• Proceedings of the Korean Nutrition Society Conference
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• 1995.07a
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• pp.550-558
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• 1995

Nutrition surveillance can sometimes be a powerful tool for raising awareness of nutrition problems at national and community levels and for promoting improved policies and programs to improve nutrition. Whereas many countries have been collected nutrition surveillance data for several years, the experience is often discouraging in terms of converting this data into information deemed useful by decision-makers and in terms of demonstrating impacts on decision-making. This presentation will describe the results of multi-country review of this problem undertaken by UNICEF in 1992-1994, the revised concept of "Nutrition Informatin Strategies" that emerged from the review, and the efforts currently underway at communtiy level in upstate New York to implement this revised concept.d concept.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.53-59
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• 2018

Due to the recent developments in computer vision technology, complex actions can be recognized with reasonable accuracy in smart cities. In contrast, violence recognition such as events related to fight and knife, has gained less attention. The capability of visual surveillance can be used for detecting fight in streets or in prison centers. In this paper, we proposed a deep learning-based violence recognition method for surveillance cameras. A convolutional neural network (CNN) model is trained and fine-tuned on available benchmark datasets of fights and knives for violence recognition. When an abnormal event is detected, an alarm can be sent to the nearest police station to take immediate action. Moreover, when the probabilities of fight and knife classes are predicted very low, this situation is considered as normal situation. The experimental results of the proposed method outperformed other state-of-the-art CNN models with high margin by achieving maximum 99.21% accuracy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1417-1425
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• 2021

The purpose of this study is to map mineral and coal (Minerba) policies by analyzing the law and producing research novelty on mineral and coal governance policies in Indonesia with the Theory U approach. This study uses a qualitative research with the U theory approach. The results of the SNA analysis indicate that good mineral and coal governance must be carried out at various levels, from micro to macro. First, related to regulations on mineral and coal governance at the macro level. Regulations regarding the management of mineral and coal need to be carried out with a deeper evaluation related to the tax system, licensing system, increased value added and downstreaming and mineral and coal funds. The second is related to the regulation of mining management in the meso level. Third, related to the management of mineral and coal at the micro level, it is necessary to conduct more stringent supervision of the impacts caused by the mining sector of the Minerba. In addition, surveillance is also carried out as per law in order to avoid harmful behavior for both the company and the state. The originality of this research is the theory of U in the Mining Law research.

• Defense and Technology
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• no.12 s.274
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• pp.46-53
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• 2001

미래 전쟁에 대비하기 위하여, 미국은 합동참모본부의 Joint Vision 2020에서 정보에서의 우월성을 기초로 압도적인 기동, 정확한 공격, 집중된 군수지원, 전면적인 방어를 이룩하여 전체적인 우위전력 확보를 도모하여, 정보에서의 우월성 확보를 위해 $C^4ISR$(Command, Control, Communication and Computer, Intelligence, Surveillance, Reconnaissance)개념에 의한 통합체계의 구축을 목표로 제시하고 있다.

• Defense and Technology
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• no.1 s.275
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• pp.58-67
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• 2002

미래 전쟁에 대비하기 위하여, 미국은 합동참모본부의 Joint Vision 2020에서 정보에서의 우월성을 기초로 압도적인 기동, 정확한 공격, 집중된 군수지원, 전면적인 방어를 이룩하여 전체적인 우위전력 확보를 도모하며, 정보에서의 우월성 확 보 를 위 해 $C^4ISR$(Command, Control, Communication and Computer, Intelligence, Surveillance, Reconnaissance) 개념에 의한 통합체계의 구축을 목표로 제시하고 있다.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.87-94
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• 2006

For realizing an ubiquitous home network(uHome-net), various sensors should be able to be connected to an integrated wire/wireless sensor network. This paper describes an application case of applying LonWorks technology being widely used in control network to wire/wireless sensor network in uHome-net and the design and application of LonRF device that consists of a neuron chip including LonTalk protocol, a 433.92MHz RF transceiver, a sensor, and application programs. As an application example of the LonRF device, the LonRF smart badge that can measure the 3D location of objects in indoor environment and interwork with the uHome-net was developed. LonRF device based home network services were realized on the uHome-net testbed such as indoor positioning service, remote surveillance service and remote metering service were realized. This research shows that LonWorks technology based sensor network could be applicable to the control network in an ubiquitous home network and the LonRF device can be used as a wireless node in various sensor networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.7
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• pp.1026-1031
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• 2002

In this Paper, We analysed the technical characteristics of a automatic identification system that will introduce in aviation and marine radio stations. IMO's Marine Safety Committee approved revision of chapter V of the Safety of Life at Sea(SOLAS) Convention in 73rd meeting. According to this, AIS will become a mandatory carriage requirement by 01 July 2002. AIS as a surveillance system continuously receives its own position from the GNSS and then repeatedly broadcasts it on a W:.u data link for avoiding traffic conflicts and possible disasters. VHF data link is organized so that a specified number of time slots make up a repeatable frame. Each radio station can autonomously allocate and deallocate slots within the frame using selection algorithm which is called SOTDMA(Self-Organized Time Division Multiple Access). The results can be an aid in the continued of understanding technical characteristics for AIS as a broad surveillance system.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.7-14
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• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.189-192
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• 2014

Recently, U.S. and Europe, which are advanced to Air Traffic Control Management, are interest in replacing Radar System with Communications, Navigation and Surveillance(CNS) and Air Traffic Management(ATM). They pursue to research the efficient Air Traffic Control Management. This paper covers ADS-B 1090ES system which is one of CNS/ATM surveillance systems. This research satisfied all performance required by RTCA DO-268B and EUROCAE ED-129. It optimized algorism to mainly enhance performance such as quality of receiver signal, dynamic range, and so on. The optimized mechanism provided stable performance of demodulation, tuned the level of signal, and had reduced the false reception ratio by the signal level difference. The analyzed algorism helped great performance and will be considered to apply broad system applications.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.103-116
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• 2010

In this paper, we propose an optimal camera placement using agent-based simulation. To derive importance of space and to cover the space efficiently, we accomplished an agent-based simulation based on classification of space and pattern analysis of moving people. We developed an agent-based camera placement method considering camera performance as well as space priority extracted from path finding algorithms. We demonstrate that the method not only determinates the optimal number of cameras, but also coordinates the position and orientation of the cameras with considering the installation costs. To validate the method, we compare simulation results with videos of real materials and show experimental results simulated in a specific space.