• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.2
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• pp.471-476
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• 2006

Chongmyung-tang(CMT, 聰明湯), oriental herbal medicine which consists of Polygaglae Radix(遠志), Acori Graminei Rhizoma(石菖蒲) and Hoelen(白茯神) has effect on amnesia, dementia. In order to evaluate effect of CMT on memory and learning in mice, CMT extract was used for studies. This paper describes the effects of CMT extract on memory and learning processes by using the passive and active avoidance performance tests, novel object recognition task and water maze task. The CMT extract ameliorated the memory retrieval deficit induced by ethanol in the passive avoidance responses but did not affect ambulatory activity of normal mice. These results suggest that CMT has an ameliorating effect on memory retrieval impairment. CMT extract decreased spontaneous motor activity(SMA) in the latter sessions of memory registration in active avoidance responses. These results suggest that CMT has partly transquilizing or antianxiety effects. In novel object recognition task to measure visual recognition memory, CMT-administered mice enhanced in long term memory for 1-3 days. In water maze task to measure spatial learning, which requires the activation of NMDA receptors in the hippocampus, spatial learning in CMT-administered mice was faster than in wild-type mice. These results suggest that CMT enhances memory and activates NMDA receptors.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.419-434
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• 2020

The purpose of the study is to design and propose metadata standard for building AI training dataset of landmark images. In order to achieve the purpose, we first examined and analyzed the state of art of the types of image retrieval systems and their indexing methods, comprehensively. We then investigated open training dataset and machine learning tools for image object recognition. Sequentially, we selected metadata elements optimized for the AI training dataset of landmark images and defined the input data for each element. We then concluded the study with implications and suggestions for the development of application services using the results of the study.

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.19-26
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• 2010

The most critical element in the real-time operation of RFID application programs that are suitable for the mobile environment is the RFID middleware, made exclusively for mobile handsets, which processes collected data on a real-time basis and sends only the useful information to the application client. In this paper, we intend to design and implement the Pet management system for optimized mobile RFID middleware that supports real-time data processing. The proposed Pet management system consists of registration module, retrieval module, communication module, and display module in order to display retrieval result from server. Also, the captured data in the PDA is transmitted to the server and another client system using the mobile application interface that supports the SOAP application access protocol.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.100-105
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• 2009

In this paper, we Propose a browsing system to reduce the contents retrieval time in the personalized broadcasting system. For this purpose, we add a subgenre table between Classification DS and Summarization DS of MPEG-7 MDS. The subgenre includes a subgenre list to shorten the searching time of contents which we want to find. In addition we divide metadata into event and object using Summarization DS of the MPEG-7 MDS. In this way, the hierarchical browsing of broadcasting contents is made possible. This structure may reduce the complexity of search by storing event and object separately. Our simulation results show that the search time of the proposed system is shorter than that of the previous works.

• ETRI Journal
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• v.35 no.4
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• pp.687-696
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• 2013

The development of proxy caching is essential in the area of video-on-demand (VoD) to meet users' expectations. VoD requires high bandwidth and creates high traffic due to the nature of media. Many researchers have developed proxy caching models to reduce bandwidth consumption and traffic. Proxy caching keeps part of a media object to meet the viewing expectations of users without delay and provides interactive playback. If the caching is done continuously, the entire cache space will be exhausted at one stage. Hence, the proxy server must apply cache replacement policies to replace existing objects and allocate the cache space for the incoming objects. Researchers have developed many cache replacement policies by considering several parameters, such as recency, access frequency, cost of retrieval, and size of the object. In this paper, the Weighted-Rank Cache replacement Policy (WRCP) is proposed. This policy uses such parameters as access frequency, aging, and mean access gap ratio and such functions as size and cost of retrieval. The WRCP applies our previously developed proxy caching model, Hot-Point Proxy, at four levels of replacement, depending on the cache requirement. Simulation results show that the WRCP outperforms our earlier model, the Dual Cache Replacement Policy.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.823-828
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• 2003

The main objective of this paper is to provide a methodology of feature extraction using shape of image objects for content-based image retrieval. The shape of most real-life objects is irregular, and hence there is no universal approach to quantify the shape of an arbitrary object. In particular. electronic catalogs contain many image objects for their products. In this paper, we perform feature extraction based on individual objects in images rather than on the whole image itself, since our method uses a shape-based approach of objects using RLC lines within an image. Experiments show that shape parameters distinctly represented image objects and provided better classification and discrimination among image objects in an image database compared to Texture.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1418-1432
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• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.7
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• pp.677-684
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• 2016

With the increase of multimedia information such as image, researches on extracting high-level semantic information from low-level visual information has been realized, and in order to automatically generate this kind of information. Various technologies have been developed. Generally, image retrieval is widely preceded by comparing colors and shapes among images. In some cases, images with similar color, shape and even meaning are hard to retrieve. In this article, in order to retrieve the object in an image, technical value of middle level is converted into meaning value of middle level. Furthermore, to enhance accuracy of segmentation, K-means algorithm is engaged to compute k values for various images. Thus, object retrieval can be achieved by segmented low-level feature and relationship of meaning is derived from ontology. The method mentioned in this paper is supposed to be an effective approach to retrieve images as required by users.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1033-1043
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• 2000

Recently as the user request on NoD (News-on-Demand) is largely increasing, there are a lot of researches to fulfill it. However, because of short life-cycle of new video data and periodical change of video data depending on anchor, it is difficult to apply the conventional video storage techniques to NOD applications directly. For this, we design and implement low-level storage manager for efficient storage and retrieval of multimedia data in NOD Services. Our low-level storage manager not only efficiently sotres video stream dat of new video itself, but also handles its index information. It provides an inverted file method for efficient text-based retrieval and an X-tree index structure for high-dimensional feature vectors. In addition, our low-level storage manager provides some application program interfaces (APIs) for storing video objects itself and index information extracted from hierarchial new video and some APIs for retrieving video objects easily by using cursors. Finally, we implement our low-level storage manager based on SHORE (Scalable Heterogeneous Object REpository) storage system by sunig a standard C++ language under UNIX operating system.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.581-586
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• 2004

In this paper, we proposed a content-based image retrieval using a color feature for central region and its optimized comparing bin method. Human's visual characteristic is influenced by existent of central object. So we supposed that object is centrally located in image and then we extract color feature at central region. When the background of image is simple, the retrieval result can be bad affected by major color of background. Our method overcome this drawback as a result of the human visual characteristic. After we transform Image into HSV color space, we extract color feature from the quantized image with 16 level. The experimental results showed that the method using the eight high rank bin is better than using the 16 bin The case which extracts the feature with image's central region was superior compare with the case which extracts the feature with the whole image about 5%.