• Korean Journal of Construction Engineering and Management
• /
• v.19 no.3
• /
• pp.43-51
• /
• 2018

Facility Management (FM) phase in building lifecycle management is the most crucial phase concerning building value and life cycle cost management. Nevertheless, systematic and rational FM process is not yet constructed, leading to failure of facility value and cost management from accurate and proactive FM. This is because there has been minimal approach regarding construction of optimal FM process based on rational FM data analysis. The purpose of this study is to provide optimal FM process with quantitative FM data analysis method using spatial data. This study investigated existing FM data structure and derive the limitation of it from both expert interview and practical FM material analysis. As a solution for this limitation, this study provided optimal FM process with MTBF (Mean Time Between Failure), which is quantitative FM data analysis method. The effect of the provided process was validated with a case study. It is expected that this process allows rational and objective FM data analysis, resulting in accurate and proactive FM. And it is expected that it can be used as a useful basic data for developing an effective system for the FM process.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.8
• /
• pp.115-124
• /
• 2003

To guarantee the proper functions of a satellite in the extreme space environment, the several test models are developed generally. There are advantages that the design and the analysis of Flight Model(FM) can be validated through these test models, and the functional reliabilities can be increased by reflecting the modifications on the final design of FM. The integration and test of Structure & Thermal Model(STM) of KOMPSAT, being currently developed, have been completed. In this paper, the processes of design/analysis and integration of the STM propulsion system, one of the KOMPSAT modules, are described.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.51
• /
• pp.73-87
• /
• 1999

본 연구에서는 다양한 종류의 공정을 수행할 수 있는 가공장비와 자동화된 물류 운반시스템으로 구성된 FMS의 효율적 운영을 위해 셀 제조방식의 개념을 도입한 다수의 유연셀 형성 방법을 제시하고 있다. 서로 독립적인 유연셀의 형성을 위해 FMS의 장점인 공정유연성을 최대한 활용할 수 있도록 기계-공정 행렬과 부품-공정 행렬에 기초한 2 종류의 새로운 유사도 계수와 예외적 요소의 수를 최소화하기 위한 셀 형성 알고리즘을 개발하였다. 두 행렬들은 다공정 수행가능기계간 유사도와 기계셀과 부품간 비처리 능력지수 산출의 기초자료로 사용된다. 알고리즘은 예외적 요소의 수를 최소로 하면서 셀의 수를 최대로 하는 정리에 기초하여 공정을 기계에 할당하며, 다수의 대체경로가 유연셀내에서 형성될 수 있도록 크게 2 단계로 구성되어 있다. 마지막으로 수치예제와 함께 예외적 요소의 발생수를 척도로 하여 기존의 방법들과 비교, 평가하고 있다.

• Broadcasting and Media Magazine
• /
• v.1 no.3
• /
• pp.16-29
• /
• 1996

본 논문에서는 지상망 디지털 오디오방송(DAB) 시스템의 출현 배경과 미국 내에서 DAB 시스템의 개발과 성능시험 평가를 위한 NAB, NRSC, EIA, FCC, NASA, Lewis 연구소, 카나다 CRC의 활동상을 소개한다. 구체적으로는 미국에서 개발 중에 있는 USA Digital Radio사, Amati Communications사와 Kintel Technologies사의 FM In-Band On-Channel(IBOC)방식, AT＆T사의 FM In-Band Adjacent-Channel(IBAC)방식과 USA Digital Radio사의 AM IBOC 방식의 원리와 특성, 핵심기술, 개발현황, 성능시험 결과와 각 방식의 장단점을 비교 분석하며 또한 미국의 In-Band 방식과 유럽의 Eureka 147 New-Band 방식을 비교 분석한다.

• Journal of the Korean Institute of Navigation
• /
• v.19 no.2
• /
• pp.115-120
• /
• 1995

Recently, the ship automation technology(SAT) has received great attention for the efficient management of the ship with minimum human efforts. Among the SAT, a distance measuring system, the key element is the signal processing unit for the interpretion of the received signal from the remote sensing of the oil tank. In this paper, the tank monitoring system using FM-CW is described for the oil tank level guage measurement with an emphsis of signal processing unit.

• The Journal of the Acoustical Society of Korea
• /
• v.13 no.4
• /
• pp.50-59
• /
• 1994

The pan-european paging system European Radio MEssage System (ERMES), a new system of digital information communication, has 16 channels with 25KHz channel spacing. The ERMES modulation format is 4-PAM/FM. The ERMES operates in the frequency range 169.4125MHz$\~$169.8125MHz. In this paper, an ERMES receiving system according to the European Telecommunication Standard Institute(ETSI) specfication with a double error correction capability is designed. The ERMES receiver system is designed with the conventional circuit and its error performance for muitiple signal modulated by the 4-PAM/FM method are analyzed. Since amplitude imbalance among the signal components can impair the system performance when several receivers are operated on the same RF channel simultaneously, the optimal parameters are obtained in designing the radio system. Performance of the proposed receiver system is verified via computer simulation for processing procedure.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.145-165
• /
• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Journal of Digital Contents Society
• /
• v.19 no.4
• /
• pp.731-737
• /
• 2018

The recommendation system is actively researched for the purpose of suggesting information that users may be interested in in many fields such as contents, online commerce, social network, advertisement system, and the like. However, there are many recommendation systems that propose based on past preference data, and it is difficult to provide users with little or no data in the past. Therefore, interest in higher-order data analysis is increasing and Matrix Factorization is attracting attention. In this paper, we study and propose a comparison and replay of the Factorization Machines Leaning(FM) model which is attracting attention in the recommendation system and High-Order Factorization Machines Learning(HOFM) which is a high - dimensional data analysis.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.10
• /
• pp.1935-1944
• /
• 1994

FMS is a distributed system composed of various programmable manufacturing hardware such as robots and NC machines. For the autonomous operation of such a system, an integrated software layer for the control and monitoring in needed on top of the manufacturing hardware. However, constructing and maintaining such a software layer is difficult due to the complexity of a underlying FMS and its frequently changing nature. To cope with this problem, this paper proposes an object-oriented FMS integration model, in which objects acting as virtual manufacturing cells are instantiated for each physical cell in the underlying object-oriented database. Various other entities involved in manufacturing processes and their relationship to the cell objects are also captured in the database. This paper describes the structure of this object-oriented FMS database on our prototype implementation called FREE.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
• /
• v.5 no.3
• /
• pp.22-35
• /
• 1994

To improve the bandwidth efficiency in the environment of digital mobile communications, a correlative coded FM system is designed. The signal of this system has continuous phase and high power efficiency due to the constant envelope. But this signal also has a little loss of the SNR and some degradation of the BER. In this paper, a modified MLSE method which uses correlative coded signal is adopted to improve the performance of the receiver. The MLSE method improved the BER performance in the used channel. Without the decision feedback, the receiver performance was improved by 2dB and with it, by 4dB Particularly, the MLSE method and the decision feedback showed better performance in bad channels than in a stable telephone channel.