• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4268-4290
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• 2015

Future mobile communications face enormous challenges as traditional voice services are replaced with increasing mobile multimedia and data services. To address the vast data traffic volume and the requirement of user Quality of Experience (QoE) in the next generation mobile networks, it is imperative to develop efficient content distribution technique, aiming at significantly reducing redundant data transmissions and improving content delivery performance. On the other hand, in recent years cloud computing as a promising new content-centric paradigm is exploited to fulfil the multimedia requirements by provisioning data and computing resources on demand. In this paper, we propose a cooperative caching framework which implements State based Content Distribution (SCD) algorithm for future mobile networks. In our proposed framework, cloud service providers deploy a plurality of cloudlets in the network forming a Distributed Cloud Service Network (DCSN), and pre-allocate content services in local cloudlets to avoid redundant content transmissions. We use content popularity and content state which is determined by content requests, editorial updates and new arrivals to formulate a content distribution optimization model. Data contents are deployed in local cloudlets according to the optimal solution to achieve the lowest average content delivery latency. We use simulation experiments to validate the effectiveness of our proposed framework. Numerical results show that the proposed framework can significantly improve content cache hit rate, reduce content delivery latency and outbound traffic volume in comparison with known existing caching strategies.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.4
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• pp.281-290
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• 2013

The IT asset is a core part that supports the management objective of an organization, and the fast settlement of the IT asset fault is very important. In this study, a fault recovery prediction technique is proposed, which uses the existing fault data to address the IT asset fault. The proposed fault recovery prediction technique is as follows. First, the existing fault recovery data were pre-processed and classified by fault recovery type; second, a rule was established for the keyword mapping of the classified fault recovery types and reported data; and third, a machine learning process that allows the prediction of the fault recovery method based on the established rule was presented. To verify the effectiveness of the proposed machine learning process, company A's 33,000 computer fault data for the duration of six months were tested. The hit rate for fault recovery prediction was approximately 72%, and it increased to 81% via continuous machine learning.

• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1355-1369
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• 2021

This study improved the algorithm for the road ice prediction algorithm and analyzed the prediction rate when comparing actual field measurement data and algorithm prediction value. For analysis, road and weather conditions were measured in Geumdong-ri, Sinbuk-myeon, Pocheon-si. First algorithm selected previous research result algorithm. And the 4th algorithm was improved according to the actual freezing conditions and measured values. Finally, five algorithms were developed: freezing by condensation, freezing by precipitation, freezing by snow, continuous freezing, and freezing by wind speed. When forecasting using an algorithm at the Pocheon site, the freezing hit rate was improved to 93.2%. When calculating the combination ratio for the algorithm. the algorithm for freezing due to condensation and the continuation of the frozen state accounted for 95.7%.

• The International Journal of Costume Culture
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• v.4 no.2
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• pp.77-85
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• 2001

The purpose of this study was to classify the somatotype around a upper body of 30's men. The subjects were 202 working men aged from 30 to 39 and the data of 33 items including computed items were analysed by factor analysis and cluster analysis. Re results were as follows: As a factor of somatotype in evaluating males in 30's, the horizontal area represented the chest circumference at scye and the breadth items, the vortical region indicated hit length posterior, front length, back length, the breadth difference and the length difference. The somatotype by cluster analysis was classified with 3 type. Type I as the Roher's index 1.21 indicating the smallest in the circumference and weight item was classified as the thin and long featuring bending somatotype. Type 2 with the Rohrer's index 1.35 showing the mid-group between type 1 and 3 had the highest distribution rate as the balanced featuring the standard somatotype. Type 3 as the rohrer's index 1.40 was the largest physical condition group in the obesity featuring the turning over somatotype.

• Journal of the Korean Society of Costume
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• v.53 no.6
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• pp.117-130
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• 2003

The purpose of this study is to provide the basic data on the development of ready-to-wear clothing for the elderly women as the population of the elderly has been constantly increasing as well as the purchasing power of the aged. The body measurements of 318 elderly women were taken. whose ages were over 60 years and enrolled in colleges for the elderly. sports centers. or business sites in Seoul and the neighboring districts. A total of 39 features in the lower body were used for the anthropometric measurement and analysis. The results of the study are as follows: 1. Indices of height and weight were used for factor analysis. cluster analysis, and discriminant analysis in order to 'classify lower body somatotype according to shape, excluding size factors. From the results of the factor analysis. the 5 factors showed the cumulative sum of square at 75.63%. 2. Somatotype were classified into two types according to a cluster analysis using height and weight dices. Type 1 is the group is relatively tall and has somewhat fat lower limbs. Type 2 is considered fat and has obesity factors around waist and abdomen area. The hit rate for the classified two groups showed the result at 95.9%.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.945-951
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• 2008

In this paper, a new high performance data cache scheme that improves exploitation of both the spatial and temporal locality is proposed. The proposed data cache consists of a hardware prefetch unit and two sub-caches such as a direct-mapped (DM) cache with a large block size and a fully associative buffer with a small block size. Spatial locality is exploited by fetching and storing large blocks into a direct mapped cache, and is enhanced by prefetching a neighboring block when a DM cache hit occurs. Temporal locality is exploited by storing small blocks from the DM cache in the fully associative buffer according to their activity in the DM cache when they are replaced. Experimental results on Spec2000 programs show that the proposed scheme can reduce the average miss ratio by $12.53%\sim23.62%$ and the AMAT by $14.67%\sim18.60%$ compared to the previous schemes such as direct mapped cache, 4-way set associative cache and SMI(selective mode intelligent) cache[8].

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.121-126
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• 2009

Video poxy server which is located near clients can store the frequently requested video data in storage space in order to minimize initial latency and network traffic significantly. However, due to the limited storage space in video proxy server, an appropriate deletion algorithm is needed to remove the old video data which is not serviced for a long time. Thus, we propose an efficient video data deletion algorithm for video proxy server. The proposed deletion algorithm removes the video which has the lowest request possibility based on the user access patterns. In our algorithm, we arrange the videos which are stored in video proxy server according to the requested time sequence and then, select the video which has the oldest requested time. The selected video is partially removed in order to free up storage space in video poky server. The simulation results show that the proposed algorithm performs better than other algorithms in terms of the block hit rate and the number of block deletion.

• The Research Journal of the Costume Culture
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• v.5 no.3
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• pp.1-25
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• 1997

The consumers, who are characterized by gathering a wide scope of information and by putting into action immediately, have come to the new group searching for emotion and have played a leading role of market. The characgeristics of consumers are the fact that they have followed the street fashion with no-concept, independent of the trends which the brand has provide for consumers. Therefore it leads to a big gap between the fashion information for enterprises and market formation for consumer class. The principal purpose of this paper is to get closer the distance between the information which is used in merchandise plan and real market for consumers, and to suggest the new direction of information management system in order to enhance the hit rate of merchandise plan. The results are as follows : (1) It is shown the enterprises should divide the information data between fashion information and market information, and understand the mutual relationship of them, and regard the statistical data related on the change of sensitivity and desire in market specialized in attributes of street fashion as the emotional expression\`s view, and manage them by the feedback style. (2) It is shown that enterprises should fully understand the fashion factors in the line of fashion stream with the independence of theme in order to plan the merchandise effectively for market which are specialized in the duality that it has both conservation and innovation at the same time, and detect their change. (3) It is shown that in order to predict exactly, enterprises should reflect the statistical data and the emotional factors in planning the merchandise, bring up the systematic organization, expert system. (4) It is also shown that enterprises should make an effort to pursuit the discriminated brand through the feedback management in which the consumer\`s lasting desires are reflected.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.113-120
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• 2010

Video proxy server which is located near clients can store the frequently requested video data in storage space in order to minimize initial latency and network traffic significantly. However, due to the limited storage space in video proxy server, an appropriate video selection method is needed to store the videos which are frequently requested by users. Thus, we present a time constraint multiple access technique to efficiently store the video in video proxy server. If the video is requested by user, it is temporarily stored during the predefined interval and then, delivered to the user. A video which is stored is deleted or moved into the storage space of video proxy server depending on the request condition. In addition, we propose a video deletion method in video proxy server for newly stored video data. The simulation results show that the proposed method performs better than other methods in terms of the block hit rate and the number of block deletion.