• KIEAE Journal
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• 제14권2호
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• pp.3-10
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• 2014

Impact by estimation error of hourly horizontal global solar radiation in a weather file on building energy performance was investigated in this study. There are a number of weather parameters in a given weather file, such as dry-bulb, wet-bulb, dew-point temperatures; wind speed and direction; station pressure; and solar radiation. Most of them except for solar radiation can be easily obtained from weather stations located on the sites worldwide. However, most weather stations, also including the ones in South Korea, do not measure solar radiation because the measuring equipment for solar radiation is expensive and difficult to maintain. For this reason, many researchers have studied solar radiation estimation models and suggested to apply them to predict solar radiation for different weather stations in South Korea, where the solar radiation is not measured. However, only a few studies have been conducted to identify the impact caused by estimation errors of various solar radiation models on building energy performance analysis. Therefore, four different weather files using different horizontal global solar radiation data, one using measured global solar radiation, and the other three using estimated global solar radiation models, which are Cloud-cover Radiation Model (CRM), Zhang and Huang Model (ZHM), and Meteorological Radiation Model (MRM) were packed into TRY formatted weather files in this study. These were then used for office building energy simulations to compare their energy consumptions, and the results showed that there were differences in the energy consumptions due to these four different solar radiation data. Additionally, it was found that using hourly solar radiation from the estimation models, which had a similar hourly tendency with the hourly measured solar radiation, was the most important key for precise building energy simulation analysis rather than using the solar models that had the best of the monthly or yearly statistical indices.

• The Journal of the Korea Contents Association
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• 제11권2호
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• pp.162-169
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• 2011

This paper proposed an efficient game character design method through semiotic analysis of character. It inquired into the characteristics of game character of various contents characters, added the concept of "Iconic abstraction" of Scott McCloud to its characteristics, and studied on the relation between the character and the semiotics. The semiotic character from the factual character, seized the strong and weak point of each character, and divided them in the designer's character production process and gamer's character recognition process step by step for its semiotic interpretation. As a result, two processes were reversely progressed, and the character designing process considering this gamer's semiotic recognition process is expected to be the efficient character design element that can deliver the whole characteristics of game contents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• Journal of The Korean Astronomical Society
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• 제37권4호
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• pp.285-288
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• 2004

Near-infrared imaging photometry supplemented by optical spectroscopy and narrow-band imaging of the H II region Sh 2-128 and its environment are presented. This region contains a developed H II region and the neighboring compact H II region S 128N associated with a pair of water maser sources. Midway between these, the core of a CO cloud is located. The principal ionizing source of Sh 2-128 is an 07 star close to its center. A new spectroscopic distance of 9.4 kpc is derived, very similar to the kinematic distance to the nebula. This implies a galactocentric distance of 13.5 kpc and z = 550 pc. The region is optically thin with abundances close to those predicted by galactocentric gradients. The $JHK_s$ images show that S 128N contains several infrared point sources and nebular emission knots with large near-infrared excesses. One of the three red Ks knots coincides with the compact H II region. A few of the infrared-excess objects are close to known mid- and far-infrared emission peaks. Star counts in J and $K_s$ show the presence of a small cluster of B-type stars, mainly associated with S 128N. The $JHK_s$ photometric properties together with the characteristics of the other objects in the vicinity suggest that Sh 2-128 and S 128N constitute a single complex formed from the same molecular cloud, with ages ${\~}10^6$ and < $3 {\times} 10^5$ years respectively. No molecular hydrogen emission was detected at 2.12 ${\mu}m$. The origin of this remote star forming region is an open problem.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제48권1호
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• pp.8-15
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• 2011

In this paper, we propose a new structure modeling algorithm from 3D cloud points of terrestrial LADAR data. Terrestrial LIDAR data have various obstacles which make it difficult to apply conventional algorithms designed for air-borne LIDAR data. In the proposed algorithm, the field data are separated into several clusters by adopting the structure extraction method which uses color information and Hough transform. And cluster based Delaunay triangulation technique is sequentially applied to model the artificial structure. Each cluster has its own priority and it makes possible to determine whether a cluster needs to be considered not. The proposed algorithm not only minimizes the effects of noise data but also interactively controls the level of modeling by using cluster-based approach.

• Journal of the Korean Society of Costume
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• 제59권8호
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• pp.132-151
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• 2009

All of 132 kinds of fabrics are used in excavated costume from the Dongrae Jung's Tomb. Classified by its materials, it is divided into small groups as follows: 58 pieces of silk tabby 43.9%, 2 of filament silk tabby 1.5%, 14 of thin filament silk tabby 10.6%, 19 of spun yarn silk 14.4%, 4 of twill without a pattern 3.0%, 8 of patterned silk tabby 6.1%, 23 of satin damask 17.4%, 1 of damask with supplementary gold thread 0.8%, 2 of mixture fabric with silk and cotton 1.5%, and 1 of ramie fabric 0.8%. Classified by ways of weaving: 96 pieces of plain weave 73%, 23 of satin weave 17%, 8 of patterned silk tabby consisting of plain weave material and twill weave pattern-6%, 4 of twill weave 3%, and 1 of compound weave 1 %. In point of patterns, the most often used ones are plant patterns such as lotus patterns, peony patterns, plum blossom patterns, flowers representing seasons patterns, and small flower patterns. For animal patterns, it has phoenix patterns designed together with flowers representing seasons patterns. And for natural scenery patterns, it shows cloud patterns with treasures patterns together. For object patterns, it also shows treasures patterns mixed with cloud or lotus together. For geometrical patterns, it has rhomboid patterns and 卍 character patterns; some show only rhomboid patterns and others show material patterns of 卍 character patterns blended together with fruit, lotus, etc.

• Journal of Advanced Navigation Technology
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• 제17권6호
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• pp.816-822
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• 2013

In modern networks, data rate is getting faster and transferred data is extremely increased. At this point, the malicious codes are evolving to various types very fast, and the frequency of occurring new malicious code is very short. So, it is hard to collect/analyze data using general networks with the techniques like traditional intrusion detection or anormaly detection. In this paper, we collect and analyze the data more effectively with cloud environment than general simple networks. Also we analyze the malicious code which is similar to real network's malware, using botnet server/client includes DNS Spoofing attack.

• Korean Medical Education Review
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• 제18권2호
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• pp.51-57
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• 2016

This literature review explores artificial intelligence (AI) technology trends and IBM Watson health and medical references. This study explains how healthcare will be changed by the evolution of AI technology, and also summarizes key technologies in AI, specifically the technology of IBM Watson. We look at this issue from the perspective of 'information overload,' in that medical literature doubles every three years, with approximately 700,000 new scientific articles being published every year, in addition to the explosion of patient data. Estimates are also forecasting a shortage of oncologists, with the demand expected to grow by 42%. Due to this projected shortage, physicians won't likely be able to explore the best treatment options for patients in clinical trials. This issue can be addressed by the AI Watson motivation to solve healthcare industry issues. In addition, the Watson Oncology solution is reviewed from the end user interface point of view. This study also investigates global company platform business to explain how AI and machine learning technology are expanding in the market with use cases. It emphasizes ecosystem partner business models that can support startup and venture businesses including healthcare models. Finally, we identify a need for healthcare company partnerships to be reviewed from the aspect of solution transformation. AI and Watson will change a lot in the healthcare business. This study addresses what we need to prepare for AI, Cognitive Era those are understanding of AI innovation, Cloud Platform business, the importance of data sets, and needs for further enhancement in our knowledge base.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1164-1183
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• 2019

The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

• The Journal of the Korea institute of electronic communication sciences
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• 제14권4호
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• pp.671-678
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• 2019

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data is shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the web using Daum Map API and Highcharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.