• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.30 no.2
• /
• pp.75-82
• /
• 2002

It is useful to detect the tracking error with an optimal view in the presence of measurement origin uncertainty. In this paper, after the investigation of the targer error dependent on the detection threshold as well as the detection and false alarm probabilities in a clutter environment, a new algorothm that optimizes the threshold of validation region for target trackinf is proposed. The performance of the algorithm is demonstrated through computer simulations.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.2
• /
• pp.1-8
• /
• 2013

TIn this paper, we propose a high performance L1 cache structure on the high clock CPU of 4GHz. The proposed cache memory consists of three parts, i.e., a direct-mapped cache to support fast access time, a two-way set associative buffer to exploit temporal locality, and a buffer-select table. The most recently accessed data is stored in the direct-mapped cache. If a data has a high probability of a repeated reference, when the data is replaced from the direct-mapped cache, the data is selectively stored into the two-way set associative buffer. For the high performance and low power consumption, we propose an one way among two ways set associative buffer is selectively accessed based on the buffer-select table(BST). According to simulation results, Energy $^*$ Delay product can improve about 45%, 70% and 75% compared with a direct mapped cache, a four-way set associative cache, and a victim cache with two times more space respectively.

• Proceedings of the Korean Information Science Society Conference
• /
• 2000.04b
• /
• pp.262-264
• /
• 2000

텍스트 문서 분류는 텍스트 형태로 주어진 문서를 종류별로 구분하는 작업으로 웹페이지 검색, 뉴스 그룹 검색, 메일 필터링 등이 분야에 응용될 수 있는 기반 작업이다. 지금까지 문서를 분류하는데는 k-NN, 신경망 등 여러 가지 기계학습 기법이 이용되어 왔다. 이 논문에서는 베이지안망을 이용해서 텍스트 문서 분류를 행한다. 베이지안망은 다수의 변수들간의 확률적 관계를 표현하는 그래프 모델로 DAG 형태인 망 구조와 각 노드에 연관된 지역확률분포로 구성된다. 그래프 모델을 사용할 경우 학습에 이용되는 각 속성들간의 관계를 사람이 알아보기 쉬운 형태로 학습할 수 있다는 장점이 있다. 실험 데이터로는 Reuters-21578 문서분류데이터를 이용했으며 베이안망의 성능은 나이브 베이즈 분류기와 비슷했다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10b
• /
• pp.324-329
• /
• 2006

Non-negative matrix factorization(NMF) 기법은 음이 아닌 값으로 구성된 데이터를 두 종류의 양의 행렬의 곱의 형식으로 분할하는 데이터 분석기법으로서, 텍스트마이닝, 바이오인포매틱스, 멀티미디어 데이터 분석 등에 활용되었다. 본 연구에서는 기본 NMF 기법에 기반하여 텍스트 문서로부터 토픽을 추출하고 동시에 이를 가시적으로 도시하기 위한 Topographic NMF (TNMF) 기법을 제안한다. TNMF에 의한 토픽 가시화는 데이터를 전체적인 관점에서 보다 직관적으로 파악하는데 도움이 될 수 있다. TNMF는 생성모델 관점에서 볼 때, 2개의 은닉층을 갖는 계층적 모델로 표현할 수 있으며, 상위 은닉층에서 하위 은닉층으로의 연결은 토픽공간상에서 토픽간의 전이확률 또는 이웃함수를 정의한다. TNMF에서의 학습은 전이확률값의 연속적 스케줄링 과정 속에서 반복적 파리미터 갱신 과정을 통해 학습이 이루어지는데, 파라미터 갱신은 기본 NMF 기반 학습 과정으로부터 유사한 형태로 유도될 수 있음을 보인다. 추가적으로 Probabilistic LSA에 기초한 토픽 가시화 기법 및 희소(sparse)한 해(解) 도출을 목적으로 한 non-smooth NMF 기법과의 연관성을 분석, 제시한다. NIPS 학회 논문 데이터에 대한 실험을 통해 제안된 방법론이 문서 내에 내재된 토픽들을 효과적으로 가시화 할 수 있음을 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.389-391
• /
• 2021

Traffic regulations are expanding to prevent traffic accidents for people's safety, but traffic accidents are not decreasing. In this study, the probability of traffic accidents occurring at a specific time and place is estimated by analyzing various factors such as weather forecast data from the Meteorological Agency, day of the week, time of day, location data, and location information. This study combines objective data on the occurrence of numerous previous traffic accidents with various additional elements not considered in previous studies to derive a more improved traffic accident probability prediction model. The results of this study can be effectively used for various transportation-related services for the safety of people.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.602-605
• /
• 1995

In this paper, we provide the new alogorithm for maneuvering target tracking in clutter environment using perception net. The perception net, as a structural representation of the sensing capabilities of a system, may supply the constraints that target must be satisfied with. The results form perception net applying to IMMPDA are compared with those obtained from IMMPDA.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.8
• /
• pp.143-149
• /
• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.6
• /
• pp.1097-1103
• /
• 2011

The Ministry of Education Science, and Technology proclamated the school curriculum of the republic of Korea at 9 August 2011. The characteristics of this curriculum are as follows; effective learning of student-centered, group of grade, group of category, concentration study, reduction of study subjects, extension of school autonomy, elective curriculum in high school. We investigate the modification of probability and statistics curriculum. And we discuss statistics education in university.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.169-174
• /
• 2018

There are many CCTV cameras connected to the video surveillance and monitoring center for the safety of citizens, and it is difficult for a few monitoring agents to monitor many channels of videos. In this paper, we propose an intelligent video surveillance system utilizing a safety map to efficiently monitor many channels of CCTV camera videos. The safety map establishes the frequency of crime occurrence as a database, expresses the degree of crime risk and makes it possible for agents of the video surveillance center to pay attention when a woman enters the crime risk area. The proposed gender classification method is processed in the order of pedestrian detection, tracking and classification with deep training. The pedestrian detection and tracking uses Adaboost algorithm and probabilistic data association filter, respectively. In order to classify the gender of the pedestrian, relatively simple AlexNet is applied to determine gender. Experimental results show that the proposed gender classification method is more effective than the conventional algorithm. In addition, the results of implementation of intelligent video security system combined with safety map are introduced.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_2
• /
• pp.1229-1238
• /
• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.