• 대한전자공학회논문지SP
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• 제42권2호
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• pp.37-48
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• 2005

본 논문에서는 적외선 영상에서 밝기변화를 예측하기 어려운 일정한 크기의 관심 물체를 검출하기 위하여, 밝기순위 특징과 이론 이용한 물체식별기법을 제안한다. 제안하는 밝기순위 특징은 밝기값의 분포가 균일하도록 영상을 정규화하여 나타낸 것으로, 적외선 영상과 같이 검출대상 물체의 밝기분포를 쉽게 예측하기 어려운 경우에 적합한 특징이다. 제안하는 식별기법은 주어진 후보영역이 검출대상 물체의 학습영상들에 대해 밝기순위가 부합하는 정도를 수치화하여 각각의 후보영역을 물체와 비물체로 식별한다 제안하는 기법을 통하여 별도의 후보영역 선정과정 없이도 일정한 크기의 관심 물체에 대해 화소단위의 검출결과를 획득할 수 있다. 실험에서는 적외선 자동차 영상을 이용하여 밝기순위특징이 적외선 영상 내 물체식별에 적합함을 보이고, 잡음 및 물체의 크기변화, 기울어짐이 존재하는 상황에서의 검출결과를 보인다.

• Journal of Information Science Theory and Practice
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• 제1권3호
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• pp.6-11
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• 2013

A new explanation, using exponential functions, is given for the S-shaped functional relation between the mean citation score and the proportion of top 10% (and other percentages) publications for the 500 Leiden Ranking universities. With this new model we again obtain an explanation for the concave or convex relation between the proportion of top $100{\theta}%$ publications, for different fractions of ${\theta}$.

• Nuclear Engineering and Technology
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• 제55권12호
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• pp.4408-4425
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• 2023

Alarm flood due to abnormality propagation is the most difficult alarm overloading problem in nuclear power plants (NPPs). Root-cause analysis is suggested to help operators in understand emergency events and plant status. Multilevel Flow Modeling (MFM) has been extensively applied in alarm management by virtue of the capability of explaining causal dependencies among alarms. However, there has never been a technique that can identify the actual root cause for complex alarm situations. This paper presents an automated root-cause analysis system based on MFM. The causal reasoning algorithm is first applied to identify several possible root causes that can lead to massive alarms. A novel root-cause ranking algorithm can subsequently be used to isolate the most likely faults from the other root-cause candidates. The proposed method is validated on a pressurized water reactor (PWR) simulator at HAMMLAB. The results show that the actual root cause is accurately identified for every tested operating scenario. The automation of root-cause identification and ranking affords the opportunity of real-time alarm analysis. It is believed that the study can further improve the situation awareness of operators in the alarm flooding situation.

• Journal of Multimedia Information System
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• 제1권1호
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• pp.67-75
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• 2014

Nowadays as video services grow rapidly, it is important for the service providers to provide customized services. Video ranking plays a key role for the service providers to attract the subscribers. In this paper we propose a weekly video ranking mechanism based on the quantified user engagement. The traditional QoE ranking mechanism is relatively subjective and usually is accomplished by grading, while QoS is relatively objective and is accomplished by analyzing the quality metrics. The goal of this paper is to establish a ranking mechanism which combines the both advantages of QoS and QoE according to the third-party data collection platform. We use data mining method to classify and analyze the collected data. In order to apply into the actual situation, we first group the videos and then use the regression tree and the decision tree (CART) to narrow down the number of them to a reasonable scale. After that we introduce the analytic hierarchy process (AHP) model and use Elo rating system to improve the fairness of our system. Questionnaire results verify that the proposed solution not only simplifies the computation but also increases the credibility of the system.

• 전자공학회논문지CI
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• 제46권5호
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• pp.14-28
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• 2009

PageRank 알고리즘은 구글(Google)등의 검색 엔진에서 웹 페이지의 순위(rank)를 정하는 중요한 요소이다. PageRank 알고리즘의 순위 품질(ranking quality)을 향상시키기 위해 많은 변형 알고리즘들이 제안되었지만 어떤 변형 알고리즘(혹은 변형 알고리즘들간의 조합)이 가장 좋은 순위 품질을 제공하는지가 명확하지 않다. 본 논문에서는 PageRank 알고리즘의 잘 알려진 변형 알고리즘들과 그들 간의 조합들에 대해 순위 품질을 평가한다. 이를 위해, 먼저 변형 알고리즘들을 웹의 링크(link) 구조를 이용하는 링크기반 방법(Link-based approaches)과 웹의 의미 정보를 이용하는 지식기반 방법(Knowledge-based approaches)으로 분류한다. 다음으로, 이 두 가지 방법에 속하는 알고리즘들을 조합한 알고리즘들을 제안하고, 변형 알고리즘들과 그들을 조합한 알고리즘들을 구현한다. 백만 개의 웹 페이지들로 구성된 실제 데이터에 대한 실험을 통해 PageRank의 변형 알고리즘들과 그들 간의 조합들로부터 가장 좋은 순위 품질을 제공하는 알고리즘을 찾는다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4142-4159
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• 2019

We have developed composite measures of supercomputer technology, reflecting various factors of supercomputers using Martino's scoring model. CPUs, accelerators, memory, interconnection networks, and power consumption are chosen as factors of the model. The weight values of the factors are derived based on a survey of 129 domestic and international experts. The measured values are then standardized to integrate measurement units of the factors in the model. This model has been applied to 50 supercomputers, and rank correlation analysis was performed using representative measures. As a consequence, the ranking drastically changes except for the 1st and 2nd supercomputers on the TOP500. In addition, the characteristics of memory and interconnection networks influence the ranking, and the results demonstrate that the proposed model has low correlations with HPL and HPCG but a high correlation with Green500. This indicates that power consumption is an important factor that has a significant effect on the measures of supercomputer technology. In addition, it is determined that the differences between the HPL ranking and the proposed model ranking are influenced by power consumption, CPU theoretical peak performance, and main memory bandwidth in order of significance. In conclusion, the composite measures proposed in this study are more suitable for comprehensively describing supercomputer technology than existing performance measures. The findings of this study are expected to support decision making related to management and policy in the procurement and operation of supercomputers.

• International Journal of Advanced Culture Technology
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• 제5권4호
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• pp.51-56
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• 2017

In every Summer and Winter, there open soccer transfer markets. And these markets draw huge attention from soccer fans and other ordinary people all around world. This phenomenon might indicate great interest of people from the amount of news, blog articles, public messages and replies from online community and forums about popular players and clubs of many leagues. Especially, transfer markets in the year 2017 have generated many gossips than before. In this research, we performed keyword analysis and ranking of news and messages collected and analyzed from online news sites and online forum sites, in order to investigate who and what clubs are mainly discussed.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2022년도 제34회 한글 및 한국어 정보처리 학술대회
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• pp.442-446
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• 2022

자동 음성 인식(Automatic Speech Recognition) 혹은 Speech-to-Text(STT)는 컴퓨터가 사람이 말하는 음성 언어를 텍스트 데이터로 전환하는 일련의 처리나 기술 등을 일컫는다. 음성 인식 기술이 다양한 산업 전반에 걸쳐 적용됨에 따라 높은 수준의 정확도와 더불어 다양한 분야에 적용할 수 있는 음성 인식 기술에 대한 필요성이 점차 증대되고 있다. 다만 한국어 음성 인식의 경우 기존 선행 연구에 비해 예사말/높임말의 구분이나 어미, 조사 등의 인식에 어려움이 있어 음성 인식 결과 후처리를 통한 성능 개선이 중요하다. 따라서 본 논문에서는 N-Best 음성 인식 결과가 구성되었을 때 Re-ranking을 통해 한국어 음성 인식의 성능을 개선하는 모델을 제안한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.455-458
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• 2003

The variety of document ranking algorithms have developed to provide efficient mining results for user's query on the web environment. The typical ranking algorithms are the Vector-Space Model based on the text, PsgeRank and HITS algorithms based on the hyperlink structures and other several improvement algorithms. All these are for the user's convenience and preference. However, these algorithms are usually developed on then Horizontal and non-hierarchial web environments and are not suitable for the hierarchial web environments such as enterprise and defense networks. Thus, we must consider the special environment factors in order to improve the ranking algorithms. In this paper, we analyze the several typical algorithms used by hyperlink structures on the web environment. We, then suggest a configuration of the hierarchical web environment and also give the relations between agents of the web mining system. Next, we propose an improved ranking algorithm suitable to this kind of special environments. The proposed algorithm is considered both the hyperlink structures of the documents and the location of the user of the hierarchical web.

• 산업경영시스템학회지
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• 제42권1호
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• pp.87-94
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• 2019

A wireless sensor network is emerging technology and intelligent wireless communication paradigm that is dynamically aware of its surrounding environment. It is also able to respond to it in order to achieve reliable and efficient communication. The dynamical cognition capability and environmental adaptability rely on organizing dynamical networks effectively. However, optimally clustering the cognitive wireless sensor networks is an NP-complete problem. The objective of this paper is to develop an optimal sensor network design for maximizing the performance. This proposed Ranking Artificial Bee Colony (RABC) is developed based on Artificial Bee Colony (ABC) with ranking strategy. The ranking strategy can make the much better solutions by combining the best solutions so far and add these solutions in the solution population when applying ABC. RABC is designed to adapt to topological changes to any network graph in a time. We can minimize the total energy dissipation of sensors to prolong the lifetime of a network to balance the energy consumption of all nodes with robust optimal solution. Simulation results show that the performance of our proposed RABC is better than those of previous methods (LEACH, LEACH-C, and etc.) in wireless sensor networks. Our proposed method is the best for the 100 node-network example when the Sink node is centrally located.