• Journal of Korean Academy of Nursing
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• v.18 no.3
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• pp.239-244
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• 1988

The purpose of this study was to identify the accuracy rates(hit ratio) which mean the degree of concordance between pain rating scale differences over time & subjective comparisons. Subjective comparisons mean the responses to the question “how does the pain you are now experiencing compare with the one at the time of the assessment yesterday\ulcorner” Answers to this question were translated into ‘greater’, ‘same’, or ‘less’. KPRS(Korean Pain Rating Scale) was developed through 4 consecutive studies to assess pain extensively & accurately by Lee etc. VAS(Visual Analogue Scale) was reported as valid & veliable measure for the intensity of pain by many researchers. Thirty hospitalized patients with complaints of Headache were partispated in this study during the period from May 1 to July 31, 1987. In conclusion, the accuracy rates of KPRS and VAS were 60%, 67%, respectively.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.9-15
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• 2017

This paper presents an efficient FTL for NAND flash based SSDs. Address translation information of page mapping based FTLs is stored on flash memory pages and address translation cache keeps frequently accessed entries. The proposed FTL of this paper reduces response time by considering both of temporal and spacial localities of page access patterns in translation cache management. The localities of several well-known traces are evaluated and determine the structure of the cache for high hit ratio. A simulation with several well-known traces shows that the presented FTL reduces response time in comparison to previous FTLs and can be used with relatively small size of caches.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.13-17
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• 2003

본 논문에서는 낮은 대역폭, 높은 지연, 그리고 잦은 네트워크 단절로 인한 모바일 컴퓨팅 환경의 문제점들을 해결하기 위한 효과적인 캐시 적재 기법으로서 협업 추천 기반의 데이터 마이닝 전략을 제안하였다. 캐시 적재가 모바일 클라이언트의 이러한 문제점들을 해결하기 위한 효율적인 방법이 된다는 기존의 연구는 많이 진행되어 왔다. 하지만 모바일 컴퓨터의 요구에 대한 이력 정보만을 이용한 기존의 연구는 모바일 클라이언트가 필요로 하는 모든 정보 요구를 만족하지 못하였다. 특히 저장 공간의 제약을 갖는 모바일 컴퓨터의 한계 때문에 더욱 큰 어려움을 갖게 되었다. 본 연구에서는 모바일 클라이언트의 이력 정보에 대하여 데이터 마이닝 기법을 적용한 캐시 적재 기법을 제안하여 적은 캐시 용량만으로도 모바일 클라이언트의 요구를 만족할 수 있는 아이템들을 효과적으로 서비스할 수 있도록 하였다. CSIM Simulator를 이용하여 모의 데이터를 생성하여, 제안 모형의 성능 평가를 위한 실험을 수행하였다. Cache hit ratio를 이용한 객관적인 성능 평가를 통하여 제안된 모형이 모바일 클라이언트의 캐시 적재 기법으로서 우수한 성능을 보임이 확인되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04b
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• pp.643-646
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• 2001

현재의 인터넷 사용자들은 하루가 다르게 증가하고 있는 실정이다. 사용자들의 증가로 인하여 많은 네트워크의 부하가 걸리게 되는데 이는 결국 네트워크 속도 감소로 이어지고 있다. 따라서 네트워크의 속도 문제를 해결하기 위한 방법으로 많은 연구가 진행 되어 왔는데 그 중의 하나가 웹 캐쉬 방법중의 하나인 프락시(proxy) 서버를 이용하는 방법이다. 이러한 프락시 서버 관리를 위한 모니터링 도구들이 많이 상용화 되었고 기존의 프락시 서버를 관리하는 모니터링 연구에서는 프락시 서버의 캐쉬 히트율(hit ratio)이나 바이트 히트율을 높이는 방안을 제시하고자 했다. 그러나 이러한 모니터링으로는 프락시 서버의 부하(load)가 얼마나 걸리는지를 파악 할 수가 없다. 따라서 본 논문에서는 기존의 프락시 서버 모니터링 방식과 더불어 부하의 정보를 제공함으로서 부하 균등 정책이나 사용자의 성향을 파악하여 프락시 서버를 좀 더 효율적으로 관리하고자 하는 방안을 제시하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.1007-1010
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• 2003

Efficient using of web cache is becoming important factor that decide system management efficiency in web-Based system. Cache performance depends heavily on replacement algorithms, which dynamically select a suitable subset of objects for caching in a finite space. However, replacement algorithm on web cache has many differences than traditional replacement algorithm. In this paper, a web-caching algorithm is proposed for efficient operation of web base system. The algorithm is designed based on a divided scope that considered size reference characteristic and heterogeneity on web object. The performance of the algorithm is analyzed with an experiment. With the experiment results, the algorithm is compared with previous replacement algorithms, and its performance is confirmed ith an improvement of response speed.

• Journal of Information Technology Applications and Management
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• v.14 no.2
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• pp.151-168
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• 2007

The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

• Journal of the Korea Society for Simulation
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• v.12 no.2
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• pp.25-34
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• 2003

Because of explosive growth in demand for web-based multimedia applications, proper proxy caching for large multimedia object (especially video) has become needed. For a video object which is much larger in size and has different access characteristics than the traditional web object such as image and text, caching the whole video file as a single web object is not efficient for the proxy cache. In this paper, we propose a proxy caching strategy with the constant-sized segment for video file and an improved proxy cache replacement policy. Through the event-driven simulation under various conditions, we show that our proposal is more efficient than the variable-sized segment strategy which has been proven to have higher hit ratio than other traditional proxy cache strategies.

• Journal of the Korea Society for Simulation
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• v.12 no.2
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• pp.35-44
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• 2003

The effectiveness of buffer cache replacement algorithms is critical to the performance of I/O systems. In this paper, we propose the degree of inter-reference gap (DIG) based block replacement scheme that retains merits of the least recently used (LRU) such as simple implementation and good cache hit ratio (CHR) for general patterns of references, and improves CHR further. In the proposed scheme, cache blocks with low DIGs are distinguished from blocks with high DIGs and the replacement block is selected among high DIGs blocks as done in the low inter-reference recency set (LIRS) scheme. Thus, by having the effect of the partitioning the cache memory dynamically based on DIGs, CHR is improved. Trace-driven simulation is employed to verified the superiority of the DIG based scheme and shows that the performance improves up to about 175% compared to the LRU scheme and 3% compared to the LIRS scheme for the same traces.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.3
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• pp.109-116
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• 2018

SSDs that are not allowed in-place update within the allocated page cause another allocation of a new page that will replace the previous page at the moment data modification occurs. This intrinsic characteristic of SSDs requires many changes to the existing HDD-based IO theory. In this paper, we conduct a performance comparison of FTL caching strategy in perspective of cache hashing (Global vs. grouped) and caching algorithm (LRU vs. NUR) through a simulation. Experimental results show that in terms of energy consumption for flash operation the grouped management of cache is not suitable and NUR algorithm is superior to LRU algorithm. In particular, we found that the cache hit ratio of LRU algorithm is about 10% point higher than that of NUR algorithm while the energy consumption of LRU algorithm is about 32% high.

• Publications of The Korean Astronomical Society
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• v.11 no.1
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• pp.263-277
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• 1996

We have intensively carried out numerical calculations on flare predictions from the solar activity data for photospheric sunspots, chromospheric flare and plages, coronal X-ray intensities and 2800MHz radio fluxes, by using multilinear regression method. Intensities of solar flares for the next day have been predicted from the solar data between 1977-1982 and 1993-1996. Firstly, we have calculated flare predictions with the multilinear regression method, by using separate solar data in growth and decay phase of sunspot area and magnetic field strength from the whole data on solar activities. Secondly, the same operations as above have been made for the remaining data after removal of the data with large deviation from the mean calculated by the above prediction method. we have reached a conclusion that average hit ratio of correct predictions to total predictions of flares with class of M5 over has been as high as 70% for the first case and that of correct prediction number to total observation number has been shown as 61%.