• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1390-1403
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• 1998

Database sharing system (DSS) refers to a system for high performance transaction processing. In DSS, the processing nodes are locally coupled via a high speed network and share a common database at the disk level. Each node has a local memory, a separate copy of operating system, and a DB'\fS. To reduce the number of disk accesses, the node caches database pages in its local memory buffer. However, since multiple nodes may be simultaneously cached a page, cache consistency must be cnsured so that every node can always access the'latest version of pages. In this paper, we propose efficient cache consistency schemes in DSS, where the database is logically partitioned using primary copy authority to reduce locking overhead, The proposed schemes can improve performance by reducing the disk access overhead and the message overhead due to maintaining cache consistency, Furthermore, they can show good performance when database workloads are varied dynamically.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.180-186
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• 2022

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.214-217
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• 1996

Early decision support systems (DSS) were the "passive" decision support systems in the sense that the systems only able to do what the users explicitly direct them to do. But some researchers such as Raghav Rao et al. [51 showed architectures to suggest general idea of the innovative DSS systems which offer active form of decision support, say, "active Intelligent Decision Support Systems(active IDSS)". The system can perform not only what the users want to do but some voluntary (or involuntary) intelligent works. This paper presents the issues in the design of the active IDSS in the domain of investment evaluation, a domain area where few researchers have suggested frameworks or architectures to discriminate good investment from bad one. We propose a new paradigm, by utilizing historical investment results using neural network and Multivariate Discriminant Analysis(MDA), to identify goodness of investment. A new active IDSS architecture which consists of neural network, expert system and three components of the traditional passive DSS is suggested with some scenario based results.nario based results.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.139-151
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• 2007

Decision-making in the crisis management happens in dynamic, rapidly changing, and often unpredictable distributed environments. Crisis management Decision Support Systems (DSSs) in E-Government are challenged by the need to use it availably at anytime, from anywhere, and even under any-situation. In this paper the reasons of developing distributed architecture for crisis management Decision Support Systems (DSSs) in E-Government are analyzed. Consequently, a distributed architecture for crisis management Decision Support System (DSS) is proposed in this paper. Finally it is implemented by Web Services. If crisis management Decision Support System (DSS) based on distributed architecture is implemented by Web Service, then it can provide decision support for decision-makers to deal with crisis at anytime, from anywhere, and even under any-situation.

• Journal of the Korean Solar Energy Society
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• v.22 no.4
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• pp.68-76
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• 2002

This paper discusses thermal and ventilation performance which might be caused by the adoption of one of specific building facade techniques, Double Skin System(DSS). One building with a prototypical DSS was selected and systematically investigated through field monitoring and computer simulation techniques. A network model of ventilation was successfully made using COMIS to evaluate ventilation performance of the system which can hardly be done by field measurements. Various operating conditions of air conditioning on/off and window opening were implemented in this type of building. Through the appropriate operation of the DSS in summer, simulation-based and experimental results implicate that it can lead to cooling energy savings.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.601-604
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• 2008

Acceleration analysis system transfers DSS into acceleration value utilizing Quantera that receives the measurement from the accelerometers installed in the whole nation. When earthquake occurs, the system gives accleration values in certain locations in a map where the accelerometers are installed. And it suggests a measure to fix the problems related to abnormal operations of accelerometers.

• Korean Management Science Review
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• v.2
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• pp.72-77
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• 1985

최근 선진국에서는 S/W 개발의 낮은 생산성에 따른 개발정체현상 (Backlog), 전산운영(System Management)과 관련한 현업의 불만점증과 개 개발된 S/W의 보전업무(Maintenance)의 과다현상등이 심각하게 논의되고 있는데 이는 S/W의 위기라 불리워지며 다음과 같이 설명이 되고 있다.(중략)

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.133-136
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• 1998

Supporting decision-makers involves not only functions of conventional DSS such as problem identification, alternative generation and selection but also education and business processing. The purpose of this paper is to propose Decision-Maker Support System (DMSS) that comprehensively supports decision-makers who should enhance their decision quality. The DMSS consists of three core subsystem: distance learning system, conventional DSS and ERP system.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.54.3-55
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• 2016

DEEP-South Scheduling and Data reduction System (DS SDS) consists of two separate software subsystems: Headquarters (HQ) at Korea Astronomy and Space Science Institute (KASI), and SDS Data Reduction (DR) at Korea Institute of Science and Technology Information (KISTI). HQ runs the DS Scheduling System (DSS), DS database (DB), and Control and Monitoring (C&M) designed to monitor and manage overall SDS actions. DR hosts the Moving Object Detection Program (MODP), Asteroid Spin Analysis Package (ASAP) and Data Reduction Control & Monitor (DRCM). MODP and ASAP conduct data analysis while DRCM checks if they are working properly. The functions of SDS is three-fold: (1) DSS plans schedules for three KMTNet stations, (2) DR performs data analysis, and (3) C&M checks whether DSS and DR function properly. DSS prepares a list of targets, aids users in deciding observation priority, calculates exposure time, schedules nightly runs, and archives data using Database Management System (DBMS). MODP is designed to discover moving objects on CCD images, while ASAP performs photometry and reconstructs their lightcurves. Based on ASAP lightcurve analysis and/or MODP astrometry, DSS schedules follow-up runs to be conducted with a part of, or three KMTNet telescopes.

• Environmental Engineering Research
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• v.14 no.2
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• pp.111-119
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• 2009

A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.