• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.82-88
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• 2002

In this paper, we proposed a audio indexing method that is used wavelet transform for audio data retrieval. It is difficult for audio data to make a efficient audio data index because of its own particular properties, such as requirement of large storage, real time to transfer and wide bandwidth. An audio data in del using wavelet transform make it possible to index and retrieval by using the particular wavelet transform properties. Our proposed indexing method doesn't separate data to several blocks. Therefore we use both high-pass and low-pass parts of last level coefficient of wavelet transform. Audio data indexing is made by applying the string matching algorithm to high-pass part and zero-crossing histogram to low-pass part. These are transformed to the continued strings, Through this method, we described a retrieval efficiency. The retrieval method is done by comparing the database index string to the query string and then data of minimum values is chosen to the result. Our simulation decided proper comparative coefficient and made known changing of retrieval efficiency versus audio data length. The results show that the proposed method improves retrieval efficiency compared to conventional method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.701-702
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• 2020

본 논문에서는 Jetson-Nano와 데스크탑에서 OpenCV와 YOLOv3 실시간 객체 인식 알고리즘을 이용하여 웹캠을 통해 주차장 등의 출입 차량 인식 통계 시스템을 개발하였다. 최근 에지컴퓨팅에 관심이 증가하고 있는 시점에서 Nvidia사에서 개발하여 보급하고 있는 Jetson-Nano에 YOLOv3 tiny와 OpenCV를 이용하여 차량인식을 수행하고, 구글에서 개발한 오픈 소스 Tesseract-OCR을 이용해 차량번호인식하여 입출차 혹은 주차시 차량정보를 확인할 수 있다. 딥러닝 학습 알고리즘에서 전기차 번호판의 특징점을 인식하여 전기차를 판별하여 일반차량이 전기차 주차구역에 불법주차하는 것을 모니터링할 수도 있다. 출입한 차량 데이터 베이스에서 입출차 시각, 차량번호, 전기차여부등이 확인 가능하다.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.127-135
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• 2010

Modern marine navigation requires officers on the bridge to monitor a torrent of data on both the insides and outsides of the ship from numerous useful devices. But despite these tools, navigators can still find it difficult to make a safe decision for two reasons: one is that too much data if provided too quickly tends to cause fatigue and overwhelm the officer, and the other is that any inconsistency across data from several different types of devices can lead to confusion. Indeed, the fact remains that the many marine accidents can be attributed to human error, and hence there is a strong need for decision-support tools for marine navigation. One technique of providing decision support is through the use of simulation to evaluate or predict system dynamics over time using an accurate model. This paper, as a simulation method for risk prediction for a navigation safety information system of ship, suggests a navigation prediction simulation system using various knowledge bases and discrete event simulation methodology, and supports the validity of the system through the examples of components in a restricted navigation situation scenario.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.4
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• pp.340-355
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• 1996

In order to suggest the useful information of fishing ground, a data base system on 32bit personal computer was constructed and handled by using the catch data of Korean tuna long-line, catch by species, fishing time and place, fish price and etc. mainly from 1975 to 1992. The results obtained are as follows ; In the fishing ground displaying catch rate, the catch rate has reduced as time passed, and this penomenon was more evident in Indian. And yellowfin have high catch tate in the Western Pacific of low latitute region, bigeye tuna have in the Eastern. The region of high catch rate of bigeye tuna was moved from the Indian and the Atlantic to the Pacific. The patterns of catch numbers of yellowfin and bigeye tuna appeared nearly same that, having nothing to do with catch numbers in all oceans. The region of least catch was the Northwestern Pacific, the regions of most catch were the Western Indian and the Pacific of low latitute. As to simulation of fishing ground estimation, there were economical grounds in the Western Pacific of low latitute region, the Eastern Pacific of this, the Western Indian, the Eastern Indian, and the Atlantic, in order.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.3
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• pp.141-145
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• 2018

The paper presents a new dynamic displacement measurement system. The developed displacement measurement system consists of a sensor module, a base module and a computation module. The sensor module, which contains a force-balanced accelerometer and low-price RTK-GNSS, measures the high-precision acceleration with sampling frequency of 100Hz, the low-precision displacement and velocity with sampling frequency of 10Hz. The measured data is transferred to the computation module through LAN cable, and precise displacement is estimated in real-time with 100Hz sampling frequency through a two stage Kalman filter. The field test was conducted at San Francisco-Oaklmand Bay bridge, CA, USA to verify the precision of the developed system, and it showed the RMSE was 1.68mm.

• Journal of The Korean Association of Information Education
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• v.2 no.2
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• pp.252-259
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• 1998

Vehicle navigation systems employ a certain route planning algorithm that provides the shortest path between the starting point and the destination point. The performance of a given route planning algorithm is measured through the degree of optimal route selection and the time cost to complete searching an optimal path. In this paper, various route planning algorithms are evaluated through computer simulation based on a real digital map database. Among those algorithms evaluated in this paper, the Modified Bi-directional A${\ast}$ algorithm is found to be the best algorithm for use in vehicle navigation systems.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.29-34
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• 2016

Nowadays, real-time devices that provide health care for a companion animal is being developed by IoT technology and its demand such as smart puppy tag is increasing. However, it is difficult for IoT devices of companion animals to process complex nature due to miniaturized hardware and constructive nature. There is a clear limit to custom advanced features like health care implementation. This paper designs an integrated platform with statistical analysis which makes it possible to customized services such as feed production, pharmaceutical production, and health care for each companion animal. Middleware that collects sensor information, customer's spending pattern and information from Social Network Service is also designed by making use of IoT devices which companion animals wear. Furthermore, the paper designed data analyzer which analyzes and refines data from collected information that can be applied to personalized services.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2006-2013
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• 2015

In this paper we propose a multi-protocol gateway system based on low power wireless communications. The proposed multi-protocol gateway system was designed to allow real-time monitoring and control of the on-site situation through wired and wireless networks by gathering information for streetlight power control and environmental monitoring. The sensing data using multi-sensors with composite processing that selectively used wired or wireless communication (e.g., CDMA, Ethernet (TCP/IP), GPS, etc.) were designed to act as intermediaries that transmitted to the main server through ZigBee. Inaddition, they were designed by separating a CPU board and baseboard to ensure low maintenance cost and ease of hardware replacement. The proposed multi-protocol gateway system's power, impact, continuous operation stability, and immunity test results obtained a normal operation success rate of over 95% and normal continuous operation results. Moreover, in the voltage drop test, instantaneous immunity test, and conductive RF electromagnetic field immunity test, it obtained an average rating result of "A".

• Journal of the Korean Society of Food Science and Nutrition
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• v.30 no.5
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• pp.993-999
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• 2001

The purpose of the study was to develop a nutritional counseling program using expert system to assist obese people to lose weight through behavior modification in the internet. The counseling internet program for weight loss was developed by the accumulation of knowledge for dealing with eating habits and exercising behaviors into expert system tool, Knowledge Engineering Agent (KEA) by a dietitian without any help of computer expert. KEA was built based on the theory of Multiple Classification Ripple Down Rules. To accumulate knowledge into KEA, survey was performed in 150 obese people, the dietitian reviewed and consulted each survey case, and the consulted contents were learned and accumulated into KEA. Survey questionnaires were the same as those of the internet consulting program, and they included general characteristics, dietary habits, lifestyle, and exercise patterns related to obesity. KEA was used for nutritional counseling of obese people after KEA had enough knowledge for weight loss based on behavior modification by the dietitian. To accumulate knowledge to KEA, the dietitian selected proper factors inferred from the survey questionnaire of each case, and added the conclusions for them. Conclusions were made for helping clients to correct bad eating behaviors and accumulate good behaviors for losing weight. When clients answered survey questionnaires in a counseling internet program, KEA gave the recommendation how to eat, to exercise and the deal with stress in a real time for each case. If KEA did not have enough knowledge for a specific case, the conclusion window wrote no conclusion and the dietitian needed to add conclusions for the case. The conclusions for the new case added to the KEA knowledge base. In conclusions, a counseling internet program for weight reduction can be used for give advices how to deal with obesity in a man-to-man way in a real time using KEA where nutritional knowledge based on behavior modification for weight loss was accumulated.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.335-345
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• 1999

오늘날 날로 증가하는 물류비는 개별 기업은 물론 국가 전체의 수출 경쟁력을 약화시키는 주요 원인으로 지적되고 있다. 그러나 그동안 우리나라에서는 물류비 절감을 위한 종합적이고 체계적인 대책이 이루어지지 못하였다. 특히 본 논문의 연구대상인 육상물류의 경우 그 비중이 전체 화물 운송의 60% 이상을 차지함에도 불구하고 심각한 교통체증 및 물류기반 시설의 미비, 효율적인 정보시스템의 미비 등으로 인하여 물류비가 계속 증가하는 양상을 보여 왔다. 따라서 본 논문에서는 우리나라 육상물류시스템이 안고 있는 문제점의 해결을 위한 방안들 중의 하나로 정보기술의 활용에 관한 내용을 다루고 있다. 즉 영세한 기업들도 누구나 손쉽게 이용할 수 있도록 인터넷을 이용한 육상물류중개시스템의 개발에 관한 내용을 소개하고 있다. 육상물류중개시스템은 복합화물주선업체인 (주) 대형물류와 함께 개발한 시스템으로 인터넷을 통하여 화주의 화물 운송의뢰를 접수받아 이를 여러 운송업체에게 제공해주는 역할을 수행하게 된다. 특히 육상물류중개시스템은 화물의 운송과 관련하여 발생하는 다양한 정보들을 데이터베이스에 저장하여 두었다가 세관을 비롯한 터미날에 대한 각종 신고업무에 이용할 수 있으며, 이밖에도 교통정보 및 화물 위치정보 등 다양한 서비스를 제공해줄 수 있다. 따라서 운송업체의 공차율을 줄이고 화주에게는 자신의 화물에 대한 정보를 실시간으로 전달해 줄 수 있다는 장점이 있다. 또한 이러한 육상물류중개시스템은 현재 개발중인 통합데이터베이스를 기반으로 한 항만물류원스톱서비스 시스템과 연계되어 차후에는 물류원스톱시스템으로 발전할 수 있을 것이다. 연구가 진행되고 있는 인공신경망과의 모형결합을 통해 기존연구와는 다른 새로운 통합예측방법론을 제시하고자 한다. 본 연구에서 제시하는 통합방법론은 크게 2단계 과정을 거쳐 예측모형으로 완성이 된다. 즉, 1차 모형단계에서 원시 재무시계열은 먼저 웨이블릿분석을 통해서 노이즈가 필터링 되는 동시에, 과거 재무시계열의 프랙탈 구조, 즉 비선형적인 움직임을 보다 잘 반영시켜 주는 다차원 주기요소를 가지는 시계열로 분해, 생성되며, 이렇게 주기에 따라 장단기로 분할된 시계열들은 2차 모형단계에서 신경망의 새로운 입력변수로서 사용되어 최종적인 인공 신경망모델을 구축하는 데 반영된다.ocioeconomic impacts are resulted from the program. It would be useful for the means of (ⅰ) fulfillment of public accountability to legitimate the program and to reveal the expenditure of pubic fund, and (ⅱ) managemental and strategical learning to give information necessary to improve the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic ev