• Journal of the Korea Institute of Information and Communication Engineering
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• 제17권5호
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• pp.1129-1137
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• 2013

Cloud storage system that cloud computing providers provides large amounts of data storage and processing of cloud computing is a key component. Large vendors (such as Facebook, YouTube, Google) in the mass sending of data through the network quickly and easily share photos, videos, documents, etc. from heterogeneous devices, such as tablets, smartphones, and the data that is stored in the cloud storage using was approached. At time, growth and development of the globally data, the cloud storage business model emerging is getting. Analysis new network storage cloud storage services concepts and technologies, including data manipulation, storage virtualization, data replication and duplication, security, cloud computing core.

• Transactions of the Korean Society of Mechanical Engineers B
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• 제21권10호
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• pp.1314-1325
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• 1997

Experiments have been conducted to determine the flow and heat transfer characteristics for a two-dimensional turbulent wall attaching offset jet at different oblique angles to a flat surface. The distributions of the wall static pressure coefficient and time-averaged reattachment position for various offset ratios and oblique angles have been measured. The local Nusselt number distributions on the plate surface were also measured using liquid crystal as a temperature indicator. The new hue-capturing technique utilizing a true color image processing system was used to accurately determine the temperature of the liquid crystal. The experiments were carried out at Reynolds number, Re (based on D) of from 7300 to 21,300 with offset ratio, H/D from 2.5 to 10, and oblique angle, .alpha. from 0 deg. to 400 deg..

• Journal of KIISE:Computer Systems and Theory
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• 제34권8호
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.

• Applied Microscopy
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• 제40권4호
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• pp.177-183
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• 2010

A focused ion beam (FIB) system produces a beam of positive ions (usually gallium) which are heavier than electrons and can be focused by electrostatic lenses into a spot on the specimen. With its ability milling of the specimen material by 10 to 100 nm with each pass of the beam, FIB is widely adopted in materials science, semiconductor industry, and ceramics research. Recently, FIB has been increasingly employed in the field of biomedical sciences. Here we provide a brief introduction to FIB and its applications for a wide variety of biomedical research. The surface of specimen can be in situ processed and quasi-real time visualized by two beam combination of FIB and field emission scanning electron microscope (FESEM). Due to its milling process, internal structures can be exposed and analyzed: yeast cells, fungus-inoculated wheat leaf, mannitol particles in inhalation aerosols, and oyster shell. Serial blockface tomography with the system kindles 3-dimensional reconstruction researches in the realm of nervous system and life sciences. Two-beam system of FIB/FESEM is a versatile tool to be utilized in the biomedical sciences, especially in 3-dimensional reconstruction studies.

• Progress in Medical Physics
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• 제26권1호
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Radiation Oncology Journal
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• 제20권4호
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• pp.375-380
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• 2002

Purpose : To develop a practical film dosimetry system for routine Quality Assurance (QA). Materials and Methods :An One Click Film (OCF) Dosimetry system was designed to perform swift routine QA with functions including automatic fog value elimination, angle adjustment, automatic symmetry calculation, and realtime profile generation with the ability to display realtime three-dimensional dose distributions. Results : The most frequently used functions for routine QA, such as the elimination of the fog value, conversion into an H&D curve, symmetry, and isodose distribution, can be achieved with only one click. Conclusion : Reliable results were achieved with the OCF dosimetry with simpler steps than other commercially available film dosimetry systems for routine QA. More research on the refined user interface will make this system be clinically useful.

• Journal of the Korea Society of Computer and Information
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• 제16권7호
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• pp.149-156
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• 2011

This paper proposes the effective edge selection algorithm for the rapid processing time and low memory usage of efficient graph-based image segmentation on mobile device. The graph-based image segmentation algorithm is to extract objects from a single image. The objects are consisting of graph edges, which are created by information of each image's pixel. The edge of graph is created by the difference of color intensity between the pixel and neighborhood pixels. The object regions are found by connecting the edges, based on color intensity and threshold value. Therefore, the number of edges decides on the processing time and amount of memory usage of graph-based image segmentation. Comparing to personal computer, the mobile device has many limitations such as processor speed and amount of memory. Additionally, the response time of application is an issue of mobile device programming. The image processing on mobile device should offer the reasonable response time, so that, the image segmentation processing on mobile should provide with the rapid processing time and low memory usage. In this paper, we demonstrate the performance of the effective edge selection algorithm, which effectively controls the edges of graph for the rapid processing time and low memory usage of graph-based image segmentation on mobile device.

• Journal of the Institute of Convergence Signal Processing
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• 제9권4호
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• pp.272-279
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• 2008

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see realtime operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST company. Thus, our algerian in the paper can be useful in PMP(portable multimedia player) or other portable players.

• Proceedings of the Korea Contents Association Conference
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• 한국콘텐츠학회 2009년도 춘계 종합학술대회 논문집
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• pp.17-22
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• 2009

DaVinci processors are popular media processors for implementing embedded multimedia applications. They support dual core architecture: ARM9 core for video I/O handling as well as system management and peripheral handling, and DSP C64+ core for effective digital signal processing. In this paper, we propose our efforts for optimal implementation of object tracking algorithm in DaVinci-based smart camera which is being designed and implemented by our laboratory. The smart camera in this paper is supposed to support object detection, object tracking, object classification and detection of intrusion into surveillance regions and sending the detection event to remote clients using IP protocol. Object tracking algorithm is computationally expensive since it needs to process several procedures such as foreground mask extraction, foreground mask correction, connected component labeling, blob region calculation, object prediction, and etc. which require large amount of computation times. Thus, if it is not implemented optimally in Davinci-based processors, one cannot expect real-time performance of the smart camera.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.171-179
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• 2013

Recognition and image processing technology depends on illumination variation. One of the most important factors is the parameters of algorithms. When it comes to select these values, the system has different types of recognition accuracy. In this paper, we propose performance improvement of the eye tracking system that depends on some environments such as, people, location, and illumination. Optimized threshold parameter was decided by using reinforcement learning. When the system accuracy goes down, reinforcement learning used to train the value of parameters. According to the experimental results, the performance of eye tracking system can be improved from 3% to 14% by using reinforcement learning. The improved eye tracking system can be effectively used for human-computer interaction.