• Journal of Information Processing Systems
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• v.5 no.1
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• pp.33-40
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• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3110-3114
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• 2009

Rotor temperature variation is a significant issue in the design of induction motor controls. In the literature, numerous studies have mentioned significant performance degradation due to rotor temperature variation unless it is taken into account. However, those studies have mainly focused on field-oriented control in terms of tracking performance. There was little research about the influence of rotor temperature variation on performance particularly in the case of optimal controls such as maximum torque per amp (MTPA) control strategy. This work investigates how to affect the performance of maximum torque per amp (MTPA) control strategy as rotor temperature varies in time. To this end, investigation was carried out in two ways to see whether the objective of MTPA control strategy is achieved regardless of rotor temperature variation. It is to produce a desired torque with the minimum possible stator current at the same time. Laboratory experiment shows that tracking performance and maximum torque per amp condition is significantly affected by rotor temperature variation as rotor temperature varies, thus ending up with performance degradation of MTPA control.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.84-90
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• 2019

Tremendous computation of full search or lossless motion estimation algorithms for video coding has led development of many fast motion estimation algorithms. We still need proper control of computation and prediction quality. In the paper, we suggest an algorithm that reduces computation effectively and controls computational amount and prediction quality, while keeping prediction quality as almost the same as that of the full search. The proposed algorithm uses multiple thresholds for partial block sum and times of counting unchanged minimum position for each step. It also calculates the partial block matching error, removes impossible candidates early, implements fast motion estimation by comparing times of keeping the position of minimum error for each step, and controls prediction quality and computation easily by adjusting the thresholds. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.1
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• pp.7-13
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• 2013

Bio Clean Room(BCR) and pharmaceutical product manufacturing facilities require careful assessment of many factors, including HVAC, controls, room finishes, process equipment, room operations, and utilities. Flow of equipment, personnel, and product must also be considered along with system flexibility, redundancy, and maintenance shutdown strategies. It is important to involve designers, operators, commissioning staff, quality control, maintenance, constructors, validation personnel, and the production representative during the conceptual stage of design. Critical variables for room environment and types of controls vary greatly with the clean space's intended purpose. It is particularly important to determine critical parameters with quality assurance to set limits and safety factors for temperature, humidity, room pressure, and other control requirements. In this paper, oxygen cluster ion equipment was utilized in order to enhance the indoor air quality and to prevent the airborne infection of ward in hospital. Moreover, the performance test of the equipment was also performed in order to develop the optimal sterilization system of BCR using the equipment.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.35-41
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• 2017

With the advances in Internet over Things, the demand in diverse electronic devices such as mobile phones and sensors has been rapidly increasing and boosting up the researches on those products. Semiconductor materials, devices, and fabrication processes are becoming more diverse and complicated, which accompanies finding parameters for an optimal fabrication process. In order to find the parameters, a process simulation before fabrication or a real-time process control system during fabrication can be used, but they lack incorporating the feedback from post-fabrication data and compatibility with older equipment. In this research, we have developed an artificial intelligence based simulator, which finds parameters for an optimal process and controls process equipment. In order to apply the control concept to all the equipment in a fabrication sequence, we have developed a prototype for a manipulator which can be installed over an existing buttons and knobs in the equipment and controls the equipment communicating with the AI over the Internet. The AI is based on the deep learning to find process parameters that will produce a device having target electrical characteristics. The proposed simulator can control existing equipment via the Internet to fabricate devices with desired performance and, therefore, it will help engineers to develop new devices efficiently and effectively.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.17-31
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• 2004

This paper proposes an algorithm for the robust transmission of video in error Prone environment using multiple description codingby optimal split of DCT coefficients and rate-distortionoptimization framework. In MDC, a source signal is split Into several coded streams, which is called descriptions, and each description is transmitted to the decoder through different channel. Between descriptions, structured correlations are introduced at the encoder, and the decoder exploits this correlation to reconstruct the original signal even if some descriptions are missing. It has been shown that the MDC is more resilient than the singe description coding(SDC) against severe packet loss ratecondition. But the excessive redundancy in MDC, i.e., the correlation between the descriptions, degrades the RD performance under low PLR condition. To overcome this Problem of MDC, we propose a hybrid MDC method that controls the SDC/MDC switching according to channel condition. For example, the SDC is used for coding efficiency at low PLR condition and the MDC is used for the error resilience at high PLR condition. To control the SDC/MDC switching in the optimal way, RD optimization framework are used. Lagrange optimization technique minimizes the RD-based cost function, D+M, where R is the actually coded bit rate and D is the estimated distortion. The recursive optimal pet-pixel estimatetechnique is adopted to estimate accurate the decoder distortion. Experimental results show that the proposed optimal split of DCT coefficients and SD/MD switching algorithm is more effective than the conventional MU algorithms in low PLR conditions as well as In high PLR condition.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.423-431
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• 2008

The control surveying which aims at identifying the coordinate system of satellite images with that of ground is a repeatedly performed essential process to produce digital ortho - photos and it acts as the main factor to increase the production cost of the photos by duplicated budgets and redundant works when executing the projects for acquiring basic geographical information from high density satellite images. During the experimentation, an application system was established for producing a stereo image chip by the analysis of DPPDB file structure, the stereo image chip was produced with SPOT and IKONOS images, the analysis of 3D modeling accuracy was performed to secure the required accuracy and to present the optimal number and deployment of the control points, and a 3D modeling was performed for new SPOT images and lastly, 3D ground coordinates were extracted by the observation of the same points through the overlapping with the new images. As the results of the research, it is proved that the stereo image chip can be used as the ground controls through the accuracy analysis between the coordinates of the images and the ground, close results were obtained between the coordinates by the ground survey and those by the 3D modeling using new images and the observation of the same points, positional changes were not found during observing the same points, and the research presented the methodology for improving the process of the control survey by showing the availability of the image controls on the stereo image chip instead of the ground controls.

• Fashion & Textile Research Journal
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• v.14 no.4
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• pp.597-606
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• 2012

To increase the productivity and product quality of customized baseball jerseys, this study developed a multi-variable system for a production process that efficiently controls diverse production management factors. The working time was measured through the establishment of a standard process where skilled workers and Chinese factory workers manufactured 5 sets of the same basic design jerseys. Based on the measured working time (1,136 seconds/per unit), the multi-variable process control system was developed, where hourly production management is possible according to the involved workers and equipment types. Each process was assigned accoding to the production management factors for a total of 28 standard processes. The processes were developed based on consideration of work characteristics according to the order of needlework of open-type set baseball jerseys with sleeves(the basic design of baseball jerseys)to result in a customized production system structure that could be set up with multi-variables. As a result, a total 12 types of systems were developed in consideration of the personnel involved and the number of equipments. The optimal production management system (with the highest efficiency compared to the number of workers)was A-2, B-1, C-1. D-2, E-2, F-1, and G-1. This system had extremely high efficiency and showed 99% assignment efficiency for the 7-person team. Though not optimal, possible process assignment for each working personnel is proposed as a reserve process in case work modification is inevitable due to malfunctions and the absence of equipments.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.73-83
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• 2004

With increasing numbers of vehicles on restricted roads, It happens that we have much wasted time and decreased average car speed. This paper proposes a new concept of coordinating green time which controls 10 traffic intersection systems. For instance, if we have a baseball game at 8 pm today, traffic volume toward the baseball game at 8 pm today, franc volume toward the baseball game will be increased 1 hour or 1 hour and 30 minutes before the baseball game. At that time we can not predict optimal green time Even though there have smart electro-sensitive traffic light system. Therefore, in this paper to improve average vehicle speed and reduce average vehicle waiting time, we created optimal green time using fuzzy rules md neural network as a preprocessing. Also, we developed an Intelligent PLC(Programmable Logic Controller) for real time traffic forecasting as a postprocesing about unexpectable conditions. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive franc light system does not consider coordinating green time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.92-101
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• 2012

In this paper, we propose a distributed transmit power control algorithm for optimal end-to-end throughput in wireless multihop networks. Considering a solidarity property of link rates consisting of a multihop link and the fact that the multihop end-to-end throughput is determined by the minimum link rate, the proposed scheme controls the transmit power to make all link rates be equal and so maximizes the end-to-end throughput of multihop link. In addition, in the proposed scheme the transmit node calculates its transmit power autonomously in a distributed manner just through the information sharing with its neighbor nodes and so decreases the information sharing overhead. Simulation results show that the proposed scheme achieves significant improvements in terms of end-to-end throughput and power consumption compared with the conventional maximum equal power allocation scheme.