Hz technique is useful in measuring frequency specific thresholds although the responses recorded derive primarily from the brainstem.

A Semantic-Oriented Architecture of a Functional Module for Personalized and Adaptive Access to the Knowledge in a Multimedia Digital Library

This article presents the principal results of the doctoral thesis “Semantic-oriented Architecture and Models for Personalized and Adaptive Access to the Knowledge in Multimedia Digital Library” by Desislava Ivanova Paneva-Marinova (Institute of Mathematics and Informatics), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 27 October, 2008.

Analysis and Optimization of Synthetic Aperture Ultrasound Imaging Using the Effective Aperture Approach

An effective aperture approach is used as a tool for analysis and parameter optimization of mostly known ultrasound imaging systems - phased array systems, compounding systems and synthetic aperture imaging systems. Both characteristics of an imaging system, the effective aperture function and the corresponding two-way radiation pattern, provide information about two of the most important parameters of images produced by an ultrasound system - lateral resolution and contrast. Therefore, in the design, optimization of the effective aperture function leads to optimal choice of such parameters of an imaging systems that influence on lateral resolution and contrast of images produced by this imaging system. It is shown that the effective aperture approach can be used for optimization of a sparse synthetic transmit aperture (STA) imaging system. A new two-stage algorithm is proposed for optimization of both the positions of the transmitted elements and the weights of the receive elements. The proposed system employs a 64-element array with only four active elements used during transmit. The numerical results show that Hamming apodization gives the best compromise between the contrast of images and the lateral resolution.

Personal Work Space and Content Analysis Functionality in a Cultural Heritage Digital Library

The paper presents a different vision for personalization of the user’s stay in a cultural heritage digital library that models services for personalized content marking, commenting and analyzing that doesn’t require strict user profile, but aims at adjusting the user’s individual needs. The solution is borrowed from real work and studying of traditional written content sources (incl. books, manuals), where the user mainly performs activities such as underlining the important parts of the content, writing notes and inferences, selecting and marking zones of their interest in pictures, etc. In the paper a special attention is paid to the ability to execute learning analysis allowing different ways for the user to experience the digital library content with more creative settings.

An Algorithm to Mine Normalized Weighted Sequential Patterns Using a Prefix-projected Database

Sequential pattern mining is an important subject in data mining with broad applications in many different areas. However, previous sequential mining algorithms mostly aimed to calculate the number of occurrences (the support) without regard to the degree of importance of different data items. In this paper, we propose to explore the search space of subsequences with normalized weights. We are not only interested in the number of occurrences of the sequences (supports of sequences), but also concerned about importance of sequences (weights). When generating subsequence candidates we use both the support and the weight of the candidates while maintaining the downward closure property of these patterns which allows to accelerate the process of candidate generation.

Three essays on the interrelationships among financial restatements, corporate governance, market microstructure and the firm's rate of return

The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature did not differentiate between single and multiple restatements announcements. This research investigated the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm’s rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examined the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigated how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results supported the non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examined the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examined the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supported the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examined the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis showed that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

A multimodal and adaptive real-time human -computer interface for peoples with severe motor disability

This dissertation introduces the design of a multimodal, adaptive real-time assistive system as an alternate human computer interface that can be used by individuals with severe motor disabilities. The proposed design is based on the integration of a remote eye-gaze tracking system, voice recognition software, and a virtual keyboard. The methodology relies on a user profile that customizes eye gaze tracking using neural networks. The user profiling feature facilitates the notion of universal access to computing resources for a wide range of applications such as web browsing, email, word processing and editing. ^ The study is significant in terms of the integration of key algorithms to yield an adaptable and multimodal interface. The contributions of this dissertation stem from the following accomplishments: (a) establishment of the data transport mechanism between the eye-gaze system and the host computer yielding to a significantly low failure rate of 0.9%; (b) accurate translation of eye data into cursor movement through congregate steps which conclude with calibrated cursor coordinates using an improved conversion function; resulting in an average reduction of 70% of the disparity between the point of gaze and the actual position of the mouse cursor, compared with initial findings; (c) use of both a moving average and a trained neural network in order to minimize the jitter of the mouse cursor, which yield an average jittering reduction of 35%; (d) introduction of a new mathematical methodology to measure the degree of jittering of the mouse trajectory; (e) embedding an onscreen keyboard to facilitate text entry, and a graphical interface that is used to generate user profiles for system adaptability. ^ The adaptability nature of the interface is achieved through the establishment of user profiles, which may contain the jittering and voice characteristics of a particular user as well as a customized list of the most commonly used words ordered according to the user's preferences: in alphabetical or statistical order. This allows the system to successfully provide the capability of interacting with a computer. Every time any of the sub-system is retrained, the accuracy of the interface response improves even more. ^

Three Essays on the Interrelationships Among Financial Restatements, Corporate Governance, Market Microstructure and the Firm's Rate of Return

The increase in the number of financial restatements in recent years has resulted in a significant decrease in the amount of market capitalization for restated companies. Prior literature does not differentiate between single and multiple restatements announcements. This research investigates the inter-relationships among multiple financial restatements, corporate governance, market microstructure and the firm's rate of return in the form of three essays by differentiating between single and multiple restatement announcement companies. First essay examines the stock performance of companies announcing the financial restatement multiple times. The postulation is that prior research overestimates the abnormal return by not separating single restatement companies from multiple restatement companies. This study investigates how market penalizes the companies that announce restatement more than once. Differentiating the restatement announcement data based on number of restatement announcements, the results support for non persistence hypothesis that the market has no memory and negative abnormal returns obtained after each of the restatement announcements are completely random. Second essay examines the multiple restatement announcements and its perceived resultant information asymmetry around the announcement day. This study examines the pattern of information asymmetry for these announcements in terms of whether the bid-ask spread widens around the announcement day. The empirical analysis supports the hypotheses that the spread does widen not only around the first restatement announcement day but around every subsequent announcement days as well. The third essay empirically examines the financial and corporate governance characteristics of single and multiple restatement announcements companies. The analysis shows that corporate governance variables influence the occurrence of multiple restatement announcements and can distinguish multiple restatements announcement companies from single restatement announcement companies.

Different domains in abstract concepts

This study is a first attempt to unravel the almost unexplored domain of abstract conceptual knowledge. Four kinds of abstract concepts (nominal kinds, states of the self, cognitive processes, and emotion concepts) were investigated in two experiments. Emotion concepts displayed a specific pattern in both concreteness/abstractness and imagery ratings (cf. Altarriba et al., 1999), as did the other considered domains of abstract knowledge (Experiment 1). In Experiment 2 we highlighted the specific pattern of information (taxonomic, thematic, attributive, etc) these different abstract domains elicited in a definition production task.

Assisting End-users in Filling Out Web Services

With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.

O perfil sociodemográfico de pacientes em pós-operatório imediato de prostatectomia

Identificar o perfil sociodemográfico de pacientes submetidos à prostatectomia. Método: estudo quantitativo, transversal e descritivo, realizado na clínica cirúrgica de um Hospital Universitário na cidade de Natal/RN/Brasil, com 50 indivíduos em pós-operatório imediato de prostatectomia. A coleta de dados deu-se com um roteiro de anamnese e exame físico. Para a análise estatística dos dados foi utilizado o Programa Statistical Package for the Social Sciences, versão 16.0. O projeto de pesquisa foi aprovado pelo Comitê de Ética da Universidade Federal do Rio Grande do Norte, protocolo nº 130/10 CEP/UFRN. Resultados: os homens entrevistados tinham idade média de 67,78 anos, 80% tinham companheiros, com número de filhos variando de zero a quatro (56%). Conclusão: o conhecimento do perfil sociodemográfico dos pacientes prostatectomizados proporciona um direcionamento das ações de enfermagem frente à realidade de vida dessa clientela, uma vez que os pacientes estudados apresentaram perfil similar ao observado em outras cidades brasileiras