• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.1-7
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• 2016

An uninterruptible power supply (UPS) allows small companies and domestic users to cope with power outages; but existing designs lack flexibility of control and require expensive battery maintenance, with a cost proportional to the outage compensation time. We combine a compact synchronous generator with a battery, with 10% of the capacity that would otherwise be required, to obtain a UPS with reduced maintenance costs for the same performance. Any UPS must respond immediately to a power loss, and our uninterruptible generator supply (UGS) is therefore built around real-time scheduling of its internal operations; this also makes it suitable for integration into the industrial gateway. The UGS is based on a real-time operating system, with an integrated wireless module providing connectivity to a web server, for monitoring and management, which can be performed remotely on a mobile device.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.304-308
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• 2009

This paper presents the deadline driven CPU-Power management scheme for the Real-Time Embedded OS: named TMO-eCos. It used the scheduling scenarios generated by a task serialization technique for hard real- time TMO system. The serializer does a off-line analysis at design time with period, deadline and WCET of periodic tasks. Finally, TMO-eCos kernel controls the CPU speed to save the power consumption under the condition that periodic tasks do not violate deadlines. As a result, the system shows a reasonable amount of power saving. This paper presents all of these processes and test results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.506-512
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• 2006

In this paper, we propose a lot-sizing and scheduling problem that seeks to minimize the sum of production cost and inventory cost over a given planning horizon while considering idle state of a machine in a batch production system. For this problem, we develop an integer programming model. And, we develop an efficient 2-phase heuristic algorithm to find a high quality feasible solution within reasonable time bounds. In the first phase, we seek to minimize the production cost by assigning batches to machines. Then, in the second phase, we find a production sequence of batches that reduces the inventory cost, while considering adding or deleting idle states between batches. Computational results show that the developed heuristic algorithm finds excellent feasible solutions within reasonable time bounds. Also, we could significantly reduce the total cost consisting of production cost and inventory cost by using the developed heuristic algorithm at a real manufacturing system that produces zinc alloys.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.4 s.23
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• pp.58-67
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• 2005

To overcome limitations of test scope, schedule and cost, M&S(Modeling & Simulation) technique has been applied for T&E(Test and Evaluation) of the state-of-art weapon systems. This paper proposes an air defense simulation software framework to reduce both redundancy an[1 programming errors in system simulator. The proposed framework consists of a 'model' and a 'middleware' The 'middleware' is a reliable communication service layer that supports not only HLA(High Level Architecture) which is an international standard in M&S but also TCP/IP, UDP and etc. The main role of 'model' is to schedule and to run the real-time distributed simulation. The proposed framework has been applied to M-SAM(Middle range Surface to Air Missile) system simulator. The proposed framework's scheduling and communication performance results are satisfactory and were measured by hardwired NTP(Network Timer Protocol) time-stamp with GPS(Global Positioning System) timer for better precision.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.15-27
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• 2020

This study starts with the idea that the process of creating a Gantt Chart for schedule planning is similar to Tetris game with only a straight line. In Tetris games, the X axis is M machines and the Y axis is time. It is assumed that all types of orders can be worked without separation in all machines, but if the types of orders are different, setup cost will be incurred without delay. In this study, the game described above was named Gantris and the game environment was implemented. The AI-scheduling table through in-depth reinforcement learning compares the real-time scheduling table with the human-made game schedule. In the comparative study, the learning environment was studied in single order list learning environment and random order list learning environment. The two systems to be compared in this study are four machines (Machine)-two types of system (4M2T) and ten machines-six types of system (10M6T). As a performance indicator of the generated schedule, a weighted sum of setup cost, makespan and idle time in processing 100 orders were scheduled. As a result of the comparative study, in 4M2T system, regardless of the learning environment, the learned system generated schedule plan with better performance index than the experimenter. In the case of 10M6T system, the AI system generated a schedule of better performance indicators than the experimenter in a single learning environment, but showed a bad performance index than the experimenter in random learning environment. However, in comparing the number of job changes, the learning system showed better results than those of the 4M2T and 10M6T, showing excellent scheduling performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.776-782
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• 1995

This paper presents a methodology for development of a heterarchical control system in Flexible Manufacturing Systems (FMS) environment. A Petri net based model is applied for development of control software. A real-time scheduling methodology for the heterarchical system is also developed and it is used as a software entity in the overall architecture. The partition of generic and specific modules in control software development is emphasized. The control system performs its control tasks in two stages: (1) generation of generic control code and distribution of them to each controller entity prior to system execution; (2) generation of specific control code according to job arrival and its process plan. The control software and the scheduling algorithm are evaluated by a simulation program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1305-1310
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• 2008

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.9
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• pp.22-32
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• 1997

This paper proposes an imprecise compuitation model for DCT considering QOS of images and a two dimensional DCT architecture for imprecise computations. In case that many processes are scheduling in a hard real time system, the system resources are shared among them. Thus all processes can not be allocated enough system resources (such as processing power and communication bandwidth). The imprecise computtion model can be used to provide scheduling flexibility and various QOS(quality of service)levels, to enhance fault tolerance, and to ensure service continuity in rela time systems. The DCT(discrete cosine transform) is known as one of popular image data compression techniques and adopted in JPEG and MPEG algorithms since the DCT can remove the spatial redundancy of 2-D image data efficiently. Even though many commercial data compression VLSI chips include the DCST hardware, the DCT computation is still a very time-consuming process and a lot of hardware resources are required for the DCT implementation. In this paper the DCT procedure is re-analyzed to fit to imprecise computation model. The test image is simulated on teh base of this model, and the computation time and the quality of restored image are studied. The row-column algorithm is used ot fit the proposed imprecise computation DCT which supports pipeline operatiions by pixel unit, various QOS levels and low speed stroage devices. The architecture has reduced I/O bandwidth which could make its implementation feasible in VLSI. The architecture is proved using a VHDL simulator in architecture level.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.345-348
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• 2006

LMTT (linear motor-based transfer technology) is horizontal transfer system in the maritime container terminal for the port automation. For LMTT system, shuttle cars are used instead of other types of cars. They are running on the routes which are stable on the terminal ground made of steel. The terminal scheduling complexity increases with the need of improving automation. It is necessary to make a good designed performance for the terminal system. This work presents a dispatching role using fuzzy logic for the shuttle cars. It considers the actual status of terminals and takes decisions on real time. A simulation is done to validate the role and two other dispatching rules to be compared.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.431-438
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• 2011

To ensure that equipment outages do not directly impact the reliability of the ISO-controlled grid, market participants request permission and receive approval for planned outages from the independent system operator (ISO) in competitive electricity markets. In the face of major generation outages, the ISO will make a critical decision as regards the scheduling of the essential maintenance for myriads of generating units over a fixed planning horizon in accordance with security and adequacy assessments. Mainly, we are concerned with a fundamental framework for ISO's maintenance coordination in order to determine precedence of conflicting outages. Simulated annealing, a powerful, general-purpose optimization methodology suitable for real combinatorial search problems, is used. Generally, the ISO will put forward its best effort to adjust individual generator maintenance schedules according to the time preferences of each power generator (GENCO) by taking advantage of several factors such as installed capacity and relative weightings assigned to the GENCOs. Thus, computer testing on a four-GENCO model is conducted to demonstrate the effectiveness of the proposed method and the applicability of the solution scheme to large-scale maintenance scheduling coordination problems.