• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.719-727
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• 2006

This paper proposes a new method to obtain a maximum allowable delay bound for a scheduling of networked discrete control systems and event-based scheduling method. The proposed method is formulated in terms of linear matrix inequalities and can give a much less conservative delay bound than the existing methods. A network scheduling method is presented based on the delay obtained through the proposed method, and it can adjust the sampling period to allocate same utilization to each control loop. The presented method can handle three types of data (sporadic, emergency data, periodic data and non real-time message) and guarantees real-time transmission of periodic and sporadic emergency data using modified EDF scheduling method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.9-17
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• 2019

In order to deal with high uncertainty and variability in emergency medical centers, many researchers have developed various models for their operational planning and scheduling. However, most of the models just provide static plans without any risk measures as their results, and thus the users often lose the opportunity to analyze how much risk the patients have, whether the plan is still implementable or how the plan should be changed when an unexpected event happens. In this study, we construct a simulation model combined with a risk-based planning and scheduling module designed by Simio LLC. In addition to static schedules, it provides possibility of treatment delay for each patient as a risk measure, and updates the schedule to avoid the risk when it is needed. By using the simulation model, the users can experiment various scenarios in operations quickly, and also can make a decision not based on their past experience or intuition but based on scientific estimation of risks even in urgent situations. An example of such an operational decision making process is demonstrated for a real mid-size emergency medical center located in Seoul, Republic of Korea. The model is designed for temporal short-term planning especially, but it can be expanded for long-term planning also with some appropriate adjustments.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.30-35
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• 2013

Motivated by the emergency scheduling in a transportation network, this paper considers a transportation problem, in which, the truck times and transportation costs are assumed as uncertain variables. To meet the demand in the practical applications, two optimization objectives are considered, one is the total costs and another is the completion times. And then, a multi-objective optimization model is developed according to the situation in applications. Because there are commensurability and conflicting between the two objectives commonly, a solution does not necessarily exist that is best with respective to the two objectives. Therefore, the problem is reduced to a single objective model, which is an uncertain programming with a chance-constrain. After some analysis, its equivalent deterministic form is obtained, which is a nonlinear programming. Based on a stepwise optimization strategy, a solution method is developed to solve the problem. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.209-210
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• 2018

본 논문에서는 IIoT 환경에서 효율적인 긴급 데이터 패킷 처리를 위한 스케쥴링 방식을 제안한다. 이는 weighted round robin 스케쥴링에 기반하고, 비선점형 시스템에 적용하는 방식으로 처리한다. 긴급 데이터의 평균 큐 사이즈에 따라 적응형으로 중요도를 조절함으로써 최적화시킨다. 이는 적은 패킷 손실률과 작은 딜레이로 이어진다. 이 적응형 스케쥴링 방식은 갑작스런 처리량의 변화에 많은 패킷 손실률과 딜레이 증가량 없이 대처하는 것에 효율적인 해결책이 될 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.157-164
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• 2008

In this paper we suggest a scheduling algorithm that transmits periodic traffics efficiently in tree-structured wireless sensor networks (WSNs). The related research[l] showed the problems such as increasing the energy consumption and decreasing the data throughput as the depth of tree increases. To solve these problems. we use idle time slots and avoid the redundancy at data transmission. Also we suggest the algorithm that transmits the control packet when it is similar to a previously measured data. And if emergency data is occurred, our proposed algorithm transits that data in EDP(Emergency Data Period) for reducing the wait time. The proposed algorithm shows more data throughput and less energy consumption than that of the related research.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.43-49
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• 2008

The track of high-speed railway get deteriorated according as using it. In that case, the maintenance jobs are needed for improvement of track quality. A scheduling problem for the track maintenance of high-speed railway is to determine the jobs should be performed daily. In the problem, the set of jobs for maintenance is given. Each job has it's parameters such as due date, emergency level, and processing time. In addition, jobs can be worked during a certain fixed time when the train doesn't move. In this study, we developed a mathematical model of the scheduling problem for the maintenance of high-speed railway and solved the problem using the ILOG CPLEX library.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.896-898
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• 1996

This paper presents the optimal operation scheduling of the private cogeneration system connected with auxiliary equipments. And the optimal size of auxiliary equipments is determined through evaluations of the minimum operation cost. The optimal operation scheduling is established by using the linear programming method. Simulation results show that the auxiliary boiler is operated as an economical facility but the thermal storage tank is used as a back up facility for emergency.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.89-100
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• 2016

Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.2
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• pp.127-136
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• 2016

The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.