• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1531-1536
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, A general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, The immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.573-579
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• 2011

To meet the scalability and performance requirements of data analyses, which often involve voluminous data, efficient parallel or concurrent algorithms and frameworks are essential. We present a high-performance Korean morphological analyzer which employs the MapReduce framework on the graphics processing unit (GPU). MapReduce is a programming framework introduced by Google to aid the development of web search applications on a large number of central processing units (CPUs). GPUs are designed as a special-purpose co-processor. Their programming interfaces are typically formulated for graphics applications. Compared to CPUs, GPUs have greater computation power and memory bandwidth; however, GPUs are more difficult to program because of the design of their architectures. The performance of the Korean morphological analyzer using the MapReduce framework on the GPU is evaluated in comparison with the CPU-based model. The proposed Korean Morphological analyzer shows promising scalable performance on distributed computing with the GPU.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1002-1011
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• 2013

This paper proposes the new adaptive protection algorithm for inverse-time overcurrent relays (OCRs) to ensure their proper operating time and protective coordination. The application of the proposed algorithm requires digital protection relays with microcontroller and memory. The operating parameters of digital OCRs are adjusted based on the available data whenever system conditions (system with distributed generation (DG)) vary. Moreover, it can reduce the calculation time required to determine the operating parameters for achieving its purpose. To verify its effectiveness, several case studies are performed in time-domain simulation. The results show that the proposed adaptive protection algorithm can keep the proper operating time and provide the protective coordination time interval with fast response.

• International Journal of Contents
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• v.11 no.1
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• pp.69-72
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• 2015

Generally, existing parallel main-memory spatial index structures to avoid the trade-off between query freshness and CPU cost uses light-weight locking techniques. However, still, the lock based methods have some limits such as thrashing which is a well-known problem in lock based methods. In this paper, we propose a distributed index structure for moving objects exploiting the parallelism in multiple machines. The proposed index is a lock free multi-version concurrency technique based on the D-Stream model of Spark Stream. The proposed method exploits the multiversion nature of D-Stream of Spark Streaming.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.483-491
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• 2001

In this paper, we design and implement of the remote method connection system using Java RMI in the distributed computing system. In pursuing this goal, we implement the dynamic method connection interface and API. And then we describe the dynamic memory management routine.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.10
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• pp.21-30
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• 1994

We discussed the Distributed Control System's design on preface and analyzed time of the real-time communication by using designed system. The DCS proposed in this thesis was implemented to network file system having recovery advantage and shared memory method to access file system of a Remote Station with ease. Also, this system minimized the network delay-time by using the real-time VME147 board. In implemented DCS, the performance analysis of real-time process of a Remote Station was done to get the total time for reak-tune communication from a Remote Station to the Central Station after terminating of process. For the analysis of system performance, we experiented by three steps. Firstly, we measuredthe processing the of LOOP function that real-time CPU convertes to-2,500~10.000 values from the input data of the Analog Interface Card. Secondly, we measured the processing time of the LOGIC function and the LOOP function. Lastly, we measured total processing time for communication from a Remote Station to the Centrol Station.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.177-180
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• 2002

This paper introduces a new distributed QoS (Quality of Service) control system for clusters of web servers. The proposed system can employ not only network bandwidth but also other metrics such as processor load, memory usage, and storage access load that affect the overall system performance. Moreover, it controls over clustered\ulcorner workstations in of-der to utilize idle resources among workstations. This architecture maximizes overall usage of cluster of web servers while it provides predictable and differentiated performance for each contents volume. We implemented a prototype of introduced system, and the test results showed the proposed method can control QoS in a cluster server system.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.314-317
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• 2000

Cluster system provides attractive scalability in terms of computation power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive parallel machines. In parallel processing program, each task load is difficult to predict before running the program and each task is interdependent each other in many ways. Load imbalancing induces an obstacle to system performance. Most of researches in load balancing were concerned with distributed system but researches in cluster system are few. In cluster system, the dynamic load balancing algorithm which evaluates each processor's load in runtime is purpose that the load of each node are evenly distributed. But, if communication cost or node complexity becomes high, it is not effective method for all nodes to attend load balancing process. In that circumstances, it is good to reduce the number of node which attend to load balancing process. We have modeled cluster systems and proposed marginal dynamic load balancing algorithms suitable for that circumstances.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.261-268
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• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.