Search results for: Individual patient data

Authors: Danielle Klassen, Reiko Yeap, Margo Schmitt-Boshnick, Scott Oddie

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The development of the 7-week Alberta Happiness Basics program was initiated in 2010 in response to the need for community mental health programming. This provincial wide program aims to increase overall happiness and reduce negative thoughts and feelings through a positive psychology intervention. While the 7-week program has proven effective, a shortened 4-week program has additionally been developed to address client needs. In this study, participants were interviewed to determine if the 4- and 7-week programs had similar success of producing lasting behavior change at 3, 6, and 9 months post-program. A health quality of life (HQOL) measure was also used to compare the two programs and examine patient outcomes. Quantitative and qualitative analysis showed significant improvements in HQOL and sustainable behavior change for both programs. Findings indicate that the shorter, patient-centered program was effective in increasing happiness and reducing negative thoughts and feelings.

Keywords: Primary care, mental health, depression, short duration.

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: Data mining, data analysis, prediction, optimization, building operational performance.

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Authors: Hadi Sadoghi Yazdi, Tahereh Royani, Mehri Sadoghi Yazdi, Sohrab Effati

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In this paper, a new version of support vector regression (SVR) is presented namely Fuzzy Cost SVR (FCSVR). Individual property of the FCSVR is operation over fuzzy data whereas fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown in the experimental results as a property of the proposed method and superiority relative conventional SVR.

Keywords: Support vector regression, Fuzzy input, Fuzzy cost.

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Authors: Ei Ei Myat, Ni Lar Thein

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With the tremendous growth of World Wide Web (WWW) data, there is an emerging need for effective information retrieval at the document level. Several query languages such as XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent years to provide faster way of querying XML data, but they still lack of generality and efficiency. Our approach towards evolving a framework for querying semistructured documents is based on formal query algebra. Two elements are introduced in the proposed framework: first, a generic and flexible data model for logical representation of semistructured data and second, a set of operators for the manipulation of objects defined in the data model. In additional to accommodating several peculiarities of semistructured data, our model offers novel features such as bidirectional paths for navigational querying and partitions for data transformation that are not available in other proposals.

Keywords: Algebra, Semistructured data, Query Algebra.

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Authors: Adam Świtoński, Agnieszka Michalczuk, Henryk Josiński, Andrzej Polański, KonradWojciechowski

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The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.

Keywords: Biometrics, dynamic time warping, gait identification, motion capture, time series classification, quaternion distance functions, attribute ranking.

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: Simulation data, data summarization, spatial histograms, exploration and visualization.

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Authors: Reza Nadimi, Fariborz Jolai

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This article combines two techniques: data envelopment analysis (DEA) and Factor analysis (FA) to data reduction in decision making units (DMU). Data envelopment analysis (DEA), a popular linear programming technique is useful to rate comparatively operational efficiency of decision making units (DMU) based on their deterministic (not necessarily stochastic) input–output data and factor analysis techniques, have been proposed as data reduction and classification technique, which can be applied in data envelopment analysis (DEA) technique for reduction input – output data. Numerical results reveal that the new approach shows a good consistency in ranking with DEA.

Keywords: Effectiveness, Decision Making, Data EnvelopmentAnalysis, Factor Analysis

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Authors: Okolie Uchenna, Ehiemere Ijeoma, Ezenduka Pauline, Ogbu Sylvester

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A cross sectional survey design was used to collect data from 370 diabetic patients. Two instruments were used in obtaining data; in-depth interview guide and researchers- developed questionnaire. Fisher's exact test was used to investigate association between the identified factors and nonadherence. Factors identified were: socio-demographic factors such as: gender, age, marital status, educational level and occupation; psychosocial obstacles such as: non-affordability of prescribed diet, frustration due to the restriction, limited spousal support, feelings of deprivation, feeling that temptation is inevitable, difficulty in adhering in social gatherings and difficulty in revealing to host that one is diabetic; health care providers obstacles were: poor attitude of health workers, irregular diabetes education in clinics , limited number of nutrition education sessions/ inability of the patients to estimate the desired quantity of food, no reminder post cards or phone calls about upcoming patient appointments and delayed start of appointment / time wasting in clinics.

Keywords: Behavior change, diabetes mellitus, dietarymanagement, diet adherence.

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. In this paper, we investigated three approaches to build a meta-classifier in order to increase the classification accuracy. The basic idea is to learn a metaclassifier to optimally select the best component classifier for each data point. The experimental results show that combining classifiers can significantly improve the accuracy of classification and that our meta-classification strategy gives better results than each individual classifier. For 7083 Reuters text documents we obtained a classification accuracies up to 92.04%.

Keywords: Meta-classification, Learning with Kernels, Support Vector Machine, and Performance Evaluation.

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Authors: M. Gooroochurn, M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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A registration framework for image-guided robotic surgery is proposed for three emergency neurosurgical procedures, namely Intracranial Pressure (ICP) Monitoring, External Ventricular Drainage (EVD) and evacuation of a Chronic Subdural Haematoma (CSDH). The registration paradigm uses CT and white light as modalities. This paper presents two simulation studies for a preliminary evaluation of the registration protocol: (1) The loci of the Target Registration Error (TRE) in the patient-s axial, coronal and sagittal views were simulated based on a Fiducial Localisation Error (FLE) of 5 mm and (2) Simulation of the actual framework using projected views from a surface rendered CT model to represent white light images of the patient. Craniofacial features were employed as the registration basis to map the CT space onto the simulated intraoperative space. Photogrammetry experiments on an artificial skull were also performed to benchmark the results obtained from the second simulation. The results of both simulations show that the proposed protocol can provide a 5mm accuracy for these neurosurgical procedures.

Keywords: Image-guided Surgery, Multimodality Registration, Photogrammetry, Preoperative to Intraoperative Registration.

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Authors: Yungchien Cheng, Chienmin Chu

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Current practice of indigenous Mapping production based on GIS, are mostly produced by professional GIS personnel. Given such persons maintain control over data collection and authoring, it is possible to conceive errors due to misrepresentation or cognitive misunderstanding, causing map production inconsistencies. In order to avoid such issues, this research into tribal GIS interface focuses not on customizing interfaces for individual tribes, but rather generalizing the interface and features based on indigenous tribal user needs. The methods employed differs from the traditional expert top-down approach, and instead gaining deeper understanding into indigenous Mappings and user needs, prior to applying mapping techniques and feature development.

Keywords: GIS, participatory GIS, indigenous mapping

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Authors: Kristýna Pokorná, Petr Teplý

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This paper focuses on sovereign credit risk meaning a hot topic related to the current Eurozone crisis. In the light of the recent financial crisis, market perception of the creditworthiness of individual sovereigns has changed significantly. Before the outbreak of the financial crisis, market participants did not differentiate between credit risk born by individual states despite different levels of public indebtedness. In the proceeding of the financial crisis, the market participants became aware of the worsening fiscal situation in the European countries and started to discriminate among government issuers. Concerns about the increasing sovereign risk were reflected in surging sovereign risk premium. The main of this paper is to shed light on the characteristics of the sovereign risk with the special attention paid to the mutual relation between credit spread and the CDS premium as the main measures of the sovereign risk premium.

Keywords: cointegration, credit default swap, credit risk, credit spread, sovereign risk

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Authors: Dutescu Adriana, Amariei Corneliu, Sahlian Daniela, Stanila Aurelian, Stanila Oana

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20 years of dentistry was a period of transition from communist to market economy but Romanian doctors have insufficient management knowledge. Recently, the need for modern management has increased due to technologies and superior materials appearance, as patient-s demands. Research goal is to increase efficiency by evaluating dental medical office cost categories in real pricing procedures. Empirical research is based on guided study that includes information about the association between categories of cost perception and therapeutic procedures commonly used in dental offices. Due to the obtained results to identify all the labours that make up a settled procedure costs were determined for each procedure. Financial evaluation software was created with the main functions: introducing and maintaining patient records, treatment and appointments made, procedures cost and monitoring office productivity. We believe that the study results can significantly improve the financial management of dental offices, increasing the effectiveness and quality of services.

Keywords: costs, financial methods, management.

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Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

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A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: Critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team.

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Authors: Enerit Saçdanaku, Idriz Haxhiu

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In this study was monitored the population of the European Pond Turtle, Emys orbicularis (Linnaeus, 1758) in the area of Narta Lagoon, Vlora Bay (Albania), from August to October 2014. A total of 54 individuals of E. orbicularis were studied using different methodologies. Curved Carapace Length (CCL), Plastron Length (PL) and Curved Carapace Width (CCW) were measured for each individual of E. orbicularis and were statistically analyzed. All captured turtles were separated in seven different size – classes based on their carapace length (CCL). Each individual of E. orbicularis was marked by notching the carapace (marginal scutes). Form all individuals captured resulted that 37 were females (68.5%), 14 males (25.9%), 3 juveniles (5.5%), while 18 individuals of E. orbicularis were recaptured for the first and some for the second time.

Keywords: Emys orbicularis, female, juvenile, male, population, size – classes.

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: Ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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Authors: Rajashekar Patil, S. Mohan Kumar, Shreya Ajmera

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To understand complex living system an effort has made by mechanical engineers and dentists to deliver prompt products and services to patients concerned about their aesthetic look. Since two decades various bracket systems have designed involving techniques like milling, injection molding which are technically not flexible for the customized dental product development. The aim of this paper to design, develop a customized system which is economical and mainly emphasizes the expertise design and integration of engineering and dental fields. A custom made selfadjustable lingual bracket and customized implants are designed and developed using computer aided design (CAD) and rapid prototyping technology (RPT) to improve the smiles and to overcome the difficulties associated with conventional ones. Lengthy orthodontic treatment usually not accepted by the patients because the patient compliance is lost. Patient-s compliance can be improved by facilitating faster tooth movements by designing a localized dental vibrator using advanced engineering principles.

Keywords: Orthodontics, Prosthodontics, Lingual bracket, Implants, Dental vibrator, Computer aided design, Rapid prototyping technology.

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Authors: Youkyung Park, SeungYup Kang, SungHo Kim, SimKyun Yook

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IMCS is Integrated Monitoring and Control System for thermal power plant. This system consists of mainly two parts; controllers and OIS (Operator Interface System). These two parts are connected by Ethernet-based communication. The controller side of communication is managed by CNet module and OIS side is managed by data server of OIS. CNet module sends the data of controller to data server and receives commend data from data server. To minimizes or balance the load of data server, this module buffers data created by controller at every cycle and send buffered data to data server on request of data server. For multiple data server, this module manages the connection line with each data server and response for each request from multiple data server. CNet module is included in each controller of redundant system. When controller fail-over happens on redundant system, this module can provide data of controller to data sever without loss. This paper presents three main features – separation of get task, usage of ring buffer and monitoring communication status –of CNet module to carry out these functions.

Keywords: Ethernet communication, DCS, power plant, ring buffer, data integrity

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: Big data, big data Analytics, Hadoop framework, cloud computing.

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption.

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

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Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: Data integration, data warehousing, federated architecture, online analytical processing.

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Authors: Martin Lnenicka

Abstract:

Governments collect and produce large amounts of data. Increasingly, governments worldwide have started to implement open data initiatives and also launch open data portals to enable the release of these data in open and reusable formats. Therefore, a large number of open data repositories, catalogues and portals have been emerging in the world. The greater availability of interoperable and linkable open government data catalyzes secondary use of such data, so they can be used for building useful applications which leverage their value, allow insight, provide access to government services, and support transparency. The efficient development of successful open data portals makes it necessary to evaluate them systematic, in order to understand them better and assess the various types of value they generate, and identify the required improvements for increasing this value. Thus, the attention of this paper is directed particularly to the field of open data portals. The main aim of this paper is to compare the selected open data portals on the national level using content analysis and propose a new evaluation framework, which further improves the quality of these portals. It also establishes a set of considerations for involving businesses and citizens to create eservices and applications that leverage on the datasets available from these portals.

Keywords: Big data, content analysis, criteria comparison, data quality, open data, open data portals, public sector.

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Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan

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The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.

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Authors: R. Amornmaneekul, S. Chadsuthi, D. Triampo, W. Triampo

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We apply a particle tracking technique to track the motion of individual pathogenic Leptospira. We observe and capture images of motile Leptospira by means of CCD and darkfield microscope. Image processing, statistical theories and simulations are used for data analysis. Based on trajectory patterns, mean square displacement, and power spectral density characteristics, we found that the motion modes are most likely to be directed motion mode (70%) and the rest are either normal diffusion or unidentified mode. Our findings may support the fact that why leptospires are very well efficient toward targeting internal tissues as a result of increase in virulence factor.

Keywords: Leptospirosis, spirochetes, patterns, motion.

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Authors: Reza Ariaeinejad, Norm Archer

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Self-management is becoming a new emphasis for healthcare systems around the world. But there are many different problems with adoption of new health-related intervention systems. The situation is even more complicated for chronically ill patients with disabilities, illiteracy, and impairment in judgment in addition to their conditions, or having multiple co-morbidities. Providing online decision support to manage patient health and to provide better support for chronically ill patients is a new way of dealing with chronic disease management. In this study, the importance of mobile technology through an m-Health system that supports self-management interventions including the care provider, family and social support, education and training, decision support, recreation, and ongoing patient motivation to promote adherence and sustainability of the intervention are discussed. A proposed theoretical model for adoption and sustainability of system use is developed, based on UTAUT2 and IS Continuance of Use models, both of which have been pre-validated through longitudinal studies. The objective of this paper is to show the importance of using mobile technology in adoption and sustainability of use of an m-Health system which will result in commercially sustainable self-management support for chronically ill patients.

Keywords: M-health, e-health, self-management, disease.

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Authors: Paula A. Cruise, Carvell McLeary

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Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [n_bank= 264; male=57 (22.73%); n_energy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ²) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.

Keywords: Context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention.

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Authors: Leila Batmany

Abstract:

This research studies the relationship between the feeling of distributive justice and national identity of the youth. The present analysis intends to experimentally investigate the various dimensions of the justice feeling and its effect on the national identity components. The study has taken justice into consideration from four different points of view on the basis of availability of valuable social sources such as power, wealth, knowledge and status in the political, economic, and cultural and status justice respectively. Furthermore, the national identity has been considered as the feeling of honour, attachment and commitment towards national society and its seven components i.e. history, language, culture, political system, religion, geographical territory and society. The 'field study' has been used as the method for the research with the individual as unit, taking 368 young between the age of 18 and 29 living in Tehran, chosen randomly according to Cochran formula. The individual samples have been randomly chosen among five districts in north, south, west, east, and centre of Tehran, based on the multistage cluster sampling. The data collection has been performed with the use of questionnaire and interview. The most important results are as follows: i) The feeling of economic justice is the weakest one among the youth. ii) The strongest and the weakest dimensions of the national identity are, respectively, the historical and the social dimension. iii) There is a positive and meaningful relationship between the feeling political and statues justice and then national identity, whereas no meaningful relationship exists between the economic and cultural justice and the national identity. iv) There is a positive and meaningful relationship between the feeling of justice in all dimensions and legitimacy of the political system. There is also such a relationship between the legitimacy of the political system and national identity. v) Generally, there is a positive and meaningful relationship between the feeling of distributive justice and national identity among the youth. vi) It is through the legitimacy of the political system that justice feeling can have an influence on the national identity.

Keywords: Distributive justice, national identity, legitimacy of political system, Cochran formula, multistage cluster sampling.

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Authors: Jaechun No

Abstract:

As data to be stored in storage subsystems tremendously increases, data protection techniques have become more important than ever, to provide data availability and reliability. In this paper, we present the file system-based data protection (WOWSnap) that has been implemented using WORM (Write-Once-Read-Many) scheme. In the WOWSnap, once WORM files have been created, only the privileged read requests to them are allowed to protect data against any intentional/accidental intrusions. Furthermore, all WORM files are related to their protection cycle that is a time period during which WORM files should securely be protected. Once their protection cycle is expired, the WORM files are automatically moved to the general-purpose data section without any user interference. This prevents the WORM data section from being consumed by unnecessary files. We evaluated the performance of WOWSnap on Linux cluster.

Keywords: Data protection, Protection cycle, WORM

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Authors: Pavel Vazan, Pavol Tanuska, Michal Kebisek

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The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.

Keywords: data mining, data warehousing, management of production system, simulation

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