• KIEAE Journal
• /
• 제10권5호
• /
• pp.77-85
• /
• 2010

The library is the most frequently utilized building on campus, but, it has been reported to be a facility most vulnerable to crime. However, almost no study has been conducted on crime in the library, which implies a need for research on the subject. The purpose of this study is specifically twofold. First, this study will suggest components of environmental plan to prevent fear over library crime on campus. Second, the study seeks to reveal the correlation between use per library space and fear of crime. This has been analyzed by conducting a survey among current university students, and the survey includes the following three details: first, fear over day/night crime per library space; second, components of environmental plan to prevent fear over crime per library space; third, level of use per library space on campus. The results of study show that fear of crime has low relation with crime occurrence, fear per library space is higher during the night than during the day, and the space where the fear level is usually high is the service facility. There is a difference for each space in terms of important components of environmental plan to prevent crime per library space, and installation of security device is most important. One must consider a plan for a crime safe environment regarding library space where the level of use during the day is low.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2005년도 추계종합학술대회
• /
• pp.658-661
• /
• 2005

클라이언트/서버 기반 방식의 컨텐츠 전송 시스템은 서버로 작업요청이 많아질 경우에는 서버에 처리부하가 집중되는 병목현상으로 인하여 시스템이 마비 되는 취약점을 가지고 있다. 그러나 인터넷 사용자의 폭발적인 증가와 컨텐츠 품질 향상 요구로 인하여 서버의 증설만으로는 한계에 이르렀다. 그러므로 이러한 문제점들을 개선하기 위해 P2P 기반 컴퓨팅방식을 사용한다. 본 논문에서는 컴퓨팅 자원의 공유를 목적으로 하는 P2P 컴퓨팅 환경에서 유휴 컴퓨팅 자원을 이용하여 교육 콘텐츠 전송 시스템을 설계하고 구현한다. 제안된 시스템은 인터넷 전송뿐만 아니라 위성 채널을 통해 콘텐츠를 전송할 수 있도록 시스템을 구현하고, 실시간 강의와 비실시간 강의의 콘텐츠를 모두 전송하도록 설계한다.

• 한국환경복원기술학회지
• /
• 제8권5호
• /
• pp.28-38
• /
• 2005

The De-militarized Zone(DMZ) on the Korean Peninsula is ecologically conserved and naturally developed as access to the area has been controlled in the past five decades. As a result, biodiversity and wetlands are developed very well, but they have not been sufficiently surveyed due to land mines and security reasons. Focusing on the Kyongui Line area in Paju DMZ, this study aims at examining the status of forested wetlands in detail through an on-site survey and understanding the features of forested wetlands in DMZ. The forested wetlands of Paju Kyongui Line area are inhabited by naturally grown Salix koreensis Andress. and Acer ginnale Maxim. and affected by Sacheon Basin region extensively. As the topography of this region is created of inundated area and gentle ground, it is easily affected by hydrology and irrigation and has ideal conditions as forested wetlands. In addition, forest wetlands in this area were used as agricultural land in the past but now transformed into palustrine forested wetlands after being deserted for long time. However, as construction of roads and railways increasingly blocks water paths, the coverage of Robinia pseudoacacia L. and Amorpha fruticosa L. is on the rise, which indicates that forestedwetlands are gradually becoming inland over time.

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2004년도 춘계종합학술대회
• /
• pp.255-258
• /
• 2004

정보 보호 응용에 새로운 이슈가 되고 있는 ECC 공개키 암호 알고리즘은 유한체 차원에서의 효율적인 연산처리가 중요하다. 직렬 유한체 곱셈기의 근간은 Mastrovito의 직렬 곱셈기에서 유래한다. 본 논문에서는 polynomial basis 방식을 적용하고 식을 유도하여 Mastovito의 직렬 유한체 곱셈방식의 3배 성능을 보이는 유한체 곱셈기를 제안하고, HDL로 기술하여 기능을 검증하고 성능을 평가한다. 설계된 3배속 직렬 유한체 곱셈기는 부분합을 생성하는 회로의 추가만으로 기존 직렬 곱셈기의 3배의 성능을 보여주었다.

• 대한조선학회논문집
• /
• 제46권6호
• /
• pp.659-666
• /
• 2009

Recently, there are several problems in space, contiguity and facility of the existing harbors issued due to the trend of enlarging the container capacity of the large container vessel, the Mobile Harbor has been proposed conceptually as an effective solution for those problems. This concept is a kind of transfer loader of the containers from the large container ship, which is a floating barge with a catamaran type in the underwater part, and so prompt maneuverability and work effectiveness. For the safe mooring of two floating bodies, a container and the mobile harbor, in the near sea apart from the quay, a robot arm mooring facility specially devised would be designed and verified through comparison study under various environmental sea condition in the inner and outer harbor. DP system (Dynamic Positioning System) using the azimuth thruster and a pneumatic fender, etc, will be considered as a next research topic for the mooring security of multi-body floaters.

• Nuclear Engineering and Technology
• /
• 제53권12호
• /
• pp.4072-4079
• /
• 2021

This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.

• 농촌계획
• /
• 제25권1호
• /
• pp.67-74
• /
• 2019

This study is to identify the heat vulnerability area as represented by heat risk factors which could be attributable to heat-related deaths. The heat risk factors were temperature, Older Adults(OA), Economic Disadvantage(ED), Accessibility of Medical Services(AMS), The population Single Person Households(SPH). The factors are follow as; the temperature means to the number of days for decades average daily maximum temperature above $31^{\circ}C$, the Older Adults means to population ages 65 and above, furthermore, the Economic Disadvantage means to the population of Basic Livelihood Security Recipients(BLSR), the Accessibility of Medical Services(AMS) means to 5 minutes away from emergency medical services. The results of the analysis are showed that the top-level of temperature vulnerability areas is Dong, the top-level of vulnerability OA areas is Eup, the top-level of AMS vulnerability is Eup. Moreover, the top-level of vulnerability ED area appears in the Eup and Dong. The result of analysing relative importance to each element, most of the Eup were vulnerable to heat. Since, there are many vulnerable groups such as Economic Disadvantage, Older Adults in the Eup. We can be figured out estimated the number of heat-related deaths was high in the Eup and Dong by the data of emergency activation in the Chungcheongnam-do Fire Department. Therefore, the result of this study could be reasonable.

• Journal of Information Processing Systems
• /
• 제15권3호
• /
• pp.632-644
• /
• 2019

The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

• 디지털산업정보학회논문지
• /
• 제15권1호
• /
• pp.1-7
• /
• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• Journal of Information Processing Systems
• /
• 제14권6호
• /
• pp.1494-1507
• /
• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.