937 resultados para INFORMATION AND COMPUTING SCIENCES
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Introduction of technologies in the workplace have led to a dramatic change. These changes have come with an increased capacity to gather data about one’s working performance (i.e. productivity), as well as the capacity to track one’s personal responses (i.e. emotional, physiological, etc.) to this changing workplace environment. This movement of self-monitoring or self-sensing using diverse types of wearable sensors combined with the use of computing has been identified as the Quantified-Self. Miniaturization of sensors, reduction in cost and a non-stop increase in the computer power capacity has led to a panacea of wearables and sensors to track and analyze all types of information. Utilized in the personal sphere to track information, a looming question remains, should employers use the information from the Quantified-Self to track their employees’ performance or well-being in the workplace and will this benefit employees? The aim of the present work is to layout the implications and challenges associated with the use of Quantified-Self information in the workplace. The Quantified-Self movement has enabled people to understand their personal life better by tracking multiple information and signals; such an approach could allow companies to gather knowledge on what drives productivity for their business and/or well-being of their employees. A discussion about the implications of this approach will cover 1) Monitoring health and well-being, 2) Oversight and safety, and 3) Mentoring and training. Challenges will address the question of 1) Privacy and Acceptability, 2) Scalability and 3) Creativity. Even though many questions remain regarding their use in the workplace, wearable technologies and Quantified-Self data in the workplace represent an exciting opportunity for the industry and health and safety practitioners who will be using them.
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Information technologies changed the way of how the health organizations work, contributing to their effectiveness, efficiency and sustainability. Hospital Information Systems (HIS) are emerging on all of health institutions, helping health professionals and patients. However, HIS are not always implemented and used in the best way, leading to low levels of benefits and acceptance by users of these systems. In order to mitigate this problem, it is essential to take measures able to ensure if the HIS and their interfaces are designed in a simple and interactive way. With this in mind, a study to measure the user satisfaction and their opinion was made. It was applied the Technology Acceptance Model (TAM) on a HIS implemented on various hospital centers (AIDA), being used the Pathologic Anatomy Service. The study identified weakness and strengths features of AIDA and it pointed some solutions to improve the medical record.
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Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.
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Advances in Intelligent Systems and Computing, 353
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This paper studies bargaining and conflict under incomplete information, provides an overview and a critical account of the literature on the topic and contributes with original research. We first revise models of mechanism design and sequential bargaining that take confrontation as final. Conflict and inefficiencies are to be expected in these models whenever parties have optimistic prospects on the outcome of the all-out conflict. After examining the causes and reasons for this optimism, we move to the analysis of the recent literature that considers the existence of limited confrontations that allow bargaining to resume. In the presence of private information, these limited conflicts convey information and thus become a bargaining instrument. The paper closes with a discussion on the related empirical literature, the challenges that it faces and some potential avenues for further research.
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This paper studies the implications of correlation of private signals about the liquidation value of a risky asset in a variation of a standard noisy rational expectations model in which traders receive endowment shocks which are private information and have a common component. We nd that a necessary condition to generate multiple linear partially revealing rational expectations equilibria is the existence of several sources of information dispersion. In this context equilibrium multiplicity tends to occur when information is more dispersed. A necessary condition to have strategic complementarity in information acquisition is to have mul- tiple equilibria. When the equilibrium is unique there is strategic substi- tutability in information acquisition, corroborating the result obtained in Grossman and Stiglitz (1980). JEL Classi cation: D82, D83, G14 Keywords: Multiplicity of equilibria, strategic complementarity, asym- metric information.
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The Internet is a fundamental part of the daily life of adolescents, they consider it as a safe and confidential source of information on health matters. The aims is to describe the experience of Spanish adolescents searching for health information on the Internet. Methods A cross-sectional study of 811 school-age adolescents in Granada was carried out. An adapted and piloted questionnaire was used which was controlled by trained personnel. Sociodemographic and health variables were included together with those concerning the conditions governing access to and use of information and communication technologies (ICT). Results 811 adolescents were surveyed (99.38% response rate), mean age was 17 years old. Of these, 88% used the Internet; 57.5% used it on a daily or weekly basis and 38.7% used it occasionally. Nearly half the sample group (55.7%) stated that they used the Internet to search for health-related information. The main problems reported in the search for e-health were the ignorance of good web pages (54.8%) and the lack of confidence or search skills (23.2%). Conclusions In conclusion, it seems plausible to claim that websites designed and managed by health services should have a predominant position among interventions specifically addressed to young people.
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Aquest document de treball mira d'establir un nou camp d'investigació a la cruïlla entre els fluxos de migració i d'informació i comunicació. Hi ha diversos factors que fan que valgui la pena adoptar aquesta perspectiva. El punt central és que la migració internacional contemporània és incrustada en la dinàmica de la societat de la informació, seguint models comuns i dinàmiques interconnectades. Per consegüent, s'està començant a identificar els fluxos d'informació com a qüestions clau en les polítiques de migració. A més, hi ha una manca de coneixement empíric en el disseny de xarxes d'informació i l'ús de les tecnologies d'informació i comunicació en contextos migratoris. Aquest document de treball també mira de ser una font d'hipòtesis per a investigacions posteriors.
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This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.
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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).
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To guarantee the success of a virtual library is essential that all users can access all the library resources independently of the user's location.
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Introduction To guarantee the success of a virtual library it is essential that all users can access all the library resources independently of the user’s location. Achieving this goal in the Andalusian Public Health System has been a particularly difficult task, due to it is made up of 10 research centers and 95.000 health-care professionals. Aims Since the BV-SSPA started three years ago, one of its mayor aims has been to provide remote access to all its resources in this complex scenario, as well as facilitate the access to the virtual library to both professionals and citizens. IP access was guaranteed because health-care professionals could access everything from their workplaces thanks to the intranet, but it was restricted when they were not there. The BV-SSPA solved this problem by installing a federated authentication and authorization system called PAPI and a PAPI rewriting proxy. After three years the BV-SSPA has met a new challenge: adapting its federated access system to Metalib and SFX, specifically the access management module PDS had to be connected with the existing PAPI system. This new challenge came along with the introduction of a new metasearcher and link resolver. Material and Methods Initially there were three independent systems: • A Metalib and SFX PDS module, • A federated authentication and authorization system: PAPI. • A PAPI Rewriting Proxy. The chosen solution went through the reutilization of the existing software. To achieve this goal, a PHP connector between these applications was developed and several modules in the PDS configuration were modified. On the other hand, providing a simplified access to Metalib has been solved using Xerxes and integrating it in a Drupal website. Results Thanks to this connector the BV-SSPA was able to get all its users remotely accessing its new metasearcher without changing the way they used to validate, or without having to remember a new username and password. Futhermore, thanks to Xerxes, it is possible to use Metalib from a simple interface and without having to leave the BV-SSPA website to go its native interface.
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The concept of Library of the Health Sciences has noticeably changed during the last decade. The embedded librarian is a recently emerged figure, who works as a member of multidisciplinary groups with the mission of providing them with relevant literature as well as media for acquisition, exchange and dissemination of information. This figure has been gradually implanted in some committees of the ASEMA. The objective of the present work is to describe the functions of the embedded librarian and its results in our area.
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BACKGROUND It is not clear to what extent educational programs aimed at promoting diabetes self-management in ethnic minority groups are effective. The aim of this work was to systematically review the effectiveness of educational programs to promote the self-management of racial/ethnic minority groups with type 2 diabetes, and to identify programs' characteristics associated with greater success. METHODS We undertook a systematic literature review. Specific searches were designed and implemented for Medline, EMBASE, CINAHL, ISI Web of Knowledge, Scirus, Current Contents and nine additional sources (from inception to October 2012). We included experimental and quasi-experimental studies assessing the impact of educational programs targeted to racial/ethnic minority groups with type 2 diabetes. We only included interventions conducted in countries members of the OECD. Two reviewers independently screened citations. Structured forms were used to extract information on intervention characteristics, effectiveness, and cost-effectiveness. When possible, we conducted random-effects meta-analyses using standardized mean differences to obtain aggregate estimates of effect size with 95% confidence intervals. Two reviewers independently extracted all the information and critically appraised the studies. RESULTS We identified thirty-seven studies reporting on thirty-nine educational programs. Most of them were conducted in the US, with African American or Latino participants. Most programs obtained some benefits over standard care in improving diabetes knowledge, self-management behaviors and clinical outcomes. A meta-analysis of 20 randomized controlled trials (3,094 patients) indicated that the programs produced a reduction in glycated hemoglobin of -0.31% (95% CI -0.48% to -0.14%). Diabetes knowledge and self-management measures were too heterogeneous to pool. Meta-regressions showed larger reduction in glycated hemoglobin in individual and face to face delivered interventions, as well as in those involving peer educators, including cognitive reframing techniques, and a lower number of teaching methods. The long-term effects remain unknown and cost-effectiveness was rarely estimated. CONCLUSIONS Diabetes self-management educational programs targeted to racial/ethnic minority groups can produce a positive effect on diabetes knowledge and on self-management behavior, ultimately improving glycemic control. Future programs should take into account the key characteristics identified in this review.
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BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.