• Journal of Power System Engineering
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• v.12 no.4
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• pp.18-25
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• 2008

This paper investigated the new calibration algorithm of a straight-type five-hole pressure probe necessary for calculating three-dimensional flow velocity components. The new data reduction method Includes a look-up, a geometry transformation such as the translation and reflection of nodes, and a binary search algorithm. This new calibration map was applied up to the application angle, ${\pm}55^{\circ}$ of a probe. As a result, this data reduction method showed a perfect performance without any kind of interpolation errors In calculating yaw and pitch angle from the calibration map.

• Journal of Fisheries and Marine Sciences Education
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• v.10 no.1
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• pp.63-68
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• 1998

The microbubble splits injection system are improved for the enhancement efficiency of viscous frictional drag reduction. It was confirmed that the experimental results is effective more than Mercle's[7] using the present system in the comparisons. And the new experimental equation is derived to get viscous frictional drag reduction useful for the present experimental data. The new experimental equation approaches Mercle's[7] experimental data wel.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.57-62
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• 2005

In spite of many advantages of OFDM, a major drawback for implementation is a non-linear distortion in the HPA due to a high PAPR problem. In this paper, the Complementary Clipping Transform technique (CCT) for the PAPR reduction of OFDM system is analyzed for the QPSK and QAM mapping data. BER performance and PSD in front of HPA and after HPA are analytically demonstrated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.13-19
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• 2006

The instance-based learning is a machine learning technique that has proven to be successful over a wide range of classification problems. Despite its high classification accuracy, however, it has a relatively high storage requirement and because it must search through all instances to classify unseen cases, it is slow to perform classification. In this paper, we have presented a new data reduction method for instance-based learning that integrates the strength of instance partitioning and attribute selection. Experimental results show that reducing the amount of data for instance-based learning reduces data storage requirements, lowers computational costs, minimizes noise, and can facilitates a more rapid search.

• Journal of Industrial Convergence
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• v.21 no.2
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• pp.125-131
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• 2023

In this paper, research was conducted to solve the problem of reducing the dimming level and flicker that occurs in the visible light communication system. Visible light communication is a convergence technology that provides both communication and lighting, and must satisfy not only communication performance but also lighting performance. However, since the existing data transmission method transmits without considering the transmission data sequence, it reduces the dimming level and causes a flicker phenomenon. To solve this problem, in this paper, the Dimming Improvement and Flicker Reduction Mapping technique was studied. Existing systems simply transmitted data of '0' and '1', but in this system, original data transmission channels and DIFR (Dimming Improvement and Flicker Reduction) transmission channels are assigned to RGB channels. Original data is allocated to the R channel and original data or inverse original data is allocated to the DIFR-G channel, and the DIFR-B channel maintains the maximum dimming level by transmitting through the logical operation of the R channel and the G channel. At the same time, the flicker phenomenon is prevented by preventing continuous occurrence of 'OFF' patterns. Through this, we proposed an adaptive data allocation algorithm that can faithfully play a role as a light as well as a communication function.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.301-308
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• 2009

In the modern life, machines are used for various areas in industries as the advance of science and industrial development has proceeded. In many machines, the rotating machines play an important role in many processes. Therefore, the development of fault diagnosis and monitoring system for rotating machines is required. An ubiquitous sensor network (USN) is a combination of the key computer science and engineering area technology including the wireless network, embedded system hardware and software, communication, real-time system, etc. It collects environmental information to realize a variety of functions. In this work, a data reduction algorithm for USN based remote fault diagnostic system which can be easily applied to previously built factories is proposed. To verify the feasibility of the proposed scheme, some simulations and experiments are executed.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.133-144
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• 2008

Clusters have become a popular alternative for building high-performance parallel computing systems. Today's high-performance system area network (SAN) protocols such as VIA and IBA significantly reduce user-to-user communication latency by implementing protocol stacks outside of operating system kernel. However, emerging parallel applications require a significant improvement in communication latency. Since the time required for transferring data between host memory and network interface (NI) make up a large portion of overall communication latency, the reduction of data transfer time is crucial for achieving low-latency communication. In this paper, Eager Data Transfer (EDT) mechanism is proposed to reduce the time for data transfers between the host and network interface. The EDT employs cache coherence interface hardware to directly transfer data between the host and NI. An EDT-based network interface was modeled and simulated on the Linux-based, complete system simulation environment, Linux/SimOS. Our simulation results show that the EDT approach significantly reduces the data transfer time compared to DMA-based approaches. The EDTbased NI attains 17% to 38% reduction in user-to-user message time compared to the cache-coherent DMA-based NIs for a range of message sizes (64 bytes${\sim}$4 Kbytes) in a SAN environment.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.56-64
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• 2006

This paper shows the development process of a straight-type five-hole pressure probe for measuring three-dimensional flow velocity components. The data reduction method using a bi-cubic curve-fitting program in a new calibration map was introduced in this study. This new calibration map can be applied up to the application angle, ${\pm}55^{\circ}$ of a probe. As a result, for the application angle of ${\pm}45^{\circ}$, an error for yaw and pitch angles appeared from $-1.76^{\circ}\;to\;1.83^{\circ}$ and from $-1.91^{\circ}\;to\;1.75^{\circ}$, respectively. Moreover, an error for a vector magnitude and a static pressure compared with a dynamic one showed from -7.83% to 4.87% and from -0.73 to 0.77, respectively. Even though this data reduction method showed unsatisfactory errors in a vector magnitude, it resulted in an easy and simple application method. Especially, when it was applied to an actual flow field including a swirling flow, a good result came out on the whole. However, in order to obtain a better result, it is thought that a more sophisticated interpolation method needs to be introduced.

• Journal of Drive and Control
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• v.18 no.1
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

• 정보저장시스템학회:학술대회논문집
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• 2005.10a
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• pp.83-87
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• 2005

Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time in. Today any data storage system can not satisfy these conditions, but holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System architecture without mechanical actuating pare is possible, so fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this paper, to correct errors of binary data stored in holographic digital data storage system, find cluster centers using clustering algorithm and reduce intensities of pixels around centers. We archive the procedure by two algorithms of C-mean and subtractive clustering, and compare the results of the two algorithms. By using proper clustering algorithm, the intensity profile of data page will be uniform and the better data storage system can be realized.