• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.9-20
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• 2016

Several task clustering heuristics are proposed for allocating tasks in heterogeneous systems to achieve a good response time in data intensive jobs. However, one of the challenging problems is the process in task scheduling after task allocation by task clustering. We propose a task scheduling method after task clustering, leveraging worst schedule length (WSL) as an upper bound of the schedule length. In our proposed method, a task in a WSL sequence is scheduled preferentially to make the WSL smaller. Experimental results by simulation show that the response time is improved in several task clustering heuristics. In particular, our proposed scheduling method with the task clustering outperforms conventional list-based task scheduling methods.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.15 no.4
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• pp.531-538
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• 2008

Purpose: The purpose of this study was to identify factors influencing Vancomycin-resistant enterococcus infection control among nurses in intensive care units. Method: Data were collected from August 15 to October 14, 2007 from 188 nurses working in intensive care units. The nurses answered a 26 item-questionnaire, which included management of the cohort (14 items), hand washing (6 items) and management of the environment (6 items). Descriptive statistics, t or F test, ANOVA, and multiple regression analysis were used with SPSS PC+ 14.0 to analyze the data. Results: The participant's level of awareness of Vancomycin-resistant enterococcus infection control was 3.87; that of compliance was 3.74. Significant factors influencing the level of compliance with Vancomycin-resistant enterococcus infection control were'the level of the awareness' and 'the type of intensive care unit'. These two variables accounted for 21.0% of variance for compliance with the Vancomycin-resistant enterococcus infection control among the participants. Conclusion: In order to develop a strategy to increase the compliance with Vancomycin-resistant enterococcus infection control, it is necessary to be concerned about 'the level of the awareness', 'the type of intensive care unit;', and 'experiences of caring for patients with Vancomycin-resistant enterococcus'.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.423-436
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• 2019

Purpose: The aim of the study was to explore nurses' experience of person-centered relational care in the context of critical care. Methods: Key interview questions were developed based on the human-to-human relationship model suggested by Travelbee. Data were collected through indepth interviews with a purposive sample of 11 nurses having more than 2 years of working experience in intensive care units. An interpretative phenomenological analysis was conducted to analyze the data. Results: Four super-ordinate and nine sub-ordinate themes were identified. Emerged super-ordinate themes were as follows: (1) encountering a live person via patient monitoring systems; (2) deep empathic connection; (3) humanistic and compassionate care, and (4) accompanying the journey to the end. Study findings revealed that nurses in intensive care units experienced 'balancing emotions' and 'authenticity' in caring when entering human-to-human relationships with dying patients. The phenomenon of person-centered relational care in intensive care units was found to subsume intrinsic attributes of empathy, compassion, and trust, similar to the central concepts of Travelbee's theory. Conclusion: The interpretative findings in this study provide deeper understanding of Travelbee's human-to-human relationship model. The technological environment in intensive care units did not hinder experienced nurses from forming human-to-human relationships. These themes need to be emphasized in critical care nursing education as well as in nursing management. The results of this study will contribute to understanding nurse-patient caring relationships in depth, and help improve the quality of nursing care in intensive care units.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.3
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• pp.261-273
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• 2021

Purpose: This study used a descriptive investigative design to identify educational needs for developmental supportive care for the purpose of establishing a developmental supportive care education program for nurses in neonatal intensive care units. Methods: A survey was conducted on 93 nurses working in neonatal intensive care units located in a metropolitan area, and the collected data were analyzed using descriptive statistics and a paired t-test with the SPSS 25.0 program. For the purpose of analyzing educational needs, we further analyzed data through an importance-performance analysis (IPA) and the Borich needs assessment and the locus for focus models. Results: The average importance of the developmental supportive care of nurses in neonatal intensive care units was 3.74±0.78 out of 5, and the average performance was 3.46±0.81 out of 5. A t-test on the difference between the IPA and Borich needs assessment showed the highest educational need in the categories of 'individualized care', and 'I serve on the Developmental Care Committee at my institution'. In addition, according to the results of deriving the priorities of educational needs using the Borich needs assessment and the locus for focus model, the highest priority was 'I provide appropriate pain management when noxious procedures are necessary'. Conclusion: These findings can be used as basic data to design a developmental supportive care program suitable for nurses in neonatal intensive care units to meet the educational needs for developmental supportive care.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.491-502
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• 2014

In this paper we present some research results on computing intensive applications using modern high performance architectures and from the perspective of high computational needs. Computing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there are applications based on simulations, aiming to maximize system resources for processing large computations for simulation. In this research work, we consider an application that simulates scheduling and resource allocation in a Grid computing system using Genetic Algorithms. In such application, a rather large number of simulations is needed to extract meaningful statistical results about the behavior of the simulation results. We study the performance of Oracle Grid Engine for such application running in a Cluster of high computing capacities. Several scenarios were generated to measure the response time and queuing time under different workloads and number of nodes in the cluster.

• Asia Pacific Journal of Business Review
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• v.6 no.2
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• pp.1-26
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• 2022

This study uses the human resource management (HRM) practice and ability, motivation, and opportunities (AMO) theory and corporate social and environmental responsibility, to explore the effects of environmental responsible human resource management practice (ER-HRM) on energy-intensive manufacturing's green technology innovation and organizational effectiveness. A self-completed questionnaire was administered to managers of energy-intensive manufacturing in the Lao PDR. The data was collected from 198 managers of energy-intensive manufacturing for analysis. We used structural equation modeling (SEM) by smart PLS 3.0 to test the hypotheses in this research. The findings have shown a strong direct and positive impact of the environmental ability, motivation, and opportunity of ER-HRM practice on green technology innovation and organizational effectiveness. The ability of ER-HRM practice has the highest influence on green technology innovation and organizational effectiveness. The findings also prove the partial mediation of green technology innovation links ER-HRM with organizational effectiveness. This research is expected to identify the influences of ER-HRM in energy-intensive manufacturing to achieve innovation and performance while reducing emissions.

• Biomedical Science Letters
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• v.7 no.3
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• pp.117-125
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• 2001

This study was performed in order to evaluate the risk factors for nosocomial urinary tract infection and the frequencies of organisms isolated, and to provide the epidemiologic and basic data of hospital acquired urinary tract infection in intensive care unit. A prospective analysis was performed with 1,235 urine samples following urinary bladder catheterization in 569 patients, who had no evidence of UTI at the time of catheter insertion, admitted to intensive care unit in Pusan P hospital between June 1997 and May 1998. To identify risk factors for UTI, clinical characteristics of infected patients were analyzed. We analyzed these data by percentage, chi-square and odd ratio. Obtained results were as follows: A total of 569 patients (male 341 and female 228) were an average age of 50.8 years and catheterization of 8.04 days. Incidence of UTI was 16.1% (199/1,235) and The risk factors of UTI were duration of catheterization over 7 days, no use of systemic antibiotics, summer and female, and During the first 7 days these risk factors were no use of systemic antibiotics, summer, place of first catheter insertion (ICU) and type of intensive care unit (NSICU). A total of 220 the isolated strains were Gram negative rod 83 (37.7%), yeast like fungi 74 (33.6%) and Gram positive cocci 63 (28.6%). The common organisms isolated were Enterococcus faecalis 23 (10.5%), Serratia marcescens 19 (8.6%), Pseudomonu spp.17 (7.7%), E. ooh 16 (7.3%), Staphylococcus epidemidis 11 (5.0%) mdklebsiellapneumoniae 8 (3.6%). Therefore, in these results 199 of 569 (35%) patients in ICU with indwelling urinary catheter developed UTI. The risk factors for UTI are prolonged duration of catheterization, no use of systemic antibiotics, summer, and female.

• Asian Journal of Innovation and Policy
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• v.4 no.3
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• pp.381-396
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• 2015

Cyberinfrastructure is a research infrastructure that provides an environment in which research communities can get access to distributed resources and collaborate at unprecedented levels of computation, storage, and network capacity. The Worldwide LHC Computing Grid (WLCG) is a global collaborative project of computing or data centers that enables access to scientific data generated by the Large Hadron Collider (LHC) experiments at CERN. This case study analyzes the WLCG as a model of cyberinfrastructure in research collaboration. WLCG provides a useful case of how cyberinfrastructure can work in providing an infrastructure for collaborative researches under data-intensive paradigm. Cyberinfrastructure plays the critical role of facilitating collaboration of diverse and widely separated communities of researchers. Data-intensive science requires new strategies for research support and significant development of cyberinfrastructure. The sustainability of WLCG depends on the resources of partner organizations and virtual organizations at international levels, essential for research collaboration.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.142-148
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• 2023

In this paper, we identify performance issues in executing compute kernels from PolyBench, which includes compute kernels that are the core computational units of various data-intensive workloads, such as deep learning and data-intensive applications, on Processing-in-Memory (PIM) devices. Therefore, using our in-house simulator, we measured and compared the various performance metrics of workloads based on traditional out-of-order and in-order processors with Processing-in-Memory-based systems. As a result, the PIM-based system improves performance compared to other computing models due to the short-term data reuse characteristic of computational kernels from PolyBench. However, some kernels perform poorly in PIM-based systems without a multi-layer cache hierarchy due to some kernel's long-term data reuse characteristics. Hence, our evaluation and analysis results suggest that further research should consider dynamic and workload pattern adaptive approaches to overcome performance degradation from computational kernels with long-term data reuse characteristics and hidden data locality.

• Journal of Korean Academy of Nursing
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• v.40 no.3
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• pp.307-316
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• 2010

Purpose: The purpose of this study was to identify the levels of relocation stress syndrome (RSS) and influencing the stress experienced by Intensive Care Unit (ICU) patients just after transfer to general wards. Methods: A cross-sectional study was conducted with 257 patients who transferred from the intensive care unit. Data were collected through self-report questionnaires from May to October, 2009. Data were analyzed using the Pearson correlation coefficient, t-test, one-way ANOVA, and stepwise multiple linear regression with SPSS/WIN 12.0. Results: The mean score for RSS was $17.80{\pm}9.16$. The factors predicting relocation stress syndrome were symptom experience, differences in scope and quality of care provided by ICU and ward nursing staffs, satisfaction with transfer process, length of stay in ICU and economic status, and these factors explained 40% of relocation stress syndrome (F=31.61, p<.001). Conclusion: By understanding the stress experienced by ICU patients, nurses are better able to provide psychological support and thus more holistic care to critically ill patients. Further research is needed to consider the impact of relocation stress syndrome on patients' health outcomes in the recovery trajectory.