• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.467-474
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• 1999

In this paper, Fault tolerant digital governor, using duplex I/O module and triplex CPU module and also 2 out of 3 voting algorithm and adding self diagnostic ability, is designed to realize ceaseless controlling and to improve the reliability of control system. The processor module of the system(SIDG-3000) is developed based on MC68EC040 32 Bit of Motorola, which guaranteed high quality of the module ,and SRAM for data also SRAM for command are separated. The process module also includes inter process communication function and power back up function (SRAM for back-up). System reliability is estimated by using the model of Markov process. The reliability of triplex system in mission time can be improved about 1.8 times in reliability 86%. 2.8 times in 95 %, 6 times in 99 % compared with a single control system. Designed digital governor system is applied after modelling of the steam turbine generator system of Buk-Cheju Thermal Power Plant. Simulation is carried out to prove the effectiveness of the designed digital governor system

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.4
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• pp.572-584
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• 1993

In this paper, we propose an efficient method to allocate carrier frequencies so as to minimize intermodulation products in two-level SCPC systems in which Hub station and many Remote stations communicate each other through the satellite transponder. Also we present a very efficient method to evaluate intermodulation products with highly reduced CPU time in two-level SCPC systems. We study and analyze the performance of some possible methods to extend the Deletion and Insertion operation, which is proposed by Okinaka and applied to only one-level SCPC systems, to two-level SCPC systems. The proposed algorithm is carefully selected out of these methods and is optimized, which shows superior performance to any other published strategies, especially in that it has very excellent characteristics in terms of generality for practical application. Considering the fact that most published strategies are seldom applicable to actual two-level SCPC systems, we can say that the proposed algorithm in this paper is quite meaningful.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.459-462
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• 2010

Response to nerve stimulation platform for implementing measures to detect finger movement has been functioning as an important factor. This stimulated finger on the nerve and muscle responses would vary. In other words, the finger movement of the muscle response to nerve stimulation and sensing Actuator for the H/W development is needed. In addition, a low power embedded CPU based on the top was used. H/W configuration portion of the isolation power, constant current control, High impedance INA, amplifier parts, and the stimulus mode and the Micro-control the status of current, AD converter Low Data obtained through the processing system is implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2451-2461
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• 2014

Mobile application is software executing on smart devices regardless of the time and place. Many individuals and companies have provided a lot of mobile applications services. However, there is not certain standard in terms of application's quality evaluation because study is deficient compared with increase amount of development of mobile application. Moreover, mobile application basically has many special characteristics. For these reasons mobile application is required special standard of quality different from general software. To satisfy these needs, I design and propose mobile application evaluation model. Evaluation model is mapped by characteristics of mobile application based on ISO/IEC 25000's quality characteristics and propose each quality characteristics and metrics. For verification, scenario-based studies were applied to quality model and carried out.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.617-630
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• 1996

In this paper, a shared-concurrent file system (S-CFS) is designed and implemented using conventional disks as disk arrays on a Workstation Cluster which can be used as a small-scale server. Since it is implemented on UNIX operating systems, S_CFS is not only portable and flexible but also efficient in resource usage because it does not require additional I/O nodes. The result of the research shows that on small-scale systems with enough disks, the performance of the concurrent file system on transaction processing applications is bounded by the bottleneck of CPUs computing powers while the performance of the concurrent file system on massive data I/Os is bounded by the time required to copy data between buffers. The concurrent file system,which has been implemented on a Workstation Cluster with 8 disks,shows a throughput of 388 tps in case of transaction processing applications and can provide the bandwidth of 15.8 Mbytes/sec in case of massive data processing applications. Moreover,the concurrent file system has been dsigned to enhance the throughput of applications requirring high performance I/O by controlling the paralleism of the concurrent file system on user's side.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.132-141
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• 2015

We focus on the fire scheduling problem (FSP), the problem of determining the sequence of targets to be fired at, for the objective of minimizing makespan to achieve tactical goals. In this paper, we assume that there are m available weapons to fire at n targets (> m) and the weapons are already allocated to targets. One weapon or multiple weapons can fire at one target and these fire operations should start simultaneously while the finish time of them may be different. We develop several dominance properties and a lower bound for the problem, and suggest a branch and bound algorithm implementing them. Also, In addition, heuristic algorithms that can be used for obtaining an initial upper bound in the B&B algorithm and for obtaining good solutions in a short time were developed. Computational experiments are performed on randomly generated test problems and results show that the suggested algorithm solves problems of a medium size in a reasonable amount of computation time. The proposed lower bound, the dominance properties, and the heuristics for upper bound are tested in B&B respectively, and the result showed that lower bound is effective to fathoming nodes and the dominance properties and heuristics also worked well. Also, it is showed that the CPU time required by this algorithm increases rapidly as the problem size increases. Therefore, the suggested B&B algorithm would be limited to solve large size problems. However, the employed heuristic algorithms can be effectively used in the B&B algorithm and can give good solutions for large problems within a few seconds.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.1-12
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• 2021

In this paper, we propose a tool called ARCAV (Atomatic Recovery of CUDA Atomicity violation) to automatically repair atomicity violations in GPU (Graphics Processing Unit) program. ARCAV monitors information of every barrier and memory to make actual memory writes occur at the end of the barrier region or to make the program execute barrier region again. Existing methods do not repair atomicity violations but only detect the atomicity violations in GPU programs because GPU programs generally do not support lock and sleep instructions which are necessary for repairing the atomicity violations. Proposed ARCAV is designed for GPU execution model. ARCAV detects and repairs four patterns of atomicity violations which represent real-world cases. Moreover, ARCAV is independent of memory hierarchy and thread configuration. Our experiments show that the performance of ARCAV is stable regardless of the number of threads or blocks. The overhead of ARCAV is evaluated using four real-world kernels, and its slowdown is 2.1x, in average, of native execution time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1255-1261
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• 2020

Cache side-channel attack is a class of attacks to retrieve sensitive information from a system by exploiting shared cache resources in CPUs. As the attacks are delivered to wide range of environments from mobile systems to cloud systems recently, many detection strategies have been proposed. Since the conventional cache side-channel attacks are likely to incur tremendous number of cache events, most of the previous detection mechanisms were designed to carefully monitor mostly cache events. However, recently proposed attacks tend to incur less cache events during the attack. PRIME+ABORT attack, for example, leverages the Intel TSX instead of accessing cache to measure access time. Because of the characteristic, attack detection mechanisms based on cache events may hardly detect the attack. In this paper, we conduct an in-depth analysis of the PRIME+ABORT attack to identify the other useful hardware events for detection rather than cache events. Based on our finding, we present a novel mechanism called PRIME+ABORT Detector to detect the PRIME+ABORT attack and demonstrate that the detection mechanism can achieve 99.5% success rates with 0.3% performance overhead.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.4
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• pp.17-27
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• 2010

Major IT vendors expect that cloud computing technology makes it possible to reduce the contents service cycle, speed up application deployment and skip the installation process, reducing operational costs, proactive management etc. However, cloud computing environment for massive content service solutions requires high-performance data processing to reduce the time of data processing and analysis. In this study, Efficient_Cloud_Processing_Scheme(ECPS) is proposed for allocation of resources for massive content services. For high-performance services, optimized resource allocation plan is presented using MapReduce programming techniques and association rules that is used to detect hidden patterns in data mining, based on levels of Hadoop platform(Infrastructure as a service). The proposed ECPS has brought more than 20% improvement in performance and speed compared to the traditional methods.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.