894 resultados para 289900 Other Information, Computing and Communication Sciences
A note on information seasonality and the disappearance of the weekend effect in the UK stock market
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The weekend effect in UK stock prices has disappeared in the 1990s. Beneath the surface however there remain systematic day-of-the-week effects only visible when returns are partitioned by the direction of the market. A systematic pattern of market-wide news arrivals into the UK stock market is discovered and found to provide an explanation for these day-of-the-week effects.
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Concern has been expressed in the professional literature - borne out by professional experience and observation - that the supply and demand relationship existing between the 13 English and Welsh Library and Information Studies (LIS) Schools (as providers of `First Professional' staff) and the Higher Education Library and Information Services (HE LIS) sector of England and Wales (as one group of employers of such staff) is unsatisfactory and needs attention. An appropriate methodology to investigate this problem was devised. A basic content analysis of Schools' curricular and recruitment material intended for public consumption was undertaken to establish an overview of the LIS initial professional education system in England and Wales, and to identify and analyse any covert messages imparted to readers. This was followed by a mix of Main Questionnaires and Semi-Structured Interviews with appropriate populations. The investigation revealed some serious areas of dissatisfaction by the HE LIS Chiefs with the role and function of the Schools. Considerable divergence of views emerged on the state of the working relationships between the two sectors and on the Schools' successes in meeting the needs of the HE LIS sector and on CPD provision. There were, however, areas of substantial and consistent agreement between the two sectors. The main implications of the findings were that those areas encompassing divergence of views were worrying and needed addressing by both sides. Possible ways forward included recommendations on improving the image of the profession purveyed by the Schools; the forming of closer and more effective inter-sectoral relationships; recognising fully the importance of `practicum' and increasing and sustaining the network of `practicum' providers.
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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT
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Objectives: To disentangle the effects of physician gender and patient-centered communication style on patients' oral engagement in depression care. Methods: Physician gender, physician race and communication style (high patient-centered (HPC) and low patient-centered (LPC)) were manipulated and presented as videotaped actors within a computer simulated medical visit to assess effects on analogue patient (AP) verbal responsiveness and care ratings. 307 APs (56% female; 70% African American) were randomly assigned to conditions and instructed to verbally respond to depression-related questions and indicate willingness to continue care. Disclosures were coded using Roter Interaction Analysis System (RIAS). Results: Both male and female APs talked more overall and conveyed more psychosocial and emotional talk to HPC gender discordant doctors (all p <.05). APs were more willing to continue treatment with gender-discordant HPC physicians (p <.05). No effects were evident in the LPC condition. Conclusions: Findings highlight a role for physician gender when considering active patient engagement in patient-centered depression care. This pattern suggests that there may be largely under-appreciated and consequential effects associated with patient expectations in regard to physician gender that these differ by patient gender. Practice implications: High patient-centeredness increases active patient engagement in depression care especially in gender discordant dyads. © 2014.
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The purpose of this work is the development of database of the distributed information measurement and control system that implements methods of optical spectroscopy for plasma physics research and atomic collisions and provides remote access to information and hardware resources within the Intranet/Internet networks. The database is based on database management system Oracle9i. Client software was realized in Java language. The software was developed using Model View Controller architecture, which separates application data from graphical presentation components and input processing logic. The following graphical presentations were implemented: measurement of radiation spectra of beam and plasma objects, excitation function for non-elastic collisions of heavy particles and analysis of data acquired in preceding experiments. The graphical clients have the following functionality of the interaction with the database: browsing information on experiments of a certain type, searching for data with various criteria, and inserting the information about preceding experiments.
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Switched mode power supplies (SMPSs) are essential components in many applications, and electromagnetic interference is an important consideration in the SMPS design. Spread spectrum based PWM strategies have been used in SMPS designs to reduce the switching harmonics. This paper proposes a novel method to integrate a communication function into spread spectrum based PWM strategy without extra hardware costs. Direct sequence spread spectrum (DSSS) and phase shift keying (PSK) data modulation are employed to the PWM of the SMPS, so that it has reduced switching harmonics and the input and output power line voltage ripples contain data. A data demodulation algorithm has been developed for receivers, and code division multiple access (CDMA) concept is employed as communication method for a system with multiple SMPSs. The proposed method has been implemented in both Buck and Boost converters. The experimental results validated the proposed DSSS based PWM strategy for both harmonic reduction and communication.
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The investigations of human mitochondrial DNA (mtDNA) have considerably contributed to human evolution and migration. The Middle East is considered to be an essential geographic area for human migrations out of Africa since it is located at the crossroads of Africa, and the rest of the world. United Arab Emirates (UAE) population inhabits the eastern part of Arabian Peninsula and was investigated in this study. Published data of 18 populations were included in the statistical analysis. The diversity indices showed (1) high genetic distance among African populations and (2) high genetic distance between African populations and non-African populations. Asian populations clustered together in the NJ tree between the African and European populations. MtDNA haplotypes database of the UAE population was generated. By incorporating UAE mtDNA dataset into the existing worldwide mtDNA database, UAE Forensic Laboratories will be able to analyze future mtDNA evidence in a more significant and consistent manner. ^
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With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.