• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.49-63
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• 1997

We consider the problem of classifying a p x 1 observation into one of two multivariate normal populations when the training smaples contain a block of missing observation. A new classification procedure is proposed which is a linear combination of two discriminant functions, one based on the complete samples and the other on the incomplete samples. The new discriminant function is easy to use.

• The Journal of Internal Korean Medicine
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• v.21 no.4
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• pp.687-691
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• 2000

In this case report regarding one patient with complete left bundle branch block and mild hypokinesia of left ventricle, who had cebebellar infarction and therefore showed the symptoms of cerabellar dyskinesia followed by dyspnea, chest discomfortness, insomnia and dry cough. From the point of oriental diagnostic criteria, the patient s clinical conditions were all classified as $^{\circ}AEdeprivation$ of kidney essence' and treated accordingly. He showed no change in EKG monitoring but above symptoms were removed markedly after following treatment. Further elaboration of oriental diagnostic classification could possibly lead to the fundamental treatment.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.193-206
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• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.1
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• pp.73-80
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• 2014

Designing test case flows for water crossing operation of a wheeled vehicle is a new attempt for which very limited experiences exist. In this paper, a Function Flow Block Diagram(FFBD) and a Classification Tree Method(CTM) were combined to see if this method is viable to generate the test case flows at the functional analysis stage. It was found that this method can be practically used for the very complicated test case generation.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1851-1854
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• 2003

This paper suggests an algorithm which can retrieval images using correlations between the region classification of spatial image and the wavelet transform even though the images are rotated in a ${\pm}$90 degree arc. Owing to this proposed method, it was confirmed from experiments that the search about the whole image is not processed and only a few amount of informations are saved by using the mathematical statistics from the block map and transformed band which is resulted from region classification, and by performing the image search based on these, the improvement of search speed and the efficient search can be done.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.683-688
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• 2010

The ability to navigate autonomously in off-road terrain is the most critical technology needed for Unmanned Ground Vehicles(UGV). In this paper, we present a method for vision-based terrain cover classification using DCT features. To classify the terrain, we acquire image from a CCD sensor, then the image is divided into fixed size of blocks. And each block transformed into DCT image then extracts features which reflect frequency band characteristics. Neural network classifier is used to classify the features. The proposed method is validated and verified through many experiments and we compare it with wavelet feature based method. The results show that the proposed method is more efficiently classify the terrain-cover than wavelet feature based one.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.369-376
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• 2002

Although LRU is not adequate for database that has non-uniform reference pattern, it has been adopted in most database systems due to the absence of the proper alternative. We analyze database block reference pattern with the realistic database trace. Based on this analysis, we propose a new cache replacement policy. Trace analysis shows that extremely non-popular blocks take up about 70 % of the entire blocks. The influence of recency on blocks' re-reference likelihood is at first strong due to temporal locality, however, it rapidly decreases and eventually becomes negligible as stack distance increases. Based on this observation, RCB(Reference Characteristic Based) cache replacement policy, which we propose in this paper, classifies the entire blocks into four block groups by blocks' recency and re-reference likelihood, and operates different priority evaluation methods for each block group. RCB policy evicts non-popular blocks more quickly than the others and evaluates the priority of the block by frequency that has not been referenced for a long time. In a trace-driven simulation, RCB delivers a better performance than the existing polices(LRU, 2Q, LRU-K, LRFU). Especially compared to LRU. It reduces miss count by 5~l2.7%. Time complexity of RCB is O(1), which is the same with LRU and 2Q and superior to LRU-K(O(log$_2$N)) and LRFU(O(l) ~ O(log$_2$N)).

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.73-79
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• 2003

To manage national territory and cadastral data efficiently, accuracy and cost-efficiency in cadastral boundary surveying is inevitable. The efficient management of cadastral data is a very important element in national land management. Survey techniques are being introduced. Recently, improvements in survey techniques have been made with the development of satellite surveying, Allowing accurate and fast surveys. If we can calculate the output accurately in real-time in survey fields, it will open a new method in cadastral detail surveying. According to the classification on Law of cadastral surveying, Cadastral surveying can be divided into cadastral control point surveying and cadastral detail surveying. The control point survey can be divided into cadastral triangulation surveying and cadastral traverse surveying. The detailed survey is usually perform by plane surveying. Among these, cadastral detail surveying will be reviewed in this study. In this study, the combination of the satellites, such as US managed GPS and Russian managed GLONASS was used. In the satellite survey in downtown, data interruption symptoms arose(according to the mask angle of the satellite). Therefore; we combined the satellites to get date more accurately. A block of Haewoondae New City in Busan, Korea, which has Numerical Cadastral Law was selected as the sample area for this study. Block II and III are surrounded by high rise apartments. One side of Block I and IV is level ground and the other side is full of high rise apartments. Especially, Block II is surrounded by high rise apartment houses with 20 meters width. In the results of the study Block II did not satisfy the allowable precision, while Block I, II and IV satisfied the allowable precision of the enforcement regulations of Cadastral Law. Therefore, it is judged that the traditionally used Total Station method should be used for supplementary survey on Block II, in stead.

• The Korean Journal of Pain
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• v.8 no.2
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• pp.272-278
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• 1995

Headache is a common disease of the general population. But the main problem in any study of headache has been that of defining the disease entities. In 1988, the Headache Classification committee of the International Headache Society introduced operational diagnostic criteria for all headache disorders into 13 major group; migraine, tension-type headache, cluster headache and chronic paroxysmal hemicrania etc. Sjaastad was the first to describe "cervicogenic headache", one of various head pain syndromes that probably originate in the cervical spine. Between March 1995 and June 1995, we studied 78 out-patients of the Department of Neuro pain clinic, Sanggye Paik Hospital, Inje university. We divided the patients into three study group: Fifty-three patients with tension-type headache, 13 with cervicogenic headache, and 12 with migraine headache. The reponse of trigger point injection and $C_2$-ganglion block in patients was investigated. We paid particular attention to the response of trigger point injection in patients of the three group. The effect of trigger point injection was more marked in tension-type headache group than in the other categories. The pain reduction after $C_2$-ganglion block was more marked in cervicogenic headache group than in the others.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.105-111
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• 2009

In this paper, we propose a locally adaptive image restoration method based on nonlinear extrapolation in frequency domain. In general, the conventional method causes ringing artifacts on the object boundary. To solve this problem, we introduce an improved restoration method which considers textures of an image block. In the proposed method, a blurred image is divided into several blocks, and each block is classified into three groups; simple, one edge, and complex blocks according to the contained texture. Depending on the classification result, adaptive nonlinear extrapolation is applied to each block in a blurred image. Experimental results show that the proposed algorithm can achieve higher quality image in both subjective and objective views as compared with the conventional method.