• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.153-160
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• 2024

Information technology plays an important role in healthcare. The cloud has several applications in the fields of education, social media and medicine. But the advantage of the cloud for medical reasons is very appropriate, especially given the large volume of data generated by healthcare organizations. As in increasingly health organizations adopting towards electronic health records in the cloud which can be accessed around the world for various health issues regarding references, healthcare educational research and etc. Cloud computing has many advantages, such as "flexibility, cost and energy savings, resource sharing and rapid deployment". However, despite the significant benefits of using the cloud computing for health IT, data security, privacy, reliability, integration and portability are some of the main challenges and obstacles for its implementation. Health data are highly confidential records that should not be made available to unauthorized persons to protect the security of patient information. In this paper, we discuss the privacy and security requirement of EHS as well as privacy and security issues of EHS and also focus on a comprehensive review of the current and existing literature on Electronic health that uses a variety of approaches and procedures to handle security and privacy issues. The strengths and weaknesses of some of these methods were mentioned. The significance of security issues in the cloud computing environment is a challenge.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.39-48
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• 2013

A cloud system has to deal with highly variable workloads resulting from dynamic usage patterns in order to keep the QoS within the predefined SLA. Aside from the aspects regarding services, another emerging concern is to keep the energy consumption at a minimum. This requires the cloud providers to consider energy and performance trade-off when allocating virtualized resources in cloud data centers. In this paper, we propose a resource provisioning approach based on dynamic thresholds to detect the workload level of the host machines. The VM selection policy uses utilization data to choose a VM for migration, while the VM allocation policy designates VMs to a host based on its service reputation. We evaluated our work through simulations and results show that our work outperforms non-power aware methods that don't support migration as well as those based on static thresholds and random selection policy.

• Journal of the Korean Solar Energy Society
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• v.28 no.3
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• pp.1-6
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• 2008

It is necessary to estimate empirical constants in order to predict the monthly mean daily global radiation on a horizontal surface in the developing areas for alternative energy. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for any areas over Korea by calculating the regression models taking into account latitude, percentage of possible sunshine, and cloud cover. Results clearly demonstrates the reliability of the single linear equation for the estimation of global radiation, which is proposed by using percentage of possible sunshine method. When compared with the measured values, the average annual deviation falls between -3.1 to +0.6%.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.50-55
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• 2009

Images taken by geostationary satellite may be used to estimate solar irradiance fluxes at earth's surface. It is based on the empirical correlation between a satellite derived cloud index and the irradiance at the ground. For the validation, estimated solar radiation fluxes are compared with observed solar radiation fluxes at 16 sites over the Korean peninsular from January 1982 to December 2007. Estimated solar radiation fluxes show reliable results for estimating the global radiation with average deviation of -7.58 to +3.8% from the measured values and the yearly averaged horizontal global insolation of Korean peninsula was turned out to be $3.59kW/m^2/day$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.360-363
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• 2012

Recently green IT is considered as an essential element due to continuous consumption of energy and abrupt oil price. Thus, IT infrastructure is being replaced with cloud computing platform in oder to reduce server heat and energy consumption of data centers. In this paper, we implement an open source-based cloud platform and propose a resource scheduling algorithm for cloud VDI service using node clustering.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.12-15
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• 2012

Energy costs for operating and cooling computing resources in Cloud infrastructure have increased significantly up to the point where they would surpass the hardware purchasing costs. Thus, reducing the energy consumption can save a significant amount of management cost. One of major approach is removing hardware over-provisioning. In this paper, we propose a technique that facilitates power saving through reducing resource over provisioning based on virtualization technology. To this end, we use dynamic workload shaping to reschedule and redistribute job requests considering overall power consumption. In this paper, we present our approach to shape workloads dynamically and distribute them on virtual machines and physical machines through virtualization technology. We generated synthetic workload data and evaluated it in simulating and real implementation. Our simulated results demonstrate our approach outperforms to when not using no workload shaping methodology.

• New & Renewable Energy
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• v.7 no.1
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• pp.22-28
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• 2011

The surface solar radiations were calculated and analyzed with spatial resolutions (4 km and 1 km) using by GWNU (Gangneung-Wonju National University) solar radiation model. The GWNU solar radiation model is used various data such as aerosol optical thickness, ozone amount, total precipitable water and cloud factor are retrieved from Moderate Resolution Imaging Spectrometer (MODIS), Ozone Monitoring Instrument (OMI), MTSAT-1R satellite data and output of the Regional Data Assimilation Prediction System(RDAPS) model by Korea Meteorological Administration (KMA), respectively. The differences of spatial resolutions were analyzed with input data (especially, cloud factor from MTSAT-1R satellite). And the Maximum solar radiation by GWNU model were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud factor.

• Journal of the Korean Society of Safety
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• v.16 no.3
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• pp.83-88
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• 2001

This study was preformed by measuring the minimum ignition temperature of MBS according to the change of sample vessel size and the minimum ignition temperature of MBS dust cloud The minimum ignition temperature of MBS product decreased as the vessel size was large, and it was obtained in the range from $120.5^{\circ}C$ to $94.5^{\circ}C$ and the apparent activation energy was obtained with 32.94Kcal/mol. The minimum ignition temperature of MBS dust cloud was measured by using Godbert-Greenwald furnace and it was obtained at $407^{\circ}C$ with the sample of 0.4g in the air and the ignition of dust cloud was not occurred below 13% oxygen concentration.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.1-9
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• 2017

Innovations from current researches on cloud computing such as applying bio-inspired computing techniques have brought new level solutions in offloading mechanisms. With the growing trend of mobile devices, mobile cloud computing can also benefit from applying bio-inspired techniques. Energy-efficient offloading mechanisms on mobile cloud systems are needed to reduce the total energy consumption but previous works did not consider energy consumption in the decision-making of task distribution. This paper proposes the Particle Swarm Optimization (PSO) as an offloading strategy of cloudlet to data centers where each task is represented as a particle during the process. The collected tasks are classified using K-means clustering on the cloudlet before applying PSO in order to minimize the number of particles and to locate the best data center for a specific task, instead of considering all tasks during the PSO process. Simulation results show that the proposed PSO excels in choosing data centers with respect to energy consumption, while it has accumulated a little more processing time compared to the other approaches.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.6
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• pp.355-362
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• 2021

Various blast pressure calculation methods have been developed for predicting the explosion pressure of vapor cloud explosions. Empirical methods include the TNT equivalent method, and multi-energy method. The multi-energy method uses a charge strength that considers environmental factors. Although the Kinsella guideline was provided to determine the charge strength, there are limitations such as guidelines related to ignition sources. In this study, we proposed an improved charge strength guideline, by subdividing the ignition source intensity and expanding the type classification through literature analysis. To verify the improved charge strength guideline, and to compare it with the result obtained using the Kinsella guideline, four vapor cloud explosion cases which could be used to estimate the actual blast pressure were investigated. As a result, it was confirmed that the Kinsella guidelines showed an inaccurate, that is, wider pressure than the actual estimated blast pressure. However, the improved charge strength guideline enabled the selection of the intensity of the ignition source, and more subdivided types through the expansion of classification, hence it was possible to calculate the blast pressure relatively close to that of the actual case.