• Journal of Mechanical Science and Technology
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• 제20권7호
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• pp.961-971
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• 2006

A deadweight force standard machine is a mechanical structure that generates force by subjecting deadweights to the local gravitational field. The Korea Research Institute of Standards and Science (KRISS) developed and installed a 100 kN deadweight force standard machine for national force standards. It can generate forces from 2 kN to 110 kN in increments of 1 kN. The uncertainty of the force machine was estimated and declared as $2\times10^{-5}$. This 100 kN deadweight force machine was compared with the 500 kN deadweight force standard machine at KRISS and the 20 kN and 50 kN deadweight force standard machines at the National Metrology Institute of Japan (NMIJ). The measurement results showed good agreement between the deadweight force machines, and the accuracy level of the 100 kN deadweight force machine was verified.

• 대한물리치료과학회지
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• 제20권1호
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• pp.1-7
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• 2013

Purpose : Investigate the effects of Horse-back riding Simulation Machine training on the Balance ability in Patients with Stroke. Method : The patients were divided to control group(n=18) with conventional rehabilitation conventional rehabilitation 60min/day and experimental group(n=17) with hippotherapy simulator 15 min/day after conventional rehabilitation 45min/day, 5 time/week for 4 weeks. Balance ability of both groups was assessed using Timed Up and Go(TUG), Berg balabce scale(BBS) and Center of pressure area(COPA). In the present result, there was a no significant(P>0.05) Results : The results of this study showed that Horse-back riding Simulation Machine training, after training, had meaningful difference of TUG, BBS and COPA. Conclusion : This study showed that Horse-back riding Simulation Machine training increased balance ability that resulted in enhancement of motor performance.

• The Journal of Korean Physical Therapy
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• 제27권1호
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• pp.24-29
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• 2015

Purpose: The purpose of this study was to investigate the effect of lower limb training using a sliding rehabilitation machine on the foot motion and stability in stroke patients. Methods: Thirty participants were allocated to two groups: Training group (n=15) and Control group (n=15). Subjects in the control group received physical therapy for 30 minutes, five times per week, and those in the training group received lower limb training using a sliding rehabilitation machine for 30 minutes, five times per week, with physical therapy for 30 minutes, five times per week, during a period of six weeks. Heel rotation, hallux stiffness, foot balance, metatarsal load, toe out angle, and subtalar joint flexibility were measured by RS-scan. Results: Significant improvement of the foot motion (hallux stiffness, meta load) and the foot stability (toe out angle, subtalar joint flexibility) was observed in the training group. Conclusion: This study demonstrated that lower limb training using a sliding rehabilitation machine is an effective intervention to improve the foot motion and stability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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• pp.1516-1539
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• 2022

This article shows a set of physical information fusion IoT systems that we designed for smart buildings. Its essence is a computer system that combines physical quantities in buildings with quantitative analysis and control. In the part of the Internet of Things, its mechanism is controlled by a monitoring system based on sensor networks and computer-based algorithms. Based on the design idea of the agent, we have realized human-machine interaction (HMI) and machine-machine interaction (MMI). Among them, HMI is realized through human-machine interaction, while MMI is realized through embedded computing, sensors, controllers, and execution. Device and wireless communication network. This article mainly focuses on the function of wireless sensor networks and MMI in environmental monitoring. This function plays a fundamental role in building security, environmental control, HVAC, and other smart building control systems. The article not only discusses various network applications and their implementation based on agent design but also demonstrates our collaborative information fusion strategy. This strategy can provide a stable incentive method for the system through collaborative information fusion when the sensor system is unstable in the physical measurements, thereby preventing system jitter and unstable response caused by uncertain disturbances and environmental factors. This article also gives the results of the system test. The results show that through the CPS interaction of HMI and MMI, the intelligent building IoT system can achieve comprehensive monitoring, thereby providing support and expansion for advanced automation management.

• 대한물리의학회지
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• 제3권4호
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• pp.235-246
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• 2008

Purpose : The purpose of this study was to evaluate the effects of indoor horseback-riding machine(SLIM $RIDER^{(R)}$) exercise on balance of the elderly with dementia. Methods : Subjects over 65 years of age in the nursing home were divided into three groups : Alzheimer's dementia group(n=7), vascular dementia group(n=6), and general elderly group(n=6). All groups(n=19) practiced indoor horseback-riding machine exercise for 20 min a day, three days a week during 6 weeks, and their balance were evaluated at before and 2, 4, 6 weeks after intervention, using the BPM. The level of statistical significance was .05. Results : After the 4weeks indoor horseback-riding machine exercise, balance was significantly increased in the all groups(p<.05). Conclusion : Indoor Horseback-riding machine exercise had a positive effect on subjects' balance.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.147-158
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• 2022

Cloud Computing offers flexible, on demand, ubiquitous resources for cloud users. Cloud users are provided computing resources in a virtualized environment. In order to meet the growing demands for computing resources, data centres contain a large number of physical machines accommodating multiple virtual machines. However, cloud data centres cannot utilize their computing resources to their total capacity. Several policies have been proposed for improving energy proficiency and computing resource utilization in cloud data centres. Virtual machine placement is an effective method involving efficient mapping of virtual machines to physical machines. However, the availability of many physical machines accommodating multiple virtual machines in a data centre has made the virtual machine placement problem a non deterministic polynomial time hard (NP hard) problem. Metaheuristic algorithms have been widely used to solve the NP hard problems of multiple and conflicting objectives, such as the virtual machine placement problem. In this context, we presented essential concepts regarding virtual machine placement and objective functions for optimizing different parameters. This paper provides a taxonomy of metaheuristic algorithms for the virtual machine placement method. It is followed by a review of prominent research of virtual machine placement methods using meta heuristic algorithms and comparing them. Finally, this paper provides a conclusion and future research directions in virtual machine placement of cloud computing.

• 펄프종이기술
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• 제44권2호
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• pp.1-7
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• 2012

Hanji made of mulberry fibers has the lower printability due to their long fiber length, the diffusible property of ink, and low smoothness. This study was carried out to analyze the physical and optical properties of machine-made Hanji controlled by the different contents of paper mulberry 20, 40, 60, 80 and 100%. In this study, the results of comparing machine-made Hanji controlled by the different contents of $Paper$ $mulberry$ with commercial paper and inkjet coated paper are as following: Tearing strength of machine-made Hanji is higher than domestic paper and inkjet coated paper. By increasing paper mulberry contents of machine-made Hanji appeared that tensile strength increased and smoothness gradually decreased. Printability of machine-made Hanji is less than domestic paper and inkjet coated paper. However, there were significant possibility to use for printing paper.

• 한국섬유공학회:학술대회논문집
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• 한국섬유공학회 2003년도 The Korea-Japan Joint Symposium
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• pp.39-40
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• 2003

This research surveys the effects of POY physical properties and processing conditions of belt texturing machine to the draw textured yarns. The various textured yarns are made with variation of 1st heater temperature, draw ratio and velocity ratio, and the physical properties of these specimens such as yarn linear density, tensile properties and wet and dry thermal shrinkages are measured and analyzed with POY physical properties and processing conditions of texturing machine. Especially yarn mechanical properties of DTY are analysed with the variation of untwisting tension (T$_2$) on the untwisting part in DTY process and thin and thick DTY yam model are proposed with surging phenomena in DTY process.

• 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.

• 한국환경보건학회지
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• 제27권1호
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• pp.14-19
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• 2001

The physical and chemical transformation and reduction degree of food waste were investigated in a food waste reduction machine using thermophilic bacteria. The first operation of the reduction machine for grain, vegetables, fishes and flesh wastes proceeded during three weeks. The first and second reduction percentages of the wastes were 98.3% and 93.2%, respectively. The residue of food waste was composed of fruits, fish, and vegetables. The temperature distribution of the reduction machine ranged between 30 and 6$0^{\circ}C$ appropriate for growth of thermophilic bacteria. At initial stage the pH in the reduction machine decreased with organic acids produced, but increased as the organic acids decomposed by different thermophilic bacteria. In the reduction machine, the moisture content of the food waste was reduced from 80-90% to 10-20% after 24 hours, and the salinity of residue was 0.29% after the second operation. The degree of odor was most high between 2 and 4 hours.