• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.370-392
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• 2018

This study aims to reveal that the changes in the population and housing consumption of foreigners, which are constantly undergoing structural changes, affect both the housing market of home and host country. The cause and the change of foreigners' housing market in Seoul were analyzed to be that the foreigners' continuous inflows occurred due to the 'fixed effect of rent' on the rental market, which is different from the domestic housing market. Korean-Chinese, who tend to be circular migration, make the current concentration of the housing market. Meanwhile, Korean-Chinese, who have experienced migration from Korea, emerged as major housing consumers, causing a real estate boom in Yanji City. Housing investment by Korean-Chinese is concentrated in the 'West' from Yanbian University, closely related to the city's urban planning that affects housing supply. This transnational housing consumption of immigrants connects the housing market of home and host country, in turn, causes the filtering process in the two countries simultaneously, which results the 'transnational housing filtering process'.

• International Journal of Quality Innovation
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• v.2 no.1
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• pp.30-49
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• 2001

This paper considers a recent environment in the manufacturing process in which data in large amounts can be obtained on-line in real-time. Under this environment an on-line real-time Statistical Process Control (SPC) scheme equipped with detection of a process change, change-point estimation, and recognition of the change pattern is proposed. The proposed SPC scheme is composed of a Cusum chart, filtering methods and Akaike Information Criterion (AIC). We examine the performance of this scheme by Monte Carlo simulation and show its usefulness.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.178-180
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• 2004

In this work, we propose new method of sigma filtering for efficient filtering and preserving edge regions in DCT Domain. In block-based image compression technique, the image is first divided into non-overlapping $8{\times}8$ blocks. Then, the two-dimensional DCT is computed for each $8{\times}8$ block. Once the DCT coefficients are obtained, they are quantized using a specific quantization table. Quantization of the DCT coefficients is a lossy process, and in this step, noise is added. In this work, we combine IDCT matrix and filter matrix to a new matrix to simplify filtering process to remove noise after IDCT in spatial domain, for each $8{\times}8$ DCT coefficient block, we determine whether this block is edge or homogeneous region. If this block is edge region, we divide this $8{\times}8$ block into four $4{\times}4$ sub-blocks, and do filtering process for sub-blocks which is homogeneous region. By this process, we can remove blocking artifacts efficiently preserving edge regions at the same time.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.576-581
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• 2007

The purpose of this paper is to strengthen trust on the automated collaborative filtering system. Automated collaborative filtering system is quickly becoming a popular technique for recommendation system. This elaborative methodology contributes for reducing information overload and the result becomes index of users' preference. In addition, it can be applied to various industries in various fields. After it collaborative filtering system was developed, many researches are executed to enhance credibility and to apply in various fields. Among these diverse systems, collaborative filtering system which uses Pearson correlation coefficient is most common in many researches. In this paper, we proposed new process diagram of collaborative filtering algorithm and new factors which should improve the credibility of system. In addition, the effects and relationships are also tested.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.203-210
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• 2004

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems - content-based recommending and collaborative filtering. Collaborative filtering recommender systems have been very successful in both information filtering domains and e-commerce domains, and many researchers have presented variations of collaborative filtering to increase its performance. However, the current research on recommendation has paid little attention to the use of time related data in the recommendation process. Up to now there has not been any study on collaborative filtering to reflect changes in user interest. This paper proposes dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations. The proposed methodology detects changes in customer behavior using the customer data at different periods of time and improves the performance of recommendations using information on changes. The results of the evaluation experiment show the proposed model's improvement in making recommendations.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.439-450
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• 2010

In this paper, we propose a new idea to evaluate the prediction accuracy of user's preference generated by memory-based collaborative filtering algorithm before prediction process in the recommender system. Our analysis results show the possibility of a pre-evaluation before the prediction process of users' preference of item's transaction on the web. Classification functions proposed in this study generate a user's rating pattern under certain conditions. In this research, we test whether classification functions select users who have lower prediction or higher prediction performance under collaborative filtering recommendation approach. The statistical test results will be based on the differences of the prediction accuracy of each user group which are classified by classification functions using the generative probability of specific rating. The characteristics of rating patterns of classified users will also be presented.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1997.10a
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• pp.138-141
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• 1997

CFM(Cast Forge Method) is widely used in manufacturing industry to produce aluminium parts with good mechanical properties and low production cost. CFM is the process which produces a final products by forging from the initial billet by casting. The study on this paper covers the automatic design method which finds a pertinent shape for initial billet using Fast Fourier Transform, low-pass frequency filtering and FEM simulation of the nonisothermal forging process by DEFORM. These works will give us an information to enhance the low strength of a aluminium casting.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.59-65
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• 2008

This paper proposed a H.264 deblocking filter for the portable low-power multimedia. In H.264 deblocking filter, total 8 input pixels in filtering operations needs own filtering operation process respectively, and each filtering process has common structures for each filtering operation. By sharing common filter coefficients and registers, we have designed and implemented an smaller gated module, and moreover filtering operations are skipped on some or whole pixels what if we use some specific condition to operate filtering modules that need lots of operations. In the core of filtering modules, we achieve 33.31% and 10.85% gate count reduction compared with those of filtering modules of the conventional deblocking filter papers. The proposed low-power deblocking filter is implemented by using samsung 0.35um standard cell library technology, the maximum operationh frequency is 108MHz, and the maximum throughput is 33.03 frames/s with CCIR601 image format.

• Journal of environmental and Sanitary engineering
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• v.23 no.2
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• pp.55-63
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• 2008

All over the world, the existing process of water purification needs more flocculants and chlorine due to a gradual decline in the quality of source water. Therefore, the problem of the remaining aluminium and DBPs in purified water is on the rise. To solve this problem, the process of membrane filter has recently come into the spotight. This study reaches the following conclusions concerning TMP variation in order to solve the dropping of flux throgh a membrane filter when operating a membrane filter system in the process of water purification. 1. In case that a cohesion-precipitation process was introduced to pre-treatment of a membrane filter, initial TMP was very satisfactory(0.27kg/cm) in producing the constantly safe quality of water, $0.04{\sim}0.1$(mean 0.05) NTU by pouring 2mg/l of PACI(10% $Al_2O_3$) used for the existing process of water purification in high-density turbidity at a dry or flood season and at occurrence of high algae. 2. As flux increased at 0.5m/day.m, TMP increased 0.05 kgf/cm. 3. As filtering, operation mode of PVDF MF membrane filtering was 48 minutes and 1 cycle of back washing was 42 minutes, flux was increased 1.5m/day.m and TMP increased $0.25{\sim}0.27kgf/cm$. Without back washing, TMP increased 0.03 kgf/cm per a cycle.

• The Journal of the Korea Contents Association
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• v.7 no.8
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• pp.50-58
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• 2007

We design a filtering management scheme with synchronization function under a realtime RFID middleware system for larger-scale data processing. The application interface(AI) is to support a various access protocol, HTTP, XML, JMS, and SOAP for the RFID applications. Generally, the synchronization problem is occurred in multiple accessing of clients for single filtering file. In this paper, we implement a filtering management scheme supporting the synchronization using the filter management process, and then demonstrate the RFID middleware filtering scheme.