• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.571-575
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• 2015

This paper propose a temporal histogram -based behavior pattern analysis algorithm to analyze the movement features of moving objects from the image inputted in real-time. For the purpose of tracking and analysis of moving objects, it needs to be performed background learning which separated moving objects from the background. Moving object is extracted as a background learning after identifying the object by using the center of gravity and the coordinate correlation is performed by the object tracking. The start frame of each of the tracked object, the end frame, the coordinates information and size information are stored and managed by the linked list. Temporal histogram defines movement features pattern using x, y coordinates based on time axis, it compares each coordinates of objects for understanding its movement features and behavior pattern. Behavior pattern analysis system based on temporal histogram confirmed high tracking rate over 95% with sustaining high processing speed 45~50fps through the demo experiment.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.175-199
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• 2019

Uncertainty means incomplete stages of knowledge of propositions due to the lack of consensus of information and existing knowledge. As the amount of academic literature increases exponentially over time, new knowledge is discovered as research develops. Although the flow of time may be an important factor to identify patterns of uncertainty in scientific knowledge, existing studies have only identified the nature of uncertainty based on the frequency in a particular discipline, and they did not take into consideration of the flow of time. Therefore, in this study, we identify and analyze the uncertainty words that indicate uncertainty in the scientific literature and investigate the stream of knowledge. We examine the pattern of biomedical knowledge such as representative entity pairs, predicate types, and entities over time. We also perform the significance testing using linear regression analysis. Seven pairs out of 17 entity pairs show the significant decrease pattern statistically and all 10 representative predicates decrease significantly over time. We analyze the relative importance of representative entities by year and identify entities that display a significant rising and falling pattern.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.307-316
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• 2009

In this paper, the spatiotemporal data mining methodology for detecting a cycle of power consumption pattern with the change of time and spatial was proposed, and applied to the power consumption data collected by GIS-AMR system with an aim to use its resulting knowledge in real world applications. First, partial clustering method was applied for cluster analysis concerned with the aim of customer's power consumption. Second, the patterns of customer's power consumption data which contain time and spatial attribute were detected by 3D cube mining method. Third, using the calendar pattern mining method for detection of cyclic patterns in the various time domains, the meanings and relationships of time attribute which is previously detected patterns were analyzed and predicted. For the evaluation of the proposed spatiotemporal data mining, we analyzed and predicted the power consumption patterns included the cycle of time and spatial feature from total 266,426 data of 3,256 customers with high power consumption from Jan. 2007 to Apr. 2007 supported by the GIS-AMR system in KEPRI. As a result of applying the proposed analysis methodology, cyclic patterns of each representative profiles of a group is identified on time and location.

• Annual Conference of KIPS
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• 2020.11a
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• pp.57-60
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• 2020

순위다중패턴매칭문제는 길이가 n인 텍스트 T와 패턴들의 집합 P' = {P₁,P₂…,P_k}가 주어졌을 때, P'에 속하는 패턴들과 상대적인 순위가 일치하는 T의 모든 부분문자열들의 위치를 찾는 문제이다. P'에서 가장 짧은 패턴의 길이가 m, 가장 긴 패턴의 길이를 $\bar{m}$, 모든 패턴들의 길이의 합을 M, q개의 연속된 문자들을 q-그램이라 할 때, 기존에 텍스트의 핑거프린트를 이용하여 순위다중패턴매칭문제를 $O(q!+nqlogq+Mlog\bar{m}+nM)$ 시간에 해결하는 알고리즘이 제시되었다. 본 논문에서는 텍스트의 핑거프린트를 활용하여 O(max(q!,M,n))개의 스레드를 이용하여 순위다중패턴매칭문제를 평균적으로 $O(\bar{m}+qlogq+n/q!)$ 시간에 해결하는 병렬 구현 방법을 제시한다. 실험 결과, n = 1,000,000, k = 1,000, m = 5, q = 3일 때, 본 논문에서 제시하는 병렬 구현 방법은 기존의 순차 알고리즘보다 약 19.8배 빠르게 수행되었다.

• Proceedings of the Materials Research Society of Korea Conference
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• 2003.03a
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• pp.68-68
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• 2003

최근의 전자부품은 고밀도 고집적화 됨에 따라 여러 가지 문제점들이 발생되고 있다. 그 중 부품이 실장되는 부분에 사용되는 솔더나 전기적 회로를 구성하는 패턴간에 금속 이온 마이그레이션(Metallic Ion Migration)이 발생하여 전기적 단락(Short)를 유발함으로써 전자제품의 치명적 고장을 유발한다. 본 연구는 이온 마이그레이션 현상을 물방울시험(Water Drop Test)을 통하여 재현함으로써 발생 메카니즘을 확인하여 발생원인을 직접적으로 관찰하고, 각 종 패턴의 거리 및 전압에 따른 발생속도의 차이를 조사하기 위하여 수행되었다. 이러한 실험을 위하여 콤 패턴(Comb Pattern)의 FR-4 재질 인쇄회로기판(PCB : Printed Circuit Board)을 사용하였으며, 사용된 전극재질로는 Cu, SnPb, Au를 사용하였고, 패턴간 거리는 0.5, 1.0, 2.0mm의 3가지 종류로 구분하였다. 또한 패턴간에 인간 된 전압은 6.5V, 15V를 인가한 후 마이그레이션이 발생되는 시간을 측정하였다. 이러한 실험으로부터 다음과 같은 결론을 얻었다. (1) 6.5V의 인가전압에서는 Cu 패턴이 대체적으로 가장 빠르게 마이그레이션이 발생하였으며, 다음으로 Au가 발생하였고, Cu와 SnPb의 발생시간은 대체적으로 근사한 값을 나타내었다. 이것은 비슷한 평형전위를 갖는 재료는 마이그레이션 발생시간이 유사하게 나타나며, 높은 (+)전위를 갖을수록 발생시간이 지연됨을 알 수 있다. (2) 15V를 인가하였을 때 패턴간격이 0.5mm인 경우 Cu, Au, SnPb의 순으로 나타났으며, 1.0mm는 SnPb, Cu, Au, 2.0mm인 경우는 SnPb, Au, Cu의 순으로 마이그레이션이 발생하였다. 인가전압이 높은 경우 초기 발생에는 큰 차이가 없지만 수지상이 발생 후 성장하는데 많은 영향을 미치는 것으로 보인다. 이것은 초기 수지상의 형성에 큰 영향을 미치는 것은 재료의 평형전위에 의한 값이 좌우하지만, 수지상이 일정길이 이상 형성된 이후에는 성장속도가 평형전위에 따른 값과는 다소 다르게 나타남을 알 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.470-476
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• 2019

The pattern locking technique applied to smart phones is a locking technique that many people use conveniently. However, the safety of pattern locking techniques is very low compared with other techniques. The pattern locking technique is vulnerable to a shoulder surfing attack, which is based on the user's input and can be interpreted by looking at the movement of the shoulder, and the smudge attack is also vulnerable due to fingerprint drag marks remaining on the mobile phone pad. Therefore, in this paper, we want to add a new security method to check the pressed time by using a thread in the pattern locking scheme to secure the vulnerability. It is divided into short, middle, and long click according to the pressing time at each point. When dragging using the technique, security performance enhances $3^n$ tiems. Therefore, even if dragging in the same 'ㄱ' manner, it becomes a completely different pattern depending on the pressing time at each point.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.177-181
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• 2009

Developing u-Public facilities for application u-City is to combine both the state-of-the art of the construction and ubiquitous computing and must be flexibly comprised of the facilities for the basic service of the building such as air conditioning, heating, lighting and electric equipments to materialize a new format of spatial planning and the public facilities inside or outside. Accordingly, in this paper we suggested the time pattern system for predicting the most basic power system loads for the basic service. To application the tim e pattern we applied SOM algorithm and k-means method and then clustered the data each weekday and each time respectively. The performance evaluation results of suggestion system showed that the forecasting system better the ARIMA model than the exponential smoothing method. It has been assumed that the plan for power supply depending on demand and system operation could be performed efficiently by means of using such power load forecasting.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.431-436
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• 2015

As a number of TV programs broadcast today, researches about TV program recommender system have been studied and many researchers have been studying recommender system to produce recommendation with high accuracy. Recommender system recommends TV program to user by using metadata like genre, plot or calculating users' preferences about TV programs. In this paper, we propose a new TV program Collaborative Filtering Recommender System that exploits viewing time pattern like viewing ratio, relation with finish time and recently viewing history to calculate preference for high-quality of recommendation. To verify usefulness of our research, we also compare our method which utilizes viewing time patterns and baseline which simply recommends TV program of user's most frequently watched channel. Through this experiments, we show that our method very effectively works and recommendation performance increases.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.147-152
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• 2020

The research is carried out to analyze the cost-effectiveness of blasting patterns with regard to the diameters and design of blasting holes. Blasting patterns for single diameter array, and mixed diameter array were comparatively analyzed with regard to drilling and charging time, and materials required. The number of blasting holes required for single array pattern and mixed array pattern were 138 and 93 holes, respectively. From the drilling time analysis, reduction in time and its efficiency of mixed pattern were 139 minutes and 25%, respectively, in comparison with single pattern. Charging time reduction and its efficiency of mixed blasting pattern were evaluated as 22.5 minutes per worker and 33%, respectively, compare to single blasting pattern. The explosive quantities of G1 and G2 required for single array patterns were 270 and 30, while those were 222 and 20 for mixed array patterns for tunnelling 4m. And single pattern required 45 more detonators than the mixed pattern. The evaluation of material required can also be positive parameter for cost reduction of tunnel construction.