• 산업공학
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• 제17권3호
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• pp.282-293
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• 2004

Line Balancing is the problem to assign tasks to stations while satisfying some managerial viewpoints. Most researches about the Mixed-Model Line Balancing problems are focused on the minimizing the total processing time or the number of workstations. Independently, some research reports consider the balance issues of the physical workloads on the assembly line. In this paper, we are presenting a new mathematical model to accomplish the line balance considering both the processing time and the workloads at the same time. To this, end, we propose an zero-one integer program problem, and we use the Chebyshev Goal Programming approach as the solution method. Some computational test runs are performed to compare the pay-offs between the processing time and the workloads. And, the test results show us that the reliable balanced work schedules can be obtained through the proposed model.

• 산업경영시스템학회지
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• 제35권4호
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• pp.33-40
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• 2012

Dentists are known to be highly exposed to the musculoskeletal disorders (MSD). The present study investigated the prevalence of MSD among Korean dentists and association between their MSD and physical workload. In addition, detailed causes related to the physical workloads were identified in dental operation, and needs for improvement of dental instrument and environment were collected from Korean dentists. The standardized Nordic questionnaire was used to survey body troubles and three types of questionnaires were made to investigate the physical workloads, causes of the physical workloads and improvement priority of dental equipments, respectively. A total of 104 Korean dentists were participated in the survey. Neck trouble (82%) was the most prevalent in Korean dentists, and shoulder (68%) and low back trouble (56%) followed, while low back trouble was reported to be most frequent in previous studies. The body troubles were related to the physical workload of the corresponding body parts, although they were not associated with personal characteristics. Most Korean dentists selected 'to keep direct view inside patient's mouth' and 'no support of the hand with dental instruments' as the causes of awkward and strenuous work postures. They wanted design improvement for some equipment in their operating room such as operating light and arrangement of workplace.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.2824-2837
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• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2257-2285
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• 2022

Cyber-physical systems (CPS) have been growing exponentially due to improved cloud-datacenter infrastructure-as-a-service (CDIaaS). Incremental expandability (scalability), Quality of Service (QoS) performance, and reliability are currently the automation focus on healthy Tier 4 CDIaaS. However, stable QoS is yet to be fully addressed in Cyber-physical data centers (CP-DCS). Also, balanced agility and flexibility for the application workloads need urgent attention. There is a need for a resilient and fault-tolerance scheme in terms of CPS routing service including Pod cluster reliability analytics that meets QoS requirements. Motivated by these concerns, our contributions are fourfold. First, a Distributed Non-Recursive Cloud Model (DNRCM) is proposed to support cyber-physical workloads for remote lab activities. Second, an efficient QoS stability model with Routh-Hurwitz criteria is established. Third, an evaluation of the CDIaaS DCN topology is validated for handling large-scale, traffic workloads. Network Function Virtualization (NFV) with Floodlight SDN controllers was adopted for the implementation of DNRCM with embedded rule-base in Open vSwitch engines. Fourth, QoS evaluation is carried out experimentally. Considering the non-recursive queuing delays with SDN isolation (logical), a lower queuing delay (19.65%) is observed. Without logical isolation, the average queuing delay is 80.34%. Without logical resource isolation, the fault tolerance yields 33.55%, while with logical isolation, it yields 66.44%. In terms of throughput, DNRCM, recursive BCube, and DCell offered 38.30%, 36.37%, and 25.53% respectively. Similarly, the DNRCM had an improved incremental scalability profile of 40.00%, while BCube and Recursive DCell had 33.33%, and 26.67% respectively. In terms of service availability, the DNRCM offered 52.10% compared with recursive BCube and DCell which yielded 34.72% and 13.18% respectively. The average delays obtained for DNRCM, recursive BCube, and DCell are 32.81%, 33.44%, and 33.75% respectively. Finally, workload utilization for DNRCM, recursive BCube, and DCell yielded 50.28%, 27.93%, and 21.79% respectively.

• 대한인간공학회지
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• 제29권2호
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• pp.203-210
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• 2010

For the development of a better product which fits to the target user population, physical workloads such as reach and visibility are evaluated using digital human simulation in the early stage of product development; however, ergonomic workload assessment mainly relies on visual observation of reach envelopes and view cones generated in a 3D graphic environment. The present study developed a quantitative assessment method of physical workload in a digital environment and applied to the evaluation of a Korean utility helicopter (KUH) cockpit design. The proposed assessment method quantified physical workloads for the target user population by applying a 3-step process and identified design features requiring improvement based on the quantified workload evaluation. The scores of physical workloads were quantified in terms of posture, reach, visibility, and clearance, and 5-point scales were defined for the evaluation measures by referring to existing studies. The postures of digital humanoids for a given task were estimated to have the minimal score of postural workload by finding all feasible postures that satisfy task constraints such as a contact between the tip of the index finger and a target point. The proposed assessment method was applied to evaluate the KUH cockpit design in the preliminary design stage and identified design features requiring improvement. The proposed assessment method can be utilized to ergonomic evaluation of product designs using digital human simulation.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• 산업경영시스템학회지
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• 제28권3호
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• pp.98-108
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• 2005

The assembly line balancing problem has been focused by many research works because the efficient management of the assembly line might influence not only the quality of the products but also the working conditions for the workers. This paper deals with U-shape mixed-model assembly line balancing and considers both the processing time and the physical workloads. We suggest the goal programming approach for this situation and to overcome some difficulties of finding optimal solution, we adopt the genetic algorithm that is one of the most promising solution techniques. We tested several test problems and present the results that indicate some improvement for the line balancing as well as the stable performance of the algorithm.

• PNF and Movement
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• 제19권2호
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• pp.225-231
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• 2021

Purpose: This study was conducted to investigate the type of physical therapist response work and its intensity, along with the prolonged prevalence of COVID-19, to determine the impact on physical therapists' occupational stress and occupational burnout. Methods: An online survey was conducted with 118 physiotherapists and collected the participants' gender, final educational background, clinical work experience, workplace type, additional workload, and fatigue associated with COVID-19. After excluding one participant who submitted an incomplete questionnaire, 117 respondents were included in the final data. Results: Additional COVID-19-related workloads and response reliability for fatigue, occupational burnout, and occupational stress were shown to have Cronbach's alpha measures of 0.76, 0.89, and 0.87, respectively. Groups who had experienced a new epidemic in the past showed higher fatigue levels (3.06±0.94) than those groups who had no such experience (2.49±0.84; p < 0.05). Correlation analysis of COVID-19 work fatigue and occupational burnout scales showed a positive correlation (r = 0.19; p < 0.05). The regression of occupational burnout and occupational stress showed a regression model of Y = 20.00+0.43X₁ (X₁: job stress; p< 0.05) and an explanatory power of 24.8% with an adj.R² = 0.25. Conclusion: Based on the results, it is suggested that various institutions, such as medical institutions, educational institutions, and physiotherapists' associations, should seek ways to manage and alleviate physiotherapists' stress.

• Journal of Information Technology Applications and Management
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• 제16권2호
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• pp.135-150
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• 2009

Corporate databases are usually denormalized, due to the data modelers' impetuous belief that denormalization could improve system performance. By providing a logical insight into denormalization, this paper attempts to prevent every database modeler from falling into the denormalization pit. We indicate loopholes in the denormalization advocates' assertions, and then present four criteria to analyze the usefulness and validity of denormalization; 1) the level of concurrency among transactions, 2) the database independence of the application program, 3) the independence between the logical design and the physical one, and 4) the overhead cost to maintain database integrity under various query patterns. This paper also includes experimental results to evaluate performance of denormalized and fully normalized structures under various workloads.

• 산업경영시스템학회지
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• 제21권48호
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• pp.101-111
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• 1998

CNS (Car Navigation System) is the most compatible candidate among various in-vehicle information systems as a provider of ITS (Intelligence Transport Systems) information. It generally consists of remote controller, display, CD-changer, GPS receiver and so on. Among them, display is the most important and critical element of the HMI (Human-Machine Interface) suggesting the digital map to the driver. Therefore, it is certain that the display gives cognitive, physical, mental and visual workloads to the driver which are directly related with the driver's and road safety with the success of ITS. Until now, various human factors techniques have been developed and applied to estimate the driver's workload and to collect the driver's requirements of the CNS digital map, for example, mental workload assessment, visual activity analysis, cognitive analysis and so on. In addition to these kinds of techniques, this research performed the human sensibility ergonomics approach to directly investigate and evaluate the driver's requirements and sensibilities of the real products.