• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.125-135
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• 1993

An Unrelated Parallel Processing with Weighted jobs and Setup times scheduling prolem is studied. We consider a parallel processing in which a group of processors(machines) perform a single operation on jobs of a number of different job types. The processing time of each job depends on both the job and the machine, and each job has a weight. In addition each machine requires significant setup time between processing jobs of different job types. The performance measure is to minimize total weighted flow time in order to meet the job importance and to minimize in-process inventory. We present a 0-1 Mixed Integer Programming model as an optimizing algorithm. We also present a simple heuristic algorithm. Computational results for the optimal and the heuristic algorithm are reported and the results show that the simple heuristic is quite effective and efficient.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.262-272
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• 2007

SAD (Sum of Absolute Difference) algorithm is the most frequently executing routine in motion estimation, which is the most demanding process in motion picture encoding. To enhance the performance of motion picture encoding on a VLIW processor, an optimal implementation of SAD algorithm on VLIW processor should be accomplished. In this paper, we propose an implementation of optimal scheduling of SAD algorithm with conditional branch on a VLIW-based high performance DSP. We first transform the nested loop with conditional branch of SAD algorithm into a single loop with conditional branch which has a large enough loop body to utilize fully the ILP capability of VLIW DSP and has a conditional branch to make the escape from loop to be achieved as soon as possible. And then we apply a modulo scheduling technique to the transformed single loop. We test the proposed implementation on TMS320C6713, and analyze the code size and performance with respect to processing time. Through experiments, it is shown that the SAD implementation proposed in this paper has small code size appropriate for embedded applications, and the H.263 encoder with the proposed SAD implementation performs better than other H.263 encoder with other SAD implementations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.2
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• pp.140-145
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• 2013

This paper proposes the high speed LDPC decoder structure base on the DVB-S2. Firstly, We study the solution to avoid the memory conflict. For the high speed decoding process the decoder adapts the HSS(Horizontal Shuffle Scheduling) scheme. Secondly, for the high speed decoding algorithm normalized Min-Sum algorithm is adapted instead of Sum-Product algorithm. And the self corrected is a variant of the LDPC decoding that sets the reliability of a Mc${\rightarrow}$v message to 0 if there is an inconsistency between the signs of the current incoming messages Mv'${\rightarrow}$c and the sign of the previous incoming messages Moldv'${\rightarrow}$c This self-corrected algorithm avoids the propagation on unreliable information in the Tanner graph and thus, helps the convergence of the decoder.Start after striking space key 2 times. Lastly, and this paper propose the optimal hardware architecture supporting the high speed throughput.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2390-2392
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• 1998

In this paper, we discuss the development of monitoring system with data process equipment which transfers data from Remote Terminal Unit(RTU) to monitoring computer. The RTUs sense temperature, pressure and PLC(Programmable Logic Controller) nodes conditions of scrubber in semiconductor manufacture processing. The data Process equipment is connected every RTU and a monitoring computer through serial communication. This equipment receives informations from RTU, process data, and transfers them to monitoring computer. To avoid congestion in data communication, task scheduling algorithm used RT O/S(Real-Time Operating System) is embedded in ROM which is a part of data Process equipment.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.94-103
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• 2003

In case of environment requiring safety such as human body and requiring flexible shape, a conventional mechanical actuator system does not satisfy requirements. Therefore, in order to solve these problems. a research of various smart material such as EAP (Electro Active Polymer), EAC (Electro Active Ceramic) and SMA (Shape Memory Alloy) is in progress. Recently, the highest preferring material among various smart material is EP (Electrostictive Polymer), because it has very fast response time, powerful force and large displacement. The previous researches have been studied properties of polymer and simple control, but present researches are studied a polymer actuator. An EP (Electostrictive Polymer) actuator has properties which change variably ils shape and environmental condition. Therefore, in order to coincide with a user's purpose, it is important not only to decide a shape of actuator and mechanical design but also to investigate a efficient controller. In this paper, we constructed the control logic with an adaptive fuzzy algorithm which depends on the physical properties of EP that has a dielectric constant depending on time. It caused for a sub-actuator to operate at the same time that a sub-actuator system operation increase with a functional improvement and control efficiency improvement in each actuator, hence it becomes very important to manage it effectively and to control the sub-system which Is operated effectively. There is a limitation on the management of Main-host system which has multiple sub-system, hence it brings out the Multi-Vehicle Control process that disperse the task efficiently. Controlling the multi-dispersion system efficiently, it needs the research of Main-host system's scheduling, data interchange between sub-actuators, data interchange between Main-host system and sub-actuator system, and data communication process. Therefore in this papers, we compared the fuzzy controller with the adaptive fuzzy controller. also, we applied the scheduling method for efficient multi-control in EP Actuator and the algorithm with interchanging data, protocol design.

• Journal of KIISE
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• v.44 no.2
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• pp.213-222
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• 2017

The Internet of Things (IoT) technology is rapidly developing in recent years, and is applicable to various fields. A smart factory is one wherein all the components are organically connected to each other via a WSN, using an intelligent operating system and the IoT. A smart factory technology is used for flexible process automation and custom manufacturing, and hence needs adaptive network management for frequent network fluctuations. Moreover, ensuring the timeliness of the data collected through sensor nodes is crucial. In order to ensure network timeliness, the power consumption for information exchange increases. In this paper, we propose an IEEE 802.15.4e DSME-based distributed scheduling algorithm for mobility support, and we evaluate various performance metrics. The proposed algorithm adaptively assigns communication slots by analyzing the network traffic of each node, and improves the network reliability and timeliness. The experimental results indicate that the throughput of the DSME MAC protocol is better than the IEEE 802.15.4e TSCH and the legacy slotted CSMA/CA in large networks with more than 30 nodes. Also, the proposed algorithm improves the throughput by 15%, higher than other MACs including the original DSME. Experimentally, we confirm that the algorithm reduces power consumption by improving the availability of communication slots. The proposed algorithm improves the power consumption by 40%, higher than other MACs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12C
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• pp.181-189
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• 2001

In this thesis, a policing algorithm is proposed, which is one of the traffic management function in ATM networks. The proposed algorithm minimizes CLR(Cell Loss patio) of high priority cells and solves burstiness problem of the traffic caused by multiplexing and demultiplexing process. The proposed algorithm has been implemented with VHDL and is divided into three parts, which are an input module, an UPC module, and an output module. In implementation of the UPC module\`s memory access, memory address is assigned according to VCI\`s LSB(Lowest Significant Byte) of ATM header for convenience. And the error of VSA operation from counter\`s wrap-around can be recovered by the proposed method. ANAM library 0.25 $\mu\textrm{m}$ and design compiler of Synopsys are used for synthesis of the algorithm and Synopsys VSS tool is used for VHDL simulation of it

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.153-156
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• 2005

Real-time monitoring and controlling manufacturing process is important because of the unexpected events. When unexpected event like mechanical trouble occurs, prior plan becomes unacceptable and a new schedule must be generated though manufacturing schedule is already decided for order. Regenerating the whole schedule, however, spends much time and cost. Thus automated system which monitors and controls manufacturing process is required. In this paper, we present a system which uses radio-frequency identification and computer vision system. The system collect real-time information about manufacturing conditions and generates new schedule quickly with those information.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.337-344
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• 2000

In this paper, we define a Process Algebra ACSMR(Algebra of Communicating Shared Multiple Resources) for system specification and verification using multiple resources. ACSMR extends a concept of multiple resources in ACSR that is a branch of formal methods based on process algebra. We'll show that two specification and verification examples. One is the specification of system behavior in multiprocessor using EDF(Earliest-Deadline-First) which is a scheduling algorithm of a real-time system. The other is the specification of describing timing analysis and resources restriction in a super scalar processor using multiple ports registers.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.